From 20d111c0830239b7b19ba787479a00fdffb90b07 Mon Sep 17 00:00:00 2001
From: initial-d <duyimin123@163.com>
Date: Sat, 31 Oct 2026 19:19:15 +0800
Subject: [PATCH 1/4] Stream quantized files and measure large trained-table
 capacity and lookup

---
 tests/test_quantized_capacity.py      |  66 +++++
 tests/test_quantized_memory.py        |  51 +++-
 tools/benchmark_quantized_capacity.py | 357 ++++++++++++++++++++++++++
 tools/quantized_memory.py             | 150 +++++++++--
 4 files changed, 606 insertions(+), 18 deletions(-)
 create mode 100644 tests/test_quantized_capacity.py
 create mode 100644 tools/benchmark_quantized_capacity.py

diff --git a/tests/test_quantized_capacity.py b/tests/test_quantized_capacity.py
new file mode 100644
index 0000000..2374335
--- /dev/null
+++ b/tests/test_quantized_capacity.py
@@ -0,0 +1,66 @@
+"""Small deterministic correctness fixtures, never compression/quality evidence."""
+from argparse import Namespace
+import hashlib
+import json
+from pathlib import Path
+import shutil
+import subprocess
+import sys
+import tempfile
+import unittest
+
+try:
+    import numpy as np
+except ImportError:
+    np = None
+
+
+@unittest.skipUnless(np is not None and shutil.which("cc"), "NumPy and C compiler required")
+class CapacityTest(unittest.TestCase):
+    def test_fresh_worker_oracles_full_verification_and_direct_control(self):
+        from tools.benchmark_quantized_capacity import build, verify, query, prepare_oracle
+        with tempfile.TemporaryDirectory() as tmp:
+            root = Path(tmp)
+            library = root / ("rows.dylib" if sys.platform == "darwin" else "rows.so")
+            native = Path(__file__).resolve().parents[1] / "native/meft_rows.c"
+            subprocess.run(["cc", "-std=c11", "-O2", "-fPIC", "-dynamiclib" if sys.platform == "darwin" else "-shared",
+                            str(native), "-lz", "-o", str(library)], check=True, capture_output=True)
+            rows = np.array([[127., .5, -.5], [1., .3, -.2], [0., -0., 0.], [2., .6, -.4]], dtype="<f4")
+            source = root / "source.f32"
+            source.write_bytes(rows.tobytes())
+            ids = [3, 1, 0, 2] * 128
+            manifest = dict(shape=list(rows.shape), cases=[dict(name="fixture", queries=[dict(
+                ids=ids, sha256=hashlib.sha256(rows[ids].tobytes()).hexdigest())])])
+            oracle = prepare_oracle(source, manifest, 3)
+            oracle_file = root / "oracle.json"
+            oracle_file.write_text(json.dumps(oracle))
+            cfg = Namespace(source=source, dim=3, native_library=library, chunk_rows=2,
+                            cache_bytes=128, max_block_bytes=12, repeat=2, case="fixture",
+                            query_manifest=oracle_file, variant_label=None)
+            for encoding in ("fp32", "fp16", "int8"):
+                for backend in ("raw", "native"):
+                    cfg.encoding, cfg.backend = encoding, backend
+                    cfg.bundle = root / (encoding + backend)
+                    cfg.worker_report = root / "worker.json"
+                    build(cfg)
+                    verify(cfg)
+                    verified = json.loads(cfg.worker_report.read_text())
+                    self.assertEqual(verified["rows_verified"], len(rows))
+                    self.assertTrue(verified["all_original_ids_encoded_byte_exact"])
+                    if encoding == "fp32":
+                        self.assertEqual(verified["relative_frobenius"], 0)
+                    query(cfg)
+                    checked = json.loads(cfg.worker_report.read_text())
+                    self.assertTrue(checked["all_query_bytes_exact"])
+                    self.assertEqual(checked["query_rows"], 512)
+                    self.assertEqual(len(checked["first_trace"]["wall"]["samples_ms"]), 1)
+            cfg.backend, cfg.encoding = "direct", "fp32"
+            query(cfg)
+            self.assertTrue(json.loads(cfg.worker_report.read_text())["all_query_bytes_exact"])
+            manifest["cases"][0]["queries"][0]["sha256"] = "bad"
+            with self.assertRaisesRegex(AssertionError, "old FP32"):
+                prepare_oracle(source, manifest, 3)
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/tests/test_quantized_memory.py b/tests/test_quantized_memory.py
index 83afea1..722d5e9 100644
--- a/tests/test_quantized_memory.py
+++ b/tests/test_quantized_memory.py
@@ -1,5 +1,6 @@
 """Codec/forwarding correctness fixtures; not compression/quality evidence."""
 from argparse import Namespace
+import hashlib
 from pathlib import Path
 import shutil
 import subprocess
@@ -67,6 +68,34 @@ def test_failed_export_removes_only_new_owned_directory(self):
                 pack_quantized(rows, target, "fp16")
             self.assertEqual(keep.read_text(), "existing")
 
+    def test_file_export_streams_chunks_and_checks_original_id_hashes(self):
+        from tools.quantized_memory import pack_quantized_file, encode_rows, decode_rows
+        rows = np.array([[127., .5, -.5], [1., .3, -.2], [0., -0., 0.],
+                         [2., .6, -.4], [1., .3, -.2]], dtype="<f4")
+        with tempfile.TemporaryDirectory() as tmp:
+            source = Path(tmp) / "source.f32"
+            source.write_bytes(rows.tobytes())
+            for encoding in ("fp32", "fp16", "int8"):
+                with patch("tools.quantized_memory.encode_rows", wraps=encode_rows) as encoder:
+                    target = Path(tmp) / encoding
+                    meta = pack_quantized_file(source, target, 3, encoding, native=False, chunk_rows=2)
+                    self.assertEqual([len(call.args[0]) for call in encoder.call_args_list], [2, 2, 1])
+                encoded = encode_rows(rows, encoding)
+                self.assertEqual((target / "table.rows").read_bytes(), encoded.tobytes())
+                self.assertEqual(meta["source_float32_sha256"], hashlib.sha256(rows.tobytes()).hexdigest())
+                expected = decode_rows(encoded, 3, encoding).tobytes()
+                self.assertEqual(meta["decoded_float32_sha256"], hashlib.sha256(expected).hexdigest())
+            bad = Path(tmp) / "bad"
+            source.write_bytes(rows.tobytes() + b"x")
+            with self.assertRaisesRegex(ValueError, "complete"):
+                pack_quantized_file(source, bad, 3, "int8")
+            self.assertFalse(bad.exists())
+            rows[-1, 1] = np.inf
+            source.write_bytes(rows.tobytes())
+            with self.assertRaisesRegex(ValueError, "finite"):
+                pack_quantized_file(source, bad, 3, "int8", chunk_rows=2)
+            self.assertFalse(bad.exists())
+
 
 @unittest.skipUnless(np is not None and shutil.which("cc"), "NumPy and native C compiler required")
 class QuantizedNativeTest(unittest.TestCase):
@@ -101,26 +130,42 @@ def test_original_ids_padding_repeated_queries_and_scale_sensitive_dedup(self):
                         for _ in range(2):
                             self.assertEqual(reader.encoded_rows(ids).tobytes(), encoded[ids].tobytes())
                             self.assertEqual(reader.gather(ids).tobytes(), rounded[ids].tobytes())
+                            out = np.empty((len(ids), 2), dtype="<f4")
+                            scratch = np.empty((len(ids), reader.width), dtype="u1")
+                            reader.gather_into(ids, out, encoded_scratch=scratch)
+                            self.assertEqual(out.tobytes(), rounded[ids].tobytes())
                         self.assertEqual(reader.gather([]).shape, (0, 2))
                         for bad in ([-1], [4], [1.5], [[0]]):
                             with self.assertRaises(ValueError):
                                 reader.gather(bad)
+                            with self.assertRaises(ValueError):
+                                reader.gather_into(bad, out)
+                        with self.assertRaises(ValueError):
+                            reader.gather_into(ids, out[:, :1])
+                        out.flags.writeable = False
+                        with self.assertRaises(ValueError):
+                            reader.gather_into(ids, out)
                     with self.assertRaises(ValueError):
                         reader.gather(ids)
 
     def test_mark_compact_forwards_entire_quantized_representative(self):
-        from tools.quantized_memory import pack_quantized, QuantizedRows, encode_rows, decode_rows
+        from tools.quantized_memory import pack_quantized_file, QuantizedRows, encode_rows, decode_rows
         rows = np.array([[0., 0.], [1., .3], [2., .6]], dtype=np.float32)
         mapping = [0, 1, 1]
         with tempfile.TemporaryDirectory() as tmp:
             target = Path(tmp) / "shared"
-            meta = pack_quantized(rows, target, "int8", representatives=mapping,
-                                  row_order=[0, 1, 2], max_block_bytes=12)
+            source = Path(tmp) / "source.f32"
+            source.write_bytes(rows.tobytes())
+            meta = pack_quantized_file(source, target, 2, "int8", representatives=mapping,
+                                       row_order=[0, 1, 2], max_block_bytes=12, chunk_rows=1)
             self.assertEqual(meta["storage"]["marked_rows"], 2)
             self.assertFalse(meta["source_bytes_preserved"])
             expected = decode_rows(encode_rows(rows, "int8"), 2, "int8")[mapping]
             with QuantizedRows(target, self.library) as reader:
                 self.assertEqual(reader.gather([2, 0, 1]).tobytes(), expected[[2, 0, 1]].tobytes())
+                output = np.empty((3, 2), dtype="<f4")
+                reader.gather_into([2, 0, 1], output)
+                self.assertEqual(output.tobytes(), expected[[2, 0, 1]].tobytes())
 
     @unittest.skipUnless(torch is not None, "optional PyTorch required")
     def test_quantized_reader_preserves_model_reduction_logits_and_restores_on_failure(self):
diff --git a/tools/benchmark_quantized_capacity.py b/tools/benchmark_quantized_capacity.py
new file mode 100644
index 0000000..7c77499
--- /dev/null
+++ b/tools/benchmark_quantized_capacity.py
@@ -0,0 +1,357 @@
+"""CPU scale/latency evidence on unchanged genuinely trained FP32 rows.
+
+No training, downloads or GPU calls. Construction, verification and each query
+trace use separate processes. Uniform IDs are a synthetic access pattern on
+real vectors. Prefix subsets are storage scaling controls, not new trained
+models. Native compression is exact to encoded bytes; FP16/INT8 are lossy.
+"""
+import argparse
+import hashlib
+import importlib.metadata
+import json
+import os
+from pathlib import Path
+import random
+import subprocess
+import sys
+import time
+
+import numpy as np
+
+from .benchmark_memory_capacity import environment, memory, samples
+from .prepare_public_benchmark import file_sha256
+from .quantized_memory import QuantizedRows, encode_rows, decode_rows, pack_quantized_file
+
+
+def software_environment():
+    result = environment()
+    try:
+        result["pytorch_installed_not_used"] = importlib.metadata.version("torch")
+    except importlib.metadata.PackageNotFoundError:
+        result["pytorch_installed_not_used"] = None
+    result["thread_environment"] = {key: os.environ.get(key) for key in
+                                   ("OMP_NUM_THREADS", "MKL_NUM_THREADS", "OPENBLAS_NUM_THREADS")}
+    return result
+
+
+def write_json(path, value):
+    path.write_text(json.dumps(value, indent=2) + "\n")
+
+
+def read_chunks(source, dim, chunk_rows):
+    with source.open("rb") as stream:
+        while True:
+            part = stream.read(chunk_rows * dim * 4)
+            if not part:
+                break
+            if len(part) % (dim * 4):
+                raise ValueError("partial FP32 source row")
+            yield np.frombuffer(part, dtype="<f4").reshape(-1, dim)
+
+
+def build(args):
+    report = dict(status="running", **software_environment(), memory_before=memory())
+    started, cpu = time.perf_counter(), time.process_time()
+    metadata = pack_quantized_file(args.source, args.bundle, args.dim, args.encoding,
+                                   native=args.backend == "native", deduplicate=False,
+                                   chunk_rows=args.chunk_rows, max_block_bytes=args.max_block_bytes)
+    report.update(status="passed", wall_seconds=time.perf_counter() - started,
+                  cpu_seconds=time.process_time() - cpu, memory_after=memory(), metadata=metadata,
+                  table_bytes=(args.bundle / metadata["table_file"]).stat().st_size,
+                  bundle_bytes=sum(p.stat().st_size for p in args.bundle.iterdir()))
+    write_json(args.worker_report, report)
+
+
+def verify(args):
+    started = time.perf_counter()
+    encoded_digest, decoded_digest, source_digest = hashlib.sha256(), hashlib.sha256(), hashlib.sha256()
+    square_error = square_source = 0.0
+    relative_errors, cosine_errors = [], []
+    row = 0
+    with QuantizedRows(args.bundle, args.native_library, cache_bytes=0) as table:
+        for chunk in read_chunks(args.source, args.dim, args.chunk_rows):
+            ids = np.arange(row, row + len(chunk), dtype="<u8")
+            expected_encoded = encode_rows(chunk, table.encoding)
+            expected_decoded = decode_rows(expected_encoded, args.dim, table.encoding)
+            actual = table.encoded_rows(ids)
+            if actual.tobytes() != expected_encoded.tobytes():
+                raise AssertionError("original-ID encoded bytes differ from the codec oracle")
+            out = np.empty_like(chunk)
+            table.gather_into(ids, out)
+            if out.tobytes() != expected_decoded.tobytes():
+                raise AssertionError("preallocated FP32 reconstruction differs from the codec oracle")
+            source_digest.update(chunk.tobytes())
+            encoded_digest.update(actual.tobytes())
+            decoded_digest.update(out.tobytes())
+            x, y = chunk.astype(np.float64), out.astype(np.float64)
+            difference = np.sum((y - x)**2, axis=1)
+            norm = np.sum(x*x, axis=1)
+            other = np.sum(y*y, axis=1)
+            square_error += float(np.sum(difference))
+            square_source += float(np.sum(norm))
+            relative_errors.append(np.sqrt(difference / np.maximum(norm, np.finfo(np.float64).tiny)))
+            cosine = np.divide(np.sum(x*y, axis=1), np.sqrt(norm*other),
+                               out=np.zeros(len(x)), where=(norm*other) > 0)
+            cosine[(norm == 0) & (other == 0)] = 1
+            cosine_errors.append(1 - np.clip(cosine, -1, 1))
+            row += len(chunk)
+        if row != table.nrows or source_digest.hexdigest() != table.metadata["source_float32_sha256"]:
+            raise AssertionError("source provenance differs from the full bundle")
+        if decoded_digest.hexdigest() != table.metadata["decoded_float32_sha256"]:
+            raise AssertionError("full original-ID decoded hash differs from export audit")
+    relative = np.concatenate(relative_errors)
+    cosine = np.concatenate(cosine_errors)
+    write_json(args.worker_report, dict(status="passed", **software_environment(), rows_verified=row,
+        all_original_ids_encoded_byte_exact=True, all_decoded_rows_oracle_byte_exact=True,
+        source_sha256=source_digest.hexdigest(), encoded_original_id_sha256=encoded_digest.hexdigest(),
+        decoded_original_id_sha256=decoded_digest.hexdigest(), verify_seconds=time.perf_counter() - started,
+        relative_frobenius=float(np.sqrt(square_error / max(square_source, np.finfo(np.float64).tiny))),
+        row_relative_l2=dict(p50=float(np.median(relative)), p99=float(np.percentile(relative, 99)), max=float(np.max(relative))),
+        cosine_distance=dict(p50=float(np.median(cosine)), p99=float(np.percentile(cosine, 99)), max=float(np.max(cosine))),
+        memory_after=memory()))
+
+
+def query(args):
+    manifest = json.loads(args.query_manifest.read_text())
+    case = next(c for c in manifest["cases"] if c["name"] == args.case)
+    report = dict(status="running", **software_environment(), variant=args.variant_label or args.backend + "-" + args.encoding,
+                  case=args.case, cache_budget_bytes=args.cache_bytes if args.backend == "native" else 0,
+                  memory_before_open=memory(), batch_rows=len(case["queries"][0]["ids"]))
+    started = time.perf_counter()
+    if args.backend == "direct":
+        table = np.memmap(args.source, mode="r", dtype="<f4", shape=tuple(manifest["shape"]))
+        width = args.dim * 4
+    else:
+        table = QuantizedRows(args.bundle, args.native_library, cache_bytes=args.cache_bytes)
+        width = table.width
+    report.update(open_ms=(time.perf_counter() - started)*1000, memory_after_open=memory())
+    queries = [(np.asarray(q["ids"], dtype="<u8"), q["sha256_by_encoding"][args.encoding]) for q in case["queries"]]
+    output = np.empty((report["batch_rows"], args.dim), dtype="<f4")
+    scratch = np.empty((report["batch_rows"], width), dtype="u1")
+    report["query_buffer_bytes"] = output.nbytes + (0 if args.backend == "direct" else scratch.nbytes)
+
+    def gather(item):
+        ids, expected = item
+        started, cpu = time.perf_counter_ns(), time.process_time_ns()
+        if args.backend == "direct":
+            np.take(table, ids.view(np.int64), axis=0, out=output, mode="clip")
+        else:
+            table.gather_into(ids, output, encoded_scratch=scratch)
+        wall_ms, cpu_ms = (time.perf_counter_ns() - started)/1e6, (time.process_time_ns() - cpu)/1e6
+        work = None
+        if args.backend == "native":
+            native = table.table
+            work = {name: getattr(native, name) for name in ("last_block_reads", "last_decompressions",
+                    "last_row_cache_hits", "last_compressed_bytes", "last_decoded_bytes")}
+        if hashlib.sha256(output.tobytes()).hexdigest() != expected:
+            raise AssertionError("query output differs from the independent original-ID codec oracle")
+        return wall_ms, cpu_ms, work
+
+    def measure(items):
+        values = [gather(q) for q in items]
+        return dict(wall=samples([v[0] for v in values]), cpu=samples([v[1] for v in values]),
+                    codec_work=[v[2] for v in values],
+                    rows_per_second=sum(len(q[0]) for q in items) / (sum(v[0] for v in values)/1000))
+
+    try:
+        report["memory_before_trace"] = memory()
+        report["first_trace"] = measure(queries)
+        report["memory_after_first_trace"] = memory()
+        # Repeat the entire trace to reveal cache churn beyond the hot subset.
+        report["second_trace"] = measure(queries)
+        report["memory_after_second_trace"] = memory()
+        hot = queries[:min(8, len(queries))]
+        for item in hot:
+            gather(item)
+        report["hot_repeated"] = measure(hot * args.repeat)
+        report.update(status="passed", memory_after_hot=memory(), query_rows=sum(len(q[0]) for q in queries),
+                      distinct_rows=len(set(int(i) for q in queries for i in q[0])), all_query_bytes_exact=True)
+    finally:
+        if args.backend == "direct":
+            table._mmap.close()
+        else:
+            table.close()
+    write_json(args.worker_report, report)
+
+
+def prepare_oracle(source, manifest, dim):
+    result = dict(shape=manifest["shape"], cases=[])
+    with source.open("rb") as stream:
+        for case in manifest["cases"]:
+            queries = []
+            for query in case["queries"]:
+                ids = query["ids"]
+                if len(ids) != 512 or any(type(i) is not int or not 0 <= i < manifest["shape"][0] for i in ids):
+                    raise ValueError("expected valid fixed 512-row original-ID trace")
+                rows = []
+                for i in ids:
+                    stream.seek(i * dim * 4)
+                    rows.append(stream.read(dim * 4))
+                chunk = np.frombuffer(b"".join(rows), dtype="<f4").reshape(len(ids), dim)
+                hashes = {e: hashlib.sha256(decode_rows(encode_rows(chunk, e), dim, e).tobytes()).hexdigest()
+                          for e in ("fp32", "fp16", "int8")}
+                if hashes["fp32"] != query["sha256"]:
+                    raise AssertionError("old FP32 query oracle disagrees with unchanged source")
+                queries.append(dict(ids=ids, sha256_by_encoding=hashes))
+            result["cases"].append(dict(name=case["name"], queries=queries))
+    return result
+
+
+def run(args):
+    source, training_path = args.training_dir / "trained.f32", args.training_dir / "training.json"
+    training = json.loads(training_path.read_text())
+    manifest = json.loads(args.query_manifest.read_text())
+    if (training["status"] != "passed" or not training["all_rows_changed"]
+            or file_sha256(source) != training["trained_sha256"]
+            or manifest["shape"] != [training["ngram_rows"], training["dim"]]):
+        raise ValueError("require unchanged, genuinely trained finite rows and matched query oracle")
+    rows, dim = manifest["shape"]
+    args.output_dir.mkdir(parents=True, exist_ok=False)
+    report_path = args.output_dir / "report.json"
+    report = dict(status="running", **software_environment(), training=training,
+                  source_sha256=file_sha256(source), shape=manifest["shape"],
+                  source_bytes=source.stat().st_size, training_report_sha256=file_sha256(training_path),
+                  input_query_manifest_sha256=file_sha256(args.query_manifest),
+                  native_library_sha256=file_sha256(args.native_library),
+                  keys_bytes=(args.training_dir / "keys.json").stat().st_size,
+                  keys_sha256=file_sha256(args.training_dir / "keys.json"),
+                  settings=dict(chunk_rows=args.chunk_rows, max_block_bytes=args.max_block_bytes,
+                                cache_bytes=args.cache_bytes, repeat=args.repeat, process_repeats=args.process_repeats,
+                                seed=args.seed, scale_rows=args.scale_rows), builds={}, verification={}, workers=[],
+                  limitations=["Shared CPU and filesystem; timing rounds randomize variant/trace order, no isolation guarantee.",
+                    "Filesystem warmed by build/verification; first trace means fresh process/empty application cache, not disk-cold.",
+                    "Uniform IDs are synthetic accesses on genuine vectors; original held-out lexical trace is reused.",
+                    "FP16/INT8 are lossy relative to FP32; byte-exact claims apply to their encoded rows only.",
+                    "No downstream task quality, GPU, cgroup memory cap, physical disk I/O or monetary cost measured.",
+                    "Smaller prefixes reuse original trained rows without retraining and are storage scaling controls.",
+                    "Chunking bounds codec working buffers, not native O(block count) descriptors or arbitrary optional planner indexes.",
+                    "Complete bundle is table + codec metadata + common key registry; training source-ID provenance is separate."])
+    write_json(report_path, report)
+
+    def dispatch(phase, label, source_file, bundle, encoding, backend, case=None, block_bytes=None, variant=None):
+        target = args.output_dir / (phase + "-" + label + ".json")
+        command = [sys.executable, "-m", "tools.benchmark_quantized_capacity", "--phase", phase,
+                   "--source", str(source_file), "--bundle", str(bundle), "--dim", str(dim),
+                   "--encoding", encoding, "--backend", backend, "--worker-report", str(target),
+                   "--native-library", str(args.native_library), "--chunk-rows", str(args.chunk_rows),
+                   "--max-block-bytes", str(block_bytes or args.max_block_bytes), "--cache-bytes", str(args.cache_bytes),
+                   "--repeat", str(args.repeat), "--query-manifest", str(args.output_dir / "queries.json")]
+        if case:
+            command += ["--case", case]
+        if variant:
+            command += ["--variant-label", variant]
+        process = subprocess.run(command, capture_output=True, text=True)
+        (args.output_dir / (phase + "-" + label + ".log")).write_text(process.stdout + process.stderr)
+        value = dict(command=command, returncode=process.returncode, report_file=target.name)
+        if target.exists():
+            value["result"] = json.loads(target.read_text())
+        else:
+            value["error"] = process.stderr[-4000:]
+        return value
+
+    try:
+        write_json(args.output_dir / "queries.json", prepare_oracle(source, manifest, dim))
+        report["query_oracle_sha256"] = file_sha256(args.output_dir / "queries.json")
+        variants = [(e + "-" + b, e, b, args.max_block_bytes)
+                    for e in ("fp32", "fp16", "int8") for b in ("raw", "native")]
+        variants += [("int8-native-rows-" + str(n), "int8", "native", n * (dim + 4))
+                     for n in args.int8_extra_block_rows]
+        report["settings"]["int8_extra_block_rows"] = args.int8_extra_block_rows
+        for label, encoding, backend, block_bytes in variants:
+            bundle = args.output_dir / label
+            value = dispatch("build", label, source, bundle, encoding, backend, block_bytes=block_bytes)
+            report["builds"][label] = value
+            write_json(report_path, report)
+            if value["returncode"]:
+                raise RuntimeError("build failed: " + label)
+            value["result"]["bundle_with_keys_bytes"] = value["result"]["bundle_bytes"] + report["keys_bytes"]
+            value = dispatch("verify", label, source, bundle, encoding, backend)
+            report["verification"][label] = value
+            write_json(report_path, report)
+            if value["returncode"]:
+                raise RuntimeError("verification failed: " + label)
+            print(json.dumps(dict(phase="verified", variant=label)), flush=True)
+        for count in args.scale_rows:
+            if not 0 < count < rows:
+                raise ValueError("scale prefix must be smaller than the full trained source")
+            prefix = args.output_dir / ("prefix-" + str(count) + ".f32")
+            with source.open("rb") as src, prefix.open("wb") as dest:
+                remaining = count * dim * 4
+                while remaining:
+                    part = src.read(min(1048576, remaining))
+                    if not part:
+                        raise ValueError("source truncated")
+                    dest.write(part)
+                    remaining -= len(part)
+            label = "int8-native-prefix-" + str(count)
+            value = dispatch("build", label, prefix, args.output_dir / label, "int8", "native")
+            report["builds"][label] = value
+            write_json(report_path, report)
+            if value["returncode"]:
+                raise RuntimeError("scale build failed: " + label)
+            prefix.unlink()
+        cases = [c["name"] for c in manifest["cases"]]
+        for cycle in range(args.process_repeats):
+            jobs = [(label, e, b, c) for label, e, b, _ in variants + [("fp32-direct", "fp32", "direct", 0)] for c in cases]
+            random.Random(args.seed + cycle).shuffle(jobs)
+            for variant, encoding, backend, case in jobs:
+                label = f"{variant}-{case}-{cycle}"
+                value = dispatch("query", label, source, args.output_dir / variant, encoding, backend, case, variant=variant)
+                value.update(variant=variant, encoding=encoding, backend=backend, case=case, cycle=cycle)
+                report["workers"].append(value)
+                write_json(report_path, report)
+                if value["returncode"]:
+                    raise RuntimeError("query failed: " + label)
+                print(json.dumps(dict(phase="query-passed", variant=label)), flush=True)
+        report["status"] = "passed"
+        write_json(report_path, report)
+    except BaseException as error:
+        report.update(status="failed", error=repr(error))
+        write_json(report_path, report)
+        raise
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--training-dir", type=Path)
+    parser.add_argument("--output-dir", type=Path)
+    parser.add_argument("--query-manifest", type=Path, required=True)
+    parser.add_argument("--native-library", type=Path, required=True)
+    parser.add_argument("--chunk-rows", type=int, default=4096)
+    parser.add_argument("--max-block-bytes", type=int, default=8192)
+    parser.add_argument("--cache-bytes", type=int, default=4194304)
+    parser.add_argument("--repeat", type=int, default=20)
+    parser.add_argument("--process-repeats", type=int, default=3)
+    parser.add_argument("--seed", type=int, default=42)
+    parser.add_argument("--scale-rows", type=int, nargs="*", default=[100000, 500000])
+    parser.add_argument("--int8-extra-block-rows", type=int, nargs="*", default=[1, 4])
+    parser.add_argument("--phase", choices=("build", "verify", "query"))
+    parser.add_argument("--source", type=Path)
+    parser.add_argument("--bundle", type=Path)
+    parser.add_argument("--dim", type=int)
+    parser.add_argument("--encoding", choices=("fp32", "fp16", "int8"))
+    parser.add_argument("--backend", choices=("raw", "native", "direct"))
+    parser.add_argument("--worker-report", type=Path)
+    parser.add_argument("--case")
+    parser.add_argument("--variant-label")
+    args = parser.parse_args()
+    if os.environ.get("CUDA_VISIBLE_DEVICES") != "":
+        parser.error("set CUDA_VISIBLE_DEVICES to empty")
+    if min(args.chunk_rows, args.max_block_bytes, args.repeat, args.process_repeats) < 1 or args.cache_bytes < 0:
+        parser.error("invalid chunk/block/repeat/cache setting")
+    if any(n < 1 or n > 256 for n in args.int8_extra_block_rows) or len(set(args.int8_extra_block_rows)) != len(args.int8_extra_block_rows):
+        parser.error("distinct extra block rows between 1 and 256 required")
+    if args.phase:
+        if any(getattr(args, name) is None for name in ("source", "bundle", "dim", "encoding", "backend", "worker_report")):
+            parser.error("worker source/bundle/dim/encoding/backend/report are required")
+        if args.backend == "direct" and (args.phase != "query" or args.encoding != "fp32"):
+            parser.error("direct backend is the FP32 query control only")
+        {"build": build, "verify": verify, "query": query}[args.phase](args)
+    else:
+        if args.training_dir is None or args.output_dir is None:
+            parser.error("training-dir and output-dir required")
+        run(args)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tools/quantized_memory.py b/tools/quantized_memory.py
index 24635f0..cdef67b 100644
--- a/tools/quantized_memory.py
+++ b/tools/quantized_memory.py
@@ -6,6 +6,7 @@
 """
 import hashlib
 import json
+import os
 from pathlib import Path
 import shutil
 
@@ -59,36 +60,115 @@ def decode_rows(encoded, dim, encoding):
 
 
 def pack_quantized(rows, directory, encoding, *, native=True, representatives=None,
-                   row_order=None, deduplicate=False, max_block_bytes=8192):
-    """Publish a new research bundle; include codec metadata in measured bytes."""
-    rows = np.ascontiguousarray(rows, dtype="<f4")
-    encoded = encode_rows(rows, encoding)
+                   row_order=None, deduplicate=False, max_block_bytes=8192,
+                   chunk_rows=4096):
+    """Export a frozen matrix/memmap in chunks, including codec metadata.
+
+    Encoding, source hashing and decoded-original-ID auditing use bounded
+    chunks. Native block descriptors and optional dedup/order/representative
+    indexes still grow with table size; chunk_rows is not a total RSS cap.
+    A staging file holds encoded rows on disk until native packing completes.
+    """
+    rows = np.asarray(rows)
+    if rows.ndim != 2:
+        raise ValueError("nonempty matrix required")
+    return _pack_quantized(rows, directory, encoding, native=native, representatives=representatives,
+                           row_order=row_order, deduplicate=deduplicate,
+                           max_block_bytes=max_block_bytes, chunk_rows=chunk_rows)
+
+
+def pack_quantized_file(source, directory, dim, encoding, **options):
+    """Stream a headerless little-endian FP32 file without mapping all source pages.
+
+    Reads each chunk for encoding and again for auditing. This avoids cumulative
+    source mmap RSS. Dedup/planner indexes and native descriptors remain O(n).
+    """
+    row_width(dim, "fp32")
+    source = Path(source)
+    count, remainder = divmod(source.stat().st_size, dim * 4)
+    if not count or remainder:
+        raise ValueError("nonempty complete FP32 rows required")
+    with source.open("rb") as stream:
+        class FileRows:
+            shape = (count, dim)
+
+            def __len__(self):
+                return count
+
+            def __getitem__(self, index):
+                if os.fstat(stream.fileno()).st_size != count * dim * 4:
+                    raise ValueError("FP32 source size changed during export")
+                start, stop, _ = index.indices(count)
+                stream.seek(start * dim * 4)
+                data = stream.read((stop - start) * dim * 4)
+                if len(data) != (stop - start) * dim * 4:
+                    raise ValueError("FP32 source truncated during export")
+                return np.frombuffer(data, dtype="<f4").reshape(stop - start, dim)
+
+        return _pack_quantized(FileRows(), directory, encoding, **options)
+
+
+def _pack_quantized(rows, directory, encoding, *, native=True, representatives=None,
+                    row_order=None, deduplicate=False, max_block_bytes=8192, chunk_rows=4096):
+    if min(rows.shape) < 1 or type(chunk_rows) is not int or chunk_rows < 1:
+        raise ValueError("nonempty matrix and positive integer chunk_rows required")
+    width = row_width(rows.shape[1], encoding)
     if not native and (representatives is not None or row_order is not None or deduplicate):
         raise ValueError("raw baseline must retain original row order without compaction")
     directory = Path(directory)
     directory.mkdir(parents=True, exist_ok=False)
     try:
         source = directory / "staging.rows"
-        source.write_bytes(encoded.tobytes())
+        source_digest = hashlib.sha256()
+        with source.open("wb") as stream:
+            for start in range(0, len(rows), chunk_rows):
+                chunk = np.ascontiguousarray(rows[start:start + chunk_rows], dtype="<f4")
+                encoded = encode_rows(chunk, encoding)
+                source_digest.update(chunk.tobytes())
+                stream.write(encoded.tobytes())
         table = directory / ("table.men" if native else "table.rows")
         if native:
-            storage = pack_native(source, table, encoded.shape[1], deduplicate=deduplicate,
+            storage = pack_native(source, table, width, deduplicate=deduplicate,
                                   predictor="xor", representatives=representatives,
                                   row_order=row_order, max_block_bytes=max_block_bytes)
+        else:
+            storage = {"artifact_bytes": source.stat().st_size, "unique_rows": len(rows),
+                       "row_map_bytes": 0, "deduplicate": False}
+        mapping = None if representatives is None else np.asarray(representatives)
+        staged = None if mapping is None else np.memmap(source, mode="r", dtype="u1", shape=(len(rows), width))
+        decoded_digest, preserved = hashlib.sha256(), True
+        audit_source_digest = hashlib.sha256()
+        try:
+            with source.open("rb") as stream:
+                for start in range(0, len(rows), chunk_rows):
+                    stop = min(start + chunk_rows, len(rows))
+                    selected = (np.frombuffer(stream.read((stop - start) * width), dtype="u1").reshape(-1, width)
+                                if mapping is None else staged[mapping[start:stop]])
+                    expected = decode_rows(selected, rows.shape[1], encoding).tobytes()
+                    decoded_digest.update(expected)
+                    original = np.ascontiguousarray(rows[start:stop], dtype="<f4").tobytes()
+                    audit_source_digest.update(original)
+                    preserved &= expected == original
+        finally:
+            if staged is not None:
+                staged._mmap.close()
+        if audit_source_digest.digest() != source_digest.digest():
+            raise ValueError("FP32 source changed during export")
+        if native:
             source.unlink()
         else:
             source.rename(table)
-            storage = {"artifact_bytes": table.stat().st_size, "unique_rows": len(rows),
-                       "row_map_bytes": 0, "deduplicate": False}
-        mapping = np.arange(len(rows)) if representatives is None else np.asarray(representatives)
-        expected = decode_rows(encoded[mapping], rows.shape[1], encoding)
+        table_digest = hashlib.sha256()
+        with table.open("rb") as stream:
+            for part in iter(lambda: stream.read(1024 * 1024), b""):
+                table_digest.update(part)
         metadata = {"schema_version": 1, "shape": list(rows.shape), "encoding": encoding,
                     "byteorder": "little", "backend": "native" if native else "raw_mmap",
-                    "table_file": table.name, "row_bytes": encoded.shape[1], "storage": storage,
-                    "source_float32_sha256": hashlib.sha256(rows.tobytes()).hexdigest(),
-                    "decoded_float32_sha256": hashlib.sha256(expected.tobytes()).hexdigest(),
-                    "table_sha256": hashlib.sha256(table.read_bytes()).hexdigest(),
-                    "source_bytes_preserved": expected.tobytes() == rows.tobytes(),
+                    "table_file": table.name, "row_bytes": width, "storage": storage,
+                    "source_float32_sha256": source_digest.hexdigest(),
+                    "decoded_float32_sha256": decoded_digest.hexdigest(),
+                    "table_sha256": table_digest.hexdigest(),
+                    "source_bytes_preserved": preserved, "export_chunk_rows": chunk_rows,
                     "int8_scale_bytes_per_physical_row": 4 if encoding == "int8" else 0,
                     "rounding": "nearest-even; symmetric [-127,127] per-row scale" if encoding == "int8" else encoding,
                     "contract": "frozen original IDs; exact encoded representative bytes; quantization/sharing may change float32 rows"}
@@ -143,6 +223,46 @@ def encoded_rows(self, ids):
     def gather(self, ids):
         return decode_rows(self.encoded_rows(ids), self.dim, self.encoding)
 
+    def gather_into(self, ids, output, *, encoded_scratch=None):
+        """Restore FP32 into caller buffers; avoid allocating a full decoded result.
+
+        Both backends gather encoded bytes into the same contiguous scratch.
+        Raw uses take(out=..., mode=clip) after ID validation. Output/scratch are
+        single-call worker buffers, not cache storage; supply scratch to reuse it.
+        """
+        if self.table is None:
+            raise ValueError("quantized rows are closed")
+        ids = np.asarray(ids)
+        if ids.ndim != 1 or (ids.size and (ids.dtype.kind not in "iu" or np.any(ids < 0) or np.any(ids >= self.nrows))):
+            raise ValueError("one-dimensional original row IDs out of range")
+        if (not isinstance(output, np.ndarray) or output.dtype != np.dtype("<f4")
+                or output.shape != (len(ids), self.dim) or not output.flags.c_contiguous
+                or not output.flags.writeable):
+            raise ValueError("output must be writable contiguous float32 with the query shape")
+        if encoded_scratch is None:
+            encoded_scratch = np.empty((len(ids), self.width), dtype="u1")
+        if (not isinstance(encoded_scratch, np.ndarray) or encoded_scratch.dtype != np.uint8
+                or encoded_scratch.shape != (len(ids), self.width)
+                or not encoded_scratch.flags.c_contiguous or not encoded_scratch.flags.writeable
+                or np.shares_memory(output, encoded_scratch)
+                or np.shares_memory(ids, output) or np.shares_memory(ids, encoded_scratch)):
+            raise ValueError("scratch must be writable contiguous bytes with no buffer overlap")
+        if not len(ids):
+            return
+        if isinstance(self.table, NativeRows):
+            ids = np.ascontiguousarray(ids, dtype="<u8")
+            self.table.gather_into(ids.ctypes.data, len(ids), encoded_scratch.ctypes.data, encoded_scratch.nbytes)
+        else:
+            np.take(self.table, ids.astype(np.intp, copy=False), axis=0, out=encoded_scratch, mode="clip")
+        if self.encoding in ("fp32", "fp16"):
+            np.copyto(output, encoded_scratch.view("<f4" if self.encoding == "fp32" else "<f2").reshape(output.shape))
+        else:
+            # Only scales need a tiny contiguous copy; code rows retain strides.
+            scales = np.ascontiguousarray(encoded_scratch[:, self.dim:]).view("<f4").reshape(-1, 1)
+            if not np.isfinite(scales).all() or np.any(scales <= 0):
+                raise ValueError("invalid INT8 scale")
+            np.multiply(encoded_scratch[:, :self.dim].view("i1"), scales, out=output, dtype=np.float32)
+
     def close(self):
         if isinstance(self.table, NativeRows):
             self.table.close()

From 9de926660fd6b7e3f9ecba1016720c806b2e3431 Mon Sep 17 00:00:00 2001
From: initial-d <duyimin123@163.com>
Date: Sat, 31 Oct 2026 19:24:53 +0800
Subject: [PATCH 2/4] Add scale evidence analysis and streaming export resource
 regression checks

---
 docs/native_ngram_memory.md         |  35 ++++++++
 tests/test_quantized_capacity.py    |  20 ++++-
 tests/test_quantized_memory.py      |  21 +++++
 tools/analyze_quantized_capacity.py | 135 ++++++++++++++++++++++++++++
 4 files changed, 210 insertions(+), 1 deletion(-)
 create mode 100644 tools/analyze_quantized_capacity.py

diff --git a/docs/native_ngram_memory.md b/docs/native_ngram_memory.md
index 9ae5f22..4113d4c 100644
--- a/docs/native_ngram_memory.md
+++ b/docs/native_ngram_memory.md
@@ -207,6 +207,41 @@ the PyTorch adapter does. Use trusted, immutable artifacts and external checksum
 for archival provenance. Structural checks and sanitizers are not a production
 artifact-security guarantee.
 
+### Frozen quantized row files
+
+`tools.quantized_memory.pack_quantized_file` reads a headerless little-endian
+FP32 table in chunks, encodes FP32/FP16/per-row INT8, then packs the encoded
+rows with the same native format. The original source and decoded-original-ID
+hashes are computed incrementally. Use this file path for large exports to
+avoid accumulating resident source mmap pages:
+
+```python
+import numpy as np
+from tools.quantized_memory import pack_quantized_file, QuantizedRows
+
+pack_quantized_file("trained.f32", "int8-bundle", 256, "int8",
+                    chunk_rows=4096, max_block_bytes=8192)
+ids = np.array([2, 0, 2], dtype="<u8")
+with QuantizedRows("int8-bundle", "build/libmeft_rows.so") as rows:
+    output = np.empty((len(ids), rows.dim), dtype="<f4")
+    scratch = np.empty((len(ids), rows.width), dtype="u1")
+    rows.gather_into(ids, output, encoded_scratch=scratch)
+```
+
+This is a frozen CPU research codec. INT8 includes a FP32 scale inside every
+encoded row; FP16/INT8 change source weights. Native preserves the encoded
+representative bytes and original IDs. Dequantization writes into reusable
+NumPy FP32 output; it is not a trainable `.weight` or fused GPU kernel.
+The existing `pack_quantized(matrix, ...)` interface also encodes/audits in
+chunks, but its caller-owned matrix/mmap residency remains outside that bound.
+
+Chunking limits codec/hash buffers, not total RSS: native descriptors grow
+with block count, optional dedup/order/representative indexes grow with rows,
+and structural planning still holds full vectors/maps. Encoded staging and
+native spool/publication files also consume temporary disk space. Smaller
+blocks reduce sparse decode work at a metadata/compression cost. See the
+[same-trained-table scale and performance controls](quantized_capacity_evidence_20261031/README.md).
+
 To enable the optional codec, pass `predictor="xor"` to `pack_native`,
 `export_demo_embedding`, `export_multihead` or `export_embedding` with the native
 backend. Existing calls still write version 1. `pack_native(..., row_order=...)`
diff --git a/tests/test_quantized_capacity.py b/tests/test_quantized_capacity.py
index 2374335..391fe47 100644
--- a/tests/test_quantized_capacity.py
+++ b/tests/test_quantized_capacity.py
@@ -18,7 +18,8 @@
 @unittest.skipUnless(np is not None and shutil.which("cc"), "NumPy and C compiler required")
 class CapacityTest(unittest.TestCase):
     def test_fresh_worker_oracles_full_verification_and_direct_control(self):
-        from tools.benchmark_quantized_capacity import build, verify, query, prepare_oracle
+        from tools.benchmark_quantized_capacity import build, verify, query, prepare_oracle, software_environment
+        from tools.analyze_quantized_capacity import analyze
         with tempfile.TemporaryDirectory() as tmp:
             root = Path(tmp)
             library = root / ("rows.dylib" if sys.platform == "darwin" else "rows.so")
@@ -37,23 +38,40 @@ def test_fresh_worker_oracles_full_verification_and_direct_control(self):
             cfg = Namespace(source=source, dim=3, native_library=library, chunk_rows=2,
                             cache_bytes=128, max_block_bytes=12, repeat=2, case="fixture",
                             query_manifest=oracle_file, variant_label=None)
+            report = dict(status="passed", **software_environment(), shape=list(rows.shape),
+                          source_bytes=rows.nbytes, source_sha256=hashlib.sha256(rows.tobytes()).hexdigest(),
+                          settings={}, limitations=["fixture"], native_library_sha256="fixture",
+                          keys_bytes=42, keys_sha256="fixture", training_report_sha256="fixture",
+                          training={}, builds={}, verification={}, workers=[])
             for encoding in ("fp32", "fp16", "int8"):
                 for backend in ("raw", "native"):
+                    name = encoding + "-" + backend
                     cfg.encoding, cfg.backend = encoding, backend
                     cfg.bundle = root / (encoding + backend)
                     cfg.worker_report = root / "worker.json"
                     build(cfg)
+                    built = json.loads(cfg.worker_report.read_text())
+                    built["bundle_with_keys_bytes"] = built["bundle_bytes"] + report["keys_bytes"]
+                    report["builds"][name] = dict(returncode=0, result=built)
                     verify(cfg)
                     verified = json.loads(cfg.worker_report.read_text())
+                    report["verification"][name] = dict(returncode=0, result=verified)
                     self.assertEqual(verified["rows_verified"], len(rows))
                     self.assertTrue(verified["all_original_ids_encoded_byte_exact"])
                     if encoding == "fp32":
                         self.assertEqual(verified["relative_frobenius"], 0)
                     query(cfg)
                     checked = json.loads(cfg.worker_report.read_text())
+                    report["workers"].append(dict(returncode=0, variant=name, case="fixture", result=checked))
                     self.assertTrue(checked["all_query_bytes_exact"])
                     self.assertEqual(checked["query_rows"], 512)
                     self.assertEqual(len(checked["first_trace"]["wall"]["samples_ms"]), 1)
+            summarized = analyze(report)
+            self.assertEqual(summarized["failures"], [])
+            # Preserve format/metadata expansion against the same-encoding raw
+            # control instead of attributing quantization's gain to native.
+            self.assertLess(summarized["builds"]["int8-native"]["bundle_added_saving_vs_same_encoding_raw"], 0)
+            self.assertIn("wall_p99_ms", summarized["queries"]["int8-native"]["fixture"]["first_trace"])
             cfg.backend, cfg.encoding = "direct", "fp32"
             query(cfg)
             self.assertTrue(json.loads(cfg.worker_report.read_text())["all_query_bytes_exact"])
diff --git a/tests/test_quantized_memory.py b/tests/test_quantized_memory.py
index 722d5e9..9fbe9a3 100644
--- a/tests/test_quantized_memory.py
+++ b/tests/test_quantized_memory.py
@@ -96,6 +96,27 @@ def test_file_export_streams_chunks_and_checks_original_id_hashes(self):
                 pack_quantized_file(source, bad, 3, "int8", chunk_rows=2)
             self.assertFalse(bad.exists())
 
+    def test_same_size_source_mutation_is_rejected_by_streaming_audit(self):
+        from tools.quantized_memory import pack_quantized_file, encode_rows
+        with tempfile.TemporaryDirectory() as tmp:
+            source = Path(tmp) / "source.f32"
+            source.write_bytes(np.ones((4, 2), dtype="<f4").tobytes())
+            target = Path(tmp) / "bundle"
+            calls = 0
+            def mutate_after_encoding(chunk, encoding):
+                nonlocal calls
+                result = encode_rows(chunk, encoding)
+                calls += 1
+                if calls == 1:
+                    changed = np.ones((4, 2), dtype="<f4")
+                    changed[0, 0] = 2
+                    source.write_bytes(changed.tobytes())
+                return result
+            with patch("tools.quantized_memory.encode_rows", side_effect=mutate_after_encoding):
+                with self.assertRaisesRegex(ValueError, "source changed"):
+                    pack_quantized_file(source, target, 2, "int8", native=False, chunk_rows=2)
+            self.assertFalse(target.exists())
+
 
 @unittest.skipUnless(np is not None and shutil.which("cc"), "NumPy and native C compiler required")
 class QuantizedNativeTest(unittest.TestCase):
diff --git a/tools/analyze_quantized_capacity.py b/tools/analyze_quantized_capacity.py
new file mode 100644
index 0000000..31736da
--- /dev/null
+++ b/tools/analyze_quantized_capacity.py
@@ -0,0 +1,135 @@
+"""Summarize measured table bytes, per-process latencies and CPU resources."""
+import argparse
+import gzip
+import json
+from pathlib import Path
+
+import numpy as np
+
+
+def range_summary(values):
+    return dict(median=float(np.median(values)), min=float(min(values)), max=float(max(values)), values=values)
+
+
+def analyze(report):
+    summary = {key: report[key] for key in ("status", "source_commit", "command", "shape", "source_bytes",
+                "source_sha256", "python", "numpy", "os", "cpu", "settings", "limitations",
+                "native_library_sha256", "keys_bytes", "keys_sha256", "training_report_sha256")}
+    summary["training"] = report["training"]
+    summary["software"] = {key: report.get(key) for key in ("pytorch_installed_not_used", "thread_environment", "cpu_affinity")}
+    summary.update(builds={}, queries={}, failures=[])
+    for name, build in report["builds"].items():
+        if build["returncode"]:
+            summary["failures"].append(dict(phase="build", variant=name, error=build.get("error")))
+            continue
+        value = build["result"]
+        m = value["metadata"]
+        summary["builds"][name] = dict(rows=m["shape"][0], encoding=m["encoding"], backend=m["backend"],
+            wall_seconds=value["wall_seconds"], cpu_seconds=value["cpu_seconds"],
+            peak_rss_bytes=value["memory_after"]["peak_rss_bytes"], table_bytes=value["table_bytes"],
+            bundle_bytes=value["bundle_bytes"], bundle_with_keys_bytes=value.get("bundle_with_keys_bytes"),
+            storage=m["storage"], source_sha256=m["source_float32_sha256"], table_sha256=m["table_sha256"],
+            source_bytes_preserved=m["source_bytes_preserved"])
+        verified = report["verification"].get(name)
+        if verified and not verified["returncode"]:
+            v = verified["result"]
+            summary["builds"][name]["verification"] = {key: v[key] for key in
+                ("rows_verified", "all_original_ids_encoded_byte_exact", "all_decoded_rows_oracle_byte_exact",
+                 "encoded_original_id_sha256", "decoded_original_id_sha256", "relative_frobenius", "row_relative_l2", "cosine_distance")}
+        elif verified:
+            summary["failures"].append(dict(phase="verify", variant=name, error=verified.get("error")))
+    groups = {}
+    for worker in report["workers"]:
+        if worker["returncode"]:
+            summary["failures"].append(dict(phase="query", variant=worker["variant"], case=worker["case"], error=worker.get("error")))
+            continue
+        groups.setdefault((worker["variant"], worker["case"]), []).append(worker["result"])
+    for (variant, case), workers in groups.items():
+        target = dict(processes=len(workers), query_rows=workers[0]["query_rows"], distinct_rows=workers[0]["distinct_rows"],
+                      batch_rows=workers[0]["batch_rows"], query_buffer_bytes=workers[0]["query_buffer_bytes"],
+                      cache_budget_bytes=workers[0]["cache_budget_bytes"],
+                      all_query_bytes_exact=all(w["all_query_bytes_exact"] for w in workers))
+        for phase in ("first_trace", "second_trace", "hot_repeated"):
+            target[phase] = {"wall_" + key: range_summary([float(np.percentile(w[phase]["wall"]["samples_ms"], q)) for w in workers])
+                             for key, q in (("p50_ms", 50), ("p95_ms", 95), ("p99_ms", 99))}
+            target[phase]["rows_per_second"] = range_summary([w[phase]["rows_per_second"] for w in workers])
+            target[phase]["cpu_p50_ms"] = range_summary([w[phase]["cpu"]["p50_ms"] for w in workers])
+            if variant.find("native") >= 0:
+                decoded, compressed, hits = [], [], []
+                for w in workers:
+                    work = w[phase]["codec_work"]
+                    decoded.append(sum(c["last_decoded_bytes"] for c in work))
+                    compressed.append(sum(c["last_compressed_bytes"] for c in work))
+                    hits.append(sum(c["last_row_cache_hits"] for c in work))
+                target[phase]["logical_decoded_bytes"] = range_summary(decoded)
+                target[phase]["logical_compressed_bytes"] = range_summary(compressed)
+                target[phase]["row_cache_hits"] = range_summary(hits)
+                row_width = report["builds"][variant]["result"]["metadata"]["row_bytes"]
+                output_bytes = workers[0]["batch_rows"] * row_width * len(workers[0][phase]["wall"]["samples_ms"])
+                target[phase]["decoded_over_encoded_output"] = range_summary([v / output_bytes for v in decoded])
+        for phase in ("memory_after_first_trace", "memory_after_second_trace", "memory_after_hot"):
+            target[phase] = {key: range_summary([w[phase][key] for w in workers])
+                             for key in ("peak_rss_bytes", "VmRSS_bytes") if all(key in w[phase] for w in workers)}
+        summary["queries"].setdefault(variant, {})[case] = target
+    baseline = summary["builds"].get("fp32-raw")
+    if baseline:
+        for name, v in summary["builds"].items():
+            if v["rows"] != report["shape"][0]:
+                continue
+            v["table_saving_vs_raw_fp32"] = 1 - v["table_bytes"] / baseline["table_bytes"]
+            v["bundle_saving_vs_raw_fp32"] = 1 - v["bundle_with_keys_bytes"] / baseline["bundle_with_keys_bytes"]
+            matched = summary["builds"].get(v["encoding"] + "-raw")
+            if matched:
+                v["bundle_added_saving_vs_same_encoding_raw"] = 1 - v["bundle_with_keys_bytes"] / matched["bundle_with_keys_bytes"]
+    return summary
+
+
+def plot(summary, directory):
+    import matplotlib.pyplot as plt
+    names = ["fp32-raw", "fp32-native", "fp16-raw", "fp16-native", "int8-raw", "int8-native",
+             "int8-native-rows-4", "int8-native-rows-1"]
+    names = [n for n in names if n in summary["builds"]]
+    labels = [n.replace("-raw", " mmap").replace("-native-rows-", " native/").replace("-native", " native") for n in names]
+    fig, axes = plt.subplots(1, 3, figsize=(17, 5.4), constrained_layout=True)
+    colors = ["#4c78a8" if "fp32" in n else "#59a14f" if "fp16" in n else "#f28e2b" for n in names]
+    axes[0].barh(labels, [summary["builds"][n]["bundle_with_keys_bytes"] / 1e9 for n in names], color=colors)
+    axes[0].set(xlabel="Table + codec + common keys (GB)",
+                title=f"Same {summary['shape'][0]/1e6:.3f}M × {summary['shape'][1]} trained rows")
+    query_names = ["fp32-direct"] + names
+    for case, marker in (("heldout-lexical", "o"), ("uniform-id-stress", "s")):
+        values = [summary["queries"][n][case]["first_trace"]["wall_p50_ms"]["median"] for n in query_names]
+        axes[1].plot(values, list(range(len(query_names))), marker=marker, label=case)
+    axes[1].set_yticks(range(len(query_names)), [n.replace("fp32-direct", "FP32 direct mmap") for n in query_names])
+    axes[1].set(xscale="log", xlabel="Fresh-process first-trace batch p50 (ms)", title="512-row CPU gather → FP32")
+    axes[1].legend(fontsize=8)
+    scale_names = ["int8-native-prefix-100000", "int8-native-prefix-500000", "int8-native"]
+    scale_names = [n for n in scale_names if n in summary["builds"]]
+    axes[2].plot([summary["builds"][n]["rows"] / 1e6 for n in scale_names],
+                 [summary["builds"][n]["peak_rss_bytes"] / 2**20 for n in scale_names], "o-", color="#f28e2b")
+    axes[2].set(xlabel="Original trained rows (millions)", ylabel="Fresh builder peak RSS (MiB)",
+                title="INT8 streaming export, ≤8 KiB blocks")
+    for ax in axes[:2]:
+        ax.invert_yaxis()
+    fig.suptitle("Quantization is lossy; native preserves encoded bytes. Shared CPU, warmed filesystem, no GPU.", fontsize=11)
+    for ext in ("svg", "png"):
+        fig.savefig(directory / ("scale-performance." + ext), dpi=180)
+    plt.close(fig)
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--report", type=Path, required=True)
+    parser.add_argument("--output-dir", type=Path, required=True)
+    parser.add_argument("--plots", action="store_true")
+    args = parser.parse_args()
+    opener = gzip.open if args.report.suffix == ".gz" else open
+    with opener(args.report, "rt") as stream:
+        summary = analyze(json.load(stream))
+    args.output_dir.mkdir(parents=True, exist_ok=True)
+    (args.output_dir / "summary.json").write_text(json.dumps(summary, indent=2) + "\n")
+    if args.plots:
+        plot(summary, args.output_dir)
+
+
+if __name__ == "__main__":
+    main()

From 9485969066ee4be466673cde07823330da1a7658 Mon Sep 17 00:00:00 2001
From: initial-d <duyimin123@163.com>
Date: Sat, 31 Oct 2026 19:31:48 +0800
Subject: [PATCH 3/4] Keep raw quantized bundles when complete native overhead
 outweighs compression

---
 docs/native_ngram_memory.md           | 10 ++++++++-
 tests/test_quantized_memory.py        | 22 ++++++++++++++++++++
 tools/analyze_quantized_capacity.py   |  5 +++++
 tools/benchmark_quantized_capacity.py |  3 ++-
 tools/quantized_memory.py             | 30 +++++++++++++++++++++++++--
 5 files changed, 66 insertions(+), 4 deletions(-)

diff --git a/docs/native_ngram_memory.md b/docs/native_ngram_memory.md
index 4113d4c..d85c3a9 100644
--- a/docs/native_ngram_memory.md
+++ b/docs/native_ngram_memory.md
@@ -220,7 +220,7 @@ import numpy as np
 from tools.quantized_memory import pack_quantized_file, QuantizedRows
 
 pack_quantized_file("trained.f32", "int8-bundle", 256, "int8",
-                    chunk_rows=4096, max_block_bytes=8192)
+                    native="auto", chunk_rows=4096, max_block_bytes=8192)
 ids = np.array([2, 0, 2], dtype="<u8")
 with QuantizedRows("int8-bundle", "build/libmeft_rows.so") as rows:
     output = np.empty((len(ids), rows.dim), dtype="<f4")
@@ -234,6 +234,12 @@ representative bytes and original IDs. Dequantization writes into reusable
 NumPy FP32 output; it is not a trainable `.weight` or fused GPU kernel.
 The existing `pack_quantized(matrix, ...)` interface also encodes/audits in
 chunks, but its caller-owned matrix/mmap residency remains outside that bound.
+`native="auto"` is an optional identity-row size policy: compare actual table
+and codec JSON bytes, including the native map/descriptors, and keep raw if it
+is smaller. The common key registry cancels in that comparison. The candidate
+native file is still constructed, and this policy does not select for latency.
+It rejects structural forwarding/reordering/dedup; the default `native=True`
+and explicit raw/native paths remain unchanged.
 
 Chunking limits codec/hash buffers, not total RSS: native descriptors grow
 with block count, optional dedup/order/representative indexes grow with rows,
@@ -242,6 +248,8 @@ native spool/publication files also consume temporary disk space. Smaller
 blocks reduce sparse decode work at a metadata/compression cost. See the
 [same-trained-table scale and performance controls](quantized_capacity_evidence_20261031/README.md).
 
+### Native layout and structural export
+
 To enable the optional codec, pass `predictor="xor"` to `pack_native`,
 `export_demo_embedding`, `export_multihead` or `export_embedding` with the native
 backend. Existing calls still write version 1. `pack_native(..., row_order=...)`
diff --git a/tests/test_quantized_memory.py b/tests/test_quantized_memory.py
index 9fbe9a3..0a52fc7 100644
--- a/tests/test_quantized_memory.py
+++ b/tests/test_quantized_memory.py
@@ -188,6 +188,28 @@ def test_mark_compact_forwards_entire_quantized_representative(self):
                 reader.gather_into([2, 0, 1], output)
                 self.assertEqual(output.tobytes(), expected[[2, 0, 1]].tobytes())
 
+    def test_optional_auto_backend_avoids_map_descriptor_expansion_and_retains_useful_native(self):
+        from tools.quantized_memory import pack_quantized_file, QuantizedRows, encode_rows, decode_rows
+        # Tiny format-overhead and compressible correctness fixtures, not evidence.
+        with tempfile.TemporaryDirectory() as tmp:
+            for name, rows, encoding in (("overhead", np.array([[1., .3], [2., .6]], dtype="<f4"), "int8"),
+                                         ("compressible", np.zeros((1024, 16), dtype="<f4"), "fp32")):
+                source = Path(tmp) / (name + ".f32")
+                source.write_bytes(rows.tobytes())
+                target = Path(tmp) / name
+                meta = pack_quantized_file(source, target, rows.shape[1], encoding, native="auto")
+                expected_backend = "raw_mmap" if name == "overhead" else "native"
+                self.assertEqual(meta["backend"], expected_backend)
+                self.assertEqual(meta["backend_policy"], "auto_smallest_bundle")
+                self.assertLessEqual(meta["storage"]["artifact_bytes"], len(rows) * meta["row_bytes"])
+                expected = decode_rows(encode_rows(rows, encoding), rows.shape[1], encoding)
+                with QuantizedRows(target, self.library) as table:
+                    ids = [len(rows) - 1, 0, len(rows) - 1]
+                    self.assertEqual(table.gather(ids).tobytes(), expected[ids].tobytes())
+            with self.assertRaisesRegex(ValueError, "identity"):
+                pack_quantized_file(source, Path(tmp) / "invalid", rows.shape[1], "int8",
+                                    native="auto", representatives=[0] * len(rows))
+
     @unittest.skipUnless(torch is not None, "optional PyTorch required")
     def test_quantized_reader_preserves_model_reduction_logits_and_restores_on_failure(self):
         from tools.quantized_memory import pack_quantized, encode_rows, decode_rows
diff --git a/tools/analyze_quantized_capacity.py b/tools/analyze_quantized_capacity.py
index 31736da..b9c7229 100644
--- a/tools/analyze_quantized_capacity.py
+++ b/tools/analyze_quantized_capacity.py
@@ -49,6 +49,11 @@ def analyze(report):
                       batch_rows=workers[0]["batch_rows"], query_buffer_bytes=workers[0]["query_buffer_bytes"],
                       cache_budget_bytes=workers[0]["cache_budget_bytes"],
                       all_query_bytes_exact=all(w["all_query_bytes_exact"] for w in workers))
+        if variant == "fp32-direct" and workers[0]["source_commit"] == "20d111c0830239b7b19ba787479a00fdffb90b07":
+            # The frozen run's field counted active output only; its unused
+            # encoded scratch allocation is retained in actual RSS/timings.
+            target["query_buffer_bytes"] += workers[0]["batch_rows"] * report["shape"][1] * 4
+            target["buffer_accounting_note"] = "Corrected allocated bytes: frozen raw worker field omitted unused FP32 scratch; RSS is unchanged."
         for phase in ("first_trace", "second_trace", "hot_repeated"):
             target[phase] = {"wall_" + key: range_summary([float(np.percentile(w[phase]["wall"]["samples_ms"], q)) for w in workers])
                              for key, q in (("p50_ms", 50), ("p95_ms", 95), ("p99_ms", 99))}
diff --git a/tools/benchmark_quantized_capacity.py b/tools/benchmark_quantized_capacity.py
index 7c77499..ccbca14 100644
--- a/tools/benchmark_quantized_capacity.py
+++ b/tools/benchmark_quantized_capacity.py
@@ -128,7 +128,8 @@ def query(args):
     queries = [(np.asarray(q["ids"], dtype="<u8"), q["sha256_by_encoding"][args.encoding]) for q in case["queries"]]
     output = np.empty((report["batch_rows"], args.dim), dtype="<f4")
     scratch = np.empty((report["batch_rows"], width), dtype="u1")
-    report["query_buffer_bytes"] = output.nbytes + (0 if args.backend == "direct" else scratch.nbytes)
+    report["query_buffer_bytes"] = output.nbytes + scratch.nbytes
+    report["active_query_buffer_bytes"] = output.nbytes + (0 if args.backend == "direct" else scratch.nbytes)
 
     def gather(item):
         ids, expected = item
diff --git a/tools/quantized_memory.py b/tools/quantized_memory.py
index cdef67b..943ef89 100644
--- a/tools/quantized_memory.py
+++ b/tools/quantized_memory.py
@@ -68,6 +68,8 @@ def pack_quantized(rows, directory, encoding, *, native=True, representatives=No
     chunks. Native block descriptors and optional dedup/order/representative
     indexes still grow with table size; chunk_rows is not a total RSS cap.
     A staging file holds encoded rows on disk until native packing completes.
+    native="auto" optionally discards a larger native bundle in favor of raw;
+    it is a size policy for identity rows, not a latency optimization guarantee.
     """
     rows = np.asarray(rows)
     if rows.ndim != 2:
@@ -113,6 +115,9 @@ def _pack_quantized(rows, directory, encoding, *, native=True, representatives=N
     if min(rows.shape) < 1 or type(chunk_rows) is not int or chunk_rows < 1:
         raise ValueError("nonempty matrix and positive integer chunk_rows required")
     width = row_width(rows.shape[1], encoding)
+    automatic = native == "auto"
+    if automatic and (representatives is not None or row_order is not None or deduplicate):
+        raise ValueError("auto backend requires identity rows without structural compaction")
     if not native and (representatives is not None or row_order is not None or deduplicate):
         raise ValueError("raw baseline must retain original row order without compaction")
     directory = Path(directory)
@@ -120,17 +125,21 @@ def _pack_quantized(rows, directory, encoding, *, native=True, representatives=N
     try:
         source = directory / "staging.rows"
         source_digest = hashlib.sha256()
+        encoded_digest = hashlib.sha256() if automatic else None
         with source.open("wb") as stream:
             for start in range(0, len(rows), chunk_rows):
                 chunk = np.ascontiguousarray(rows[start:start + chunk_rows], dtype="<f4")
                 encoded = encode_rows(chunk, encoding)
                 source_digest.update(chunk.tobytes())
+                if encoded_digest is not None:
+                    encoded_digest.update(encoded.tobytes())
                 stream.write(encoded.tobytes())
         table = directory / ("table.men" if native else "table.rows")
         if native:
             storage = pack_native(source, table, width, deduplicate=deduplicate,
                                   predictor="xor", representatives=representatives,
                                   row_order=row_order, max_block_bytes=max_block_bytes)
+            candidate_bytes = table.stat().st_size
         else:
             storage = {"artifact_bytes": source.stat().st_size, "unique_rows": len(rows),
                        "row_map_bytes": 0, "deduplicate": False}
@@ -154,9 +163,9 @@ def _pack_quantized(rows, directory, encoding, *, native=True, representatives=N
                 staged._mmap.close()
         if audit_source_digest.digest() != source_digest.digest():
             raise ValueError("FP32 source changed during export")
-        if native:
+        if native and not automatic:
             source.unlink()
-        else:
+        elif not native:
             source.rename(table)
         table_digest = hashlib.sha256()
         with table.open("rb") as stream:
@@ -172,6 +181,23 @@ def _pack_quantized(rows, directory, encoding, *, native=True, representatives=N
                     "int8_scale_bytes_per_physical_row": 4 if encoding == "int8" else 0,
                     "rounding": "nearest-even; symmetric [-127,127] per-row scale" if encoding == "int8" else encoding,
                     "contract": "frozen original IDs; exact encoded representative bytes; quantization/sharing may change float32 rows"}
+        if automatic:
+            metadata.update(backend_policy="auto_smallest_bundle", candidate_native_table_bytes=candidate_bytes,
+                            backend_selection_note="Choose smallest table + codec JSON including maps/descriptors; common keys cancel. Candidate construction still occurs. Latency is not the selection criterion.")
+            raw_bytes = source.stat().st_size
+            raw_metadata = dict(metadata, backend="raw_mmap", table_file="table.rows",
+                                table_sha256=encoded_digest.hexdigest(), storage={
+                                    "artifact_bytes": raw_bytes, "unique_rows": len(rows),
+                                    "row_map_bytes": 0, "deduplicate": False})
+            def metadata_bytes(value):
+                return len((json.dumps(value, indent=2, sort_keys=True) + "\n").encode("utf-8"))
+            if raw_bytes + metadata_bytes(raw_metadata) <= candidate_bytes + metadata_bytes(metadata):
+                table.unlink()
+                table = directory / "table.rows"
+                source.rename(table)
+                metadata = raw_metadata
+            else:
+                source.unlink()
         (directory / "codec.json").write_text(json.dumps(metadata, indent=2, sort_keys=True) + "\n")
         return metadata
     except BaseException:

From bf48f414652688e95b51988bf0ed80c404452cd1 Mon Sep 17 00:00:00 2001
From: initial-d <duyimin123@163.com>
Date: Sat, 31 Oct 2026 19:38:55 +0800
Subject: [PATCH 4/4] Publish matched 1.85M-row capacity, CPU, RSS and
 raw-fallback evidence

---
 README.md                                     |    1 +
 docs/index.md                                 |    1 +
 docs/ngram_memory_research_plan.md            |    3 +-
 .../README.md                                 |  201 +
 .../auto-build.json                           |  335 +
 .../auto-build.py                             |   21 +
 .../auto-run.log                              |    1 +
 .../auto-tests.log                            |    5 +
 .../auto-verify.json                          |  303 +
 .../auto-verify.log                           |    0
 .../build.log                                 |    0
 .../checks-ssh-timeout.txt                    |    7 +
 .../checks.sh                                 |   13 +
 .../compiler.txt                              |    5 +
 .../local-tests.txt                           |    5 +
 .../old-build.json                            |  340 +
 .../old-build.py                              |   22 +
 .../old-run.log                               |    1 +
 .../old-run.sh                                |    8 +
 .../report.json.gz                            |  Bin 0 -> 413668 bytes
 .../run.log                                   |   62 +
 .../run.sh                                    |   17 +
 .../scale-performance.png                     |  Bin 0 -> 169108 bytes
 .../scale-performance.svg                     | 3043 ++++++++
 .../setup.sh                                  |   38 +
 .../summary.json                              | 6430 +++++++++++++++++
 .../supplement-run.log                        |    0
 .../supplement-run.sh                         |   19 +
 .../supplement-setup.sh                       |   61 +
 .../tests.log                                 |    5 +
 .../tests.txt                                 |   12 +
 tools/analyze_quantized_capacity.py           |   14 +-
 32 files changed, 10969 insertions(+), 4 deletions(-)
 create mode 100644 docs/quantized_capacity_evidence_20261031/README.md
 create mode 100644 docs/quantized_capacity_evidence_20261031/auto-build.json
 create mode 100644 docs/quantized_capacity_evidence_20261031/auto-build.py
 create mode 100644 docs/quantized_capacity_evidence_20261031/auto-run.log
 create mode 100644 docs/quantized_capacity_evidence_20261031/auto-tests.log
 create mode 100644 docs/quantized_capacity_evidence_20261031/auto-verify.json
 create mode 100644 docs/quantized_capacity_evidence_20261031/auto-verify.log
 create mode 100644 docs/quantized_capacity_evidence_20261031/build.log
 create mode 100644 docs/quantized_capacity_evidence_20261031/checks-ssh-timeout.txt
 create mode 100644 docs/quantized_capacity_evidence_20261031/checks.sh
 create mode 100644 docs/quantized_capacity_evidence_20261031/compiler.txt
 create mode 100644 docs/quantized_capacity_evidence_20261031/local-tests.txt
 create mode 100644 docs/quantized_capacity_evidence_20261031/old-build.json
 create mode 100644 docs/quantized_capacity_evidence_20261031/old-build.py
 create mode 100644 docs/quantized_capacity_evidence_20261031/old-run.log
 create mode 100644 docs/quantized_capacity_evidence_20261031/old-run.sh
 create mode 100644 docs/quantized_capacity_evidence_20261031/report.json.gz
 create mode 100644 docs/quantized_capacity_evidence_20261031/run.log
 create mode 100644 docs/quantized_capacity_evidence_20261031/run.sh
 create mode 100644 docs/quantized_capacity_evidence_20261031/scale-performance.png
 create mode 100644 docs/quantized_capacity_evidence_20261031/scale-performance.svg
 create mode 100644 docs/quantized_capacity_evidence_20261031/setup.sh
 create mode 100644 docs/quantized_capacity_evidence_20261031/summary.json
 create mode 100644 docs/quantized_capacity_evidence_20261031/supplement-run.log
 create mode 100644 docs/quantized_capacity_evidence_20261031/supplement-run.sh
 create mode 100644 docs/quantized_capacity_evidence_20261031/supplement-setup.sh
 create mode 100644 docs/quantized_capacity_evidence_20261031/tests.log
 create mode 100644 docs/quantized_capacity_evidence_20261031/tests.txt

diff --git a/README.md b/README.md
index 086ef29..7ba71e1 100644
--- a/README.md
+++ b/README.md
@@ -110,6 +110,7 @@ external data or GPU. It checks integration, not representative compression.
 | [Structural contribution controls](docs/structural_native_evidence_20261030/README.md) | Trained SGNS/GRU references measure DATrie and approximate joint sharing separately; exact mode finds no identical rows to merge |
 | [FP16/INT8 + structural controls](docs/quantized_structural_evidence_20261031/README.md) | Same trained tables retain additional approximate savings after quantization; 4-order GRU INT8 regresses; quality failures and fixed-default audit are separate |
 | [1.85M trained-row capacity](docs/cpu_capacity_evidence_20261030/README.md) / [sparse blocks](docs/sparse_blocks_evidence_20261030/README.md) | Smaller blocks lower native miss latency 16–27× relative to the previous native layout; raw mmap remains faster |
+| [Large FP16/INT8 capacity and CPU controls](docs/quantized_capacity_evidence_20261031/README.md) | 54 fresh query workers; FP16 native saves 52.29% backend bytes versus raw FP32; INT8 native expands versus raw INT8, prompting an optional raw fallback; quantization is lossy |
 | [TinyEngram/Qwen trained integration](docs/tinyengram_qwen_evidence_20261030/README.md) / [CUDA controls](docs/qwen_cuda_performance_20261030/README.md) | Preserved trained outputs and measured CPU/device costs; native lookup remains slower than dense offload on these traces |
 
 Official DeepSeek Engram verification uses its small demonstration, not a
diff --git a/docs/index.md b/docs/index.md
index 2a475ce..4b38393 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -17,6 +17,7 @@
 - [Original DATrie / mark-compact contribution ablations](structural_native_evidence_20261030/README.md)
 - [Same-trained-table FP16/INT8 and structural-sharing controls](quantized_structural_evidence_20261031/README.md)
 - [1.85M trained-row CPU capacity](cpu_capacity_evidence_20261030/README.md)
+- [Large FP16/INT8 capacity, construction RSS and fresh CPU traces](quantized_capacity_evidence_20261031/README.md)
 - [Sparse-block native miss latency](sparse_blocks_evidence_20261030/README.md)
 - [Native query/cache controls](native_query_evidence_20261030/README.md)
 - [Causal language-model quality controls](causal_lm_evidence_20261024/README.md)
diff --git a/docs/ngram_memory_research_plan.md b/docs/ngram_memory_research_plan.md
index 68a2a8b..7806a4d 100644
--- a/docs/ngram_memory_research_plan.md
+++ b/docs/ngram_memory_research_plan.md
@@ -126,8 +126,9 @@ work.
 | Sparse native queries | [1.85M trained rows](cpu_capacity_evidence_20261030/README.md) and [smaller blocks](sparse_blocks_evidence_20261030/README.md) | Misses improved 16–27× over the prior layout; raw mmap remains faster |
 | DATrie / mark-compact | [Trained SGNS/GRU ablations](structural_native_evidence_20261030/README.md) | Exact key indexing helps these traces; no identical structural rows found; extra joint row savings are approximate |
 | Quantization + structural sharing | [18 trained tables, 486 controls](quantized_structural_evidence_20261031/README.md) | Additional savings remain after FP16/INT8 on these references; low-order INT8 can regress; validation-selected test failures are retained |
+| Quantized scale and CPU serving | [1.85M rows, 54 fresh workers](quantized_capacity_evidence_20261031/README.md) | FP16 native saves storage with broad-query cost; INT8 native expands versus raw INT8; vector error is measured without large-table task quality |
 | End-to-end artifact cost | [FastText matched controls](fasttext_native_evidence_20261031/README.md) | Whole bundle saves only 0.46%; queries are slower; structural order adds no benefit on this model |
-| Construction/runtime resources | [Implementation boundaries](native_ngram_memory.md) | Structural planning copies full rows/maps offline; cache budgets do not bound RSS; FastText retains an unused 200 MB hash allocation |
+| Construction/runtime resources | [Streaming quantized files and resource controls](quantized_capacity_evidence_20261031/README.md), [implementation boundaries](native_ngram_memory.md) | File codecs/hashes use chunks; native descriptors and optional planner indexes still grow; structural planning copies full rows/maps; cache budgets do not bound RSS; FastText retains an unused 200 MB hash allocation |
 
 Correctness is a starting point on supported paths. Useful compression and
 serving gains still depend on the trained table and workload.
diff --git a/docs/quantized_capacity_evidence_20261031/README.md b/docs/quantized_capacity_evidence_20261031/README.md
new file mode 100644
index 0000000..e908401
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/README.md
@@ -0,0 +1,201 @@
+# Quantized capacity and CPU lookup on 1.85M trained n-gram rows
+
+This extends the existing large-table reference with FP16/INT8, streaming
+construction, smaller-block controls and repeated fresh-process CPU traces.
+It reuses **1,855,907 × 256 genuinely updated FP32 rows**, or 475,112,192 scalar
+values and 1,900,448,768 source bytes. No rows are synthesized or duplicated to
+claim scale. The 100K/500K prefixes reuse actual rows and measure storage
+construction scaling, not additional trained models.
+
+The full CPU run passed **8 complete layouts, 2 trained-row prefix builds and 54 independent query workers**. FP16 native saves **52.29%** of complete backend bytes versus raw FP32, including common keys; **5.62%** is extra over raw FP16. Raw INT8 saves **73.78%**, but native INT8 expands the complete backend by **1.23%** versus raw INT8. These are different contributions: quantization savings must not be attributed to structural compression.
+
+## Complete storage and construction
+
+| Layout | Table + codec + keys bytes | Saving vs raw FP32 | Extra saving vs matched raw encoding | Builder peak RSS MiB |
+| --- | ---: | ---: | ---: | ---: |
+| fp32-raw | 1,921,879,166 | 0.00% | +0.00% | 59.3 |
+| fp32-native | 1,809,925,278 | 5.83% | +5.83% | 86.1 |
+| fp16-raw | 971,654,781 | 49.44% | +0.00% | 58.9 |
+| fp16-native | 917,021,789 | 52.29% | +5.62% | 65.1 |
+| int8-raw | 503,966,261 | 73.78% | +0.00% | 60.2 |
+| int8-native | 510,146,194 | 73.46% | -1.23% | 61.7 |
+| int8-native-rows-4 | 533,125,924 | 72.26% | -5.79% | 126.4 |
+| int8-native-rows-1 | 578,203,012 | 69.91% | -14.73% | 379.7 |
+
+The common key registry is **21,429,556 bytes**. The FP32 paths reconstruct all original bytes. FP16 has **0.0207%** global relative Frobenius error and **0.0263%** maximum per-row relative L2. INT8 has **0.779%** global and **1.160%** maximum per-row relative L2. Native variants add no further vector error in this identity-row study. No downstream loss, perplexity or model-output quality budget is measured.
+
+INT8 1-row blocks are all raw fallback: map/descriptors add 40 bytes per original row. The complete bundle grows **14.73%** versus raw INT8, and builder RSS rises to 379.7 MiB. A raw block fallback alone therefore does not prevent whole-format expansion.
+
+| Actual trained-row prefix | Source FP32 bytes | INT8 native table bytes | Builder peak RSS MiB |
+| --- | ---: | ---: | ---: |
+| 100,000 | 102,400,000 | 26,390,162 | 63.6 |
+| 500,000 | 512,000,000 | 131,959,408 | 62.0 |
+| 1,855,907 | 1,900,448,768 | 488,715,334 | 61.7 |
+
+The observed 8 KiB INT8 builders remain around **62–64 MiB** across these prefixes. This is one fresh builder per size, not an asymptotic constant-memory claim: descriptor storage grows with block count. Source weights stay on disk, and temporary encoded/spool files remain outside serving bytes.
+
+## CPU lookup and cache churn
+
+| Layout | First lexical p50 ms | First uniform p50 ms | Second uniform p50 ms | Hot lexical p50 ms | RSS after first uniform MiB |
+| --- | ---: | ---: | ---: | ---: | ---: |
+| fp32-direct | 0.146 | 0.629 | 0.089 | 0.0383 | 280.1 |
+| fp32-raw | 0.199 | 0.692 | 0.140 | 0.0814 | 280.7 |
+| fp32-native | 8.165 | 32.279 | 30.820 | 0.1168 | 654.2 |
+| fp16-raw | 0.496 | 0.964 | 0.476 | 0.4078 | 264.1 |
+| fp16-native | 5.832 | 34.150 | 33.126 | 0.4415 | 536.0 |
+| int8-raw | 0.235 | 0.615 | 0.183 | 0.1614 | 245.1 |
+| int8-native | 3.946 | 31.550 | 30.702 | 0.1959 | 411.8 |
+| int8-native-rows-4 | 0.564 | 1.302 | 0.367 | 0.2475 | 277.0 |
+| int8-native-rows-1 | 0.346 | 0.770 | 0.361 | 0.2397 | 316.0 |
+
+INT8 1-row layout lowers native first uniform p50 from **31.55 to 0.770 ms (41.0×)**. It remains slower and larger than **raw INT8 (0.615 ms)**. Native FP16 saves storage, but broad repeated access stays around **33 ms**, because a 4 MiB row cache does not retain the entire stress trace. Small hot-set timing alone conceals this cost.
+
+Raw INT8 first uniform latency is near the direct FP32 mmap control on this shared host; these overlapping process ranges do not establish a speedup. Its hot lexical gather is **4.2× slower** than direct FP32, including CPU dequantization. The direct FP32 control also exposes wrapper overhead in the FP32 encoded reader.
+
+![Same-source storage, latency and construction resources](scale-performance.svg)
+
+## Matched builder improvement and measured raw fallback
+
+The pre-streaming main at
+[`1334883`](https://github.com/initial-d/ngram-store/commit/13348839cc414cceba4477af2e07b04da23374da)
+exports the same complete INT8 native artifact in a fresh process using a
+source FP32 mmap. Old and new **source, decoded and table hashes are identical**.
+Peak process RSS drops from **9,118.0 MiB to 61.7 MiB (147.9× lower)**. Wall time
+is 45.10 versus 43.68 seconds; this establishes a memory improvement, not a
+significant CPU speedup. Old RSS includes mapped source pages and full
+conversion/hash arrays; the file path avoids source mmap residency and those
+whole-table temporaries. Builder order is fixed on the same shared host, with
+no cgroup limit or OOM test.
+
+The optional `native="auto"` policy is verified afterward at
+[`9485969`](https://github.com/initial-d/ngram-store/commit/9485969066ee4be466673cde07823330da1a7658).
+It compares actual table plus codec JSON bytes for identity rows; common keys
+cancel. On this full INT8 source it discards the expanded native candidate and
+publishes **raw_mmap**, preserving the verified raw control's source, decoded
+and table hashes. All **1,855,907** auto rows also pass a fresh reader check.
+Auto construction peaks at **62.2 MiB**, takes 44.33 seconds and still constructs
+the native candidate before choosing. It selects for size, not latency, and
+rejects structural forwarding/reordering/dedup. Explicit raw/native choices
+remain available and unchanged.
+
+The auto bundle is **482,536,985 bytes without common keys**, or 503,966,541 bytes
+with them. Its policy audit adds 280 metadata bytes versus the explicit raw
+control; that small cost is retained. Native and raw candidate codec metadata
+are included in selection, rather than trusting per-block fallback alone.
+See [old-build.json](old-build.json), [auto-build.json](auto-build.json),
+[auto-verify.json](auto-verify.json), [old-build.py](old-build.py),
+[auto-build.py](auto-build.py), [old-run.sh](old-run.sh) and
+[supplement-run.sh](supplement-run.sh). These are separate source-pinned runs
+performed after all main query workers finished. The main report's timings
+remain at the original frozen runtime; the later runner also corrects only the
+direct-buffer reporting field outside the timed gather loop.
+
+Linux's earlier full suite reports 140 tests with 17 dependency/platform skips
+in [tests.txt](tests.txt). The later auto/codec/capacity suite passes all 12 tests
+in [auto-tests.log](auto-tests.log); local final suite passes 141 tests with 26
+skips. The full-suite SSH launcher timed out at 60 seconds while remote tests
+completed in 66.453 seconds; [checks-ssh-timeout.txt](checks-ssh-timeout.txt)
+preserves this launcher failure separately from passed experiment workers.
+
+
+## What these measurements cover
+
+Quantization is approximate to FP32. INT8 stores a FP32 scale in each row,
+alongside 256 signed codes; FP16 stores rounded values. Native compression
+preserves these encoded bytes and original IDs. Every full-table variant is
+checked against a separately computed codec oracle for **all original IDs**,
+including the preallocated FP32 decode path. Source, decoded and artifact
+hashes are retained. Vector error does not establish downstream task quality.
+
+These variants use identity row order without deduplication or structural
+sharing. Savings over raw FP16/INT8 therefore measure the ordinary block codec
+after quantization, **not a DATrie/mark-compact gain**. The original algorithm's
+contribution is measured separately in [trained structural controls](../structural_native_evidence_20261030/README.md),
+[small quantized references](../quantized_structural_evidence_20261031/README.md)
+and the [large FP32 table](../cpu_capacity_evidence_20261030/README.md).
+The latter has only 0.12% extra joint row savings, which remains a useful
+boundary rather than being replaced by the quantization result here.
+
+The complete backend count includes table/map/descriptors/scales, codec JSON
+and the same actual key registry JSON. Keys are counted for every full-table
+variant, even models that already have numeric row IDs. No backbone/model
+checkpoint, runtime/framework, training provenance map or temporary build
+files are counted as serving bytes. Staging/spool/publication files need extra
+disk space; peak temporary disk usage is not measured. Structural planning
+still holds full vectors/maps offline.
+
+## Trained-row provenance
+
+The cached enwik8 raw bytes are split 90/10 before preprocessing. The training
+registry uses lowercase ASCII words of length 2–64, min-count 2 and n-gram
+orders 2–12. The original CPU SGNS reference has dimension 256, five negatives,
+seed 42, four threads, three finite epochs and 1,212,126 sampled adjacent pairs.
+Rare-center coverage sampling overweights rare centers; this is neither
+ordinary full-corpus SGNS nor evidence of convergence or model quality.
+
+The initial export rejected 5,014 unchanged rows. The registered changed-row
+subset explicitly excludes 0.2694% and retains the original training-ID map.
+Every exported row is finite and changed. This study uses that exact subset;
+it does not delete rows from a full-model converter. Original training and
+exclusion details remain in the [capacity provenance](../cpu_capacity_evidence_20261030/README.md).
+
+## Protocol and reproducibility
+
+Each constructor, verifier and query trace runs in a separate process. Full
+table codecs use at most 8,192 decoded bytes/block: 8 FP32, 16 FP16 or 31 INT8
+rows at dimension 256. Additional INT8 1/4-row layouts trade descriptor cost for
+sparse decoding. All exporters use 4,096-row codec/hash chunks and identity
+forwarding. Native descriptors still grow with block count, so this is a
+bounded codec working set rather than a constant-RSS guarantee.
+
+The held-out lexical and uniform-ID stress traces are unchanged from the
+capacity reference: 65,536 requests each in 512-row batches. Uniform access is
+synthetic **access on real vectors**, not synthetic-vector compression evidence.
+Each worker measures the first complete trace, a second complete replay, and
+20 repetitions of the first eight batches after warmup. This separates broad
+cache churn from the small hot subset. Native row-cache payload is 4 MiB;
+mapped file pages, output, cache indexes and runtime metadata are extra.
+
+Three rounds independently shuffle all variant/trace jobs with seeds 42–44.
+Tables report the median of per-process p50 values; p95/p99, throughput and
+per-process ranges are in [summary.json](summary.json). Ranges across three
+processes are not confidence intervals. Both encoded backends use the same
+preallocated encoded scratch and FP32 output. The direct FP32 mmap control
+uses NumPy `take(out=..., mode="clip")` into FP32 without dequantization or
+the codec wrapper. Query hashes and codec-counter collection occur outside
+the measured gather interval. Counters measure logical compressed/decompressed
+codec bytes, excluding raw-row copies and cache hits; they are not disk I/O.
+The frozen direct worker's buffer field counts only its active 512 KiB output;
+it also allocates an unused 512 KiB scratch. The summary counts both, and RSS
+already includes all resident allocations. The current runner corrects that
+reporting field without changing the measured gather loop.
+
+The shared Linux AMD EPYC 7742 host runs Python 3.11.15, NumPy 2.2.6 and has
+PyTorch 2.11.0 installed (unused by the experiment). CPU workers use nice
+19 and one OMP/MKL/OpenBLAS thread. No GPU programs are queried or modified,
+weights retrained, or external data downloaded. Verification and construction
+warm filesystem pages: first trace means a fresh process and empty application
+cache, **not disk-cold access**. CPU frequency/exclusivity, memory-pressure
+behavior and whole-model inference are outside the study.
+
+The frozen runtime source is
+[`20d111c`](https://github.com/initial-d/ngram-store/commit/20d111c0830239b7b19ba787479a00fdffb90b07).
+[run.sh](run.sh) contains the exact command; [setup.sh](setup.sh) preserves
+compiler flags, and [compiler.txt](compiler.txt), [tests.txt](tests.txt),
+[run.log](run.log) and [report.json.gz](report.json.gz) preserve environment,
+raw samples/counters, commands, source/library/table hashes and outcomes.
+Raw text, keys, weights and serving tables stay on the user's machine.
+
+With the cached trained source available, build the native library from the
+pinned commit and run `run.sh`. Analyze the exported report locally:
+
+```bash
+python -m tools.analyze_quantized_capacity \
+  --report docs/quantized_capacity_evidence_20261031/report.json.gz \
+  --output-dir artifacts/quantized-capacity-analysis --plots
+```
+
+These are storage/CPU results from one English sparse-training reference.
+They do not establish a large-model memory-quality budget, original learned
+Engram checkpoint compatibility, production latency or a universal win over
+raw mmap/other compression engines.
diff --git a/docs/quantized_capacity_evidence_20261031/auto-build.json b/docs/quantized_capacity_evidence_20261031/auto-build.json
new file mode 100644
index 0000000..23b70ca
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/auto-build.json
@@ -0,0 +1,335 @@
+{
+  "status": "passed",
+  "python": "3.11.15 (main, Mar 11 2026, 17:20:07) [GCC 14.3.0]",
+  "numpy": "2.2.6",
+  "os": "Linux-5.4.0-42-generic-x86_64-with-glibc2.35",
+  "cpu": "AMD EPYC 7742 64-Core Processor",
+  "command": "/llm-align/duyimin/miniconda3/envs/gemma4/bin/python /llm-align/duyimin/ngram-scale-20261031/auto-build.py",
+  "source_commit": "9485969066ee4be466673cde07823330da1a7658",
+  "cuda_visible_devices": "",
+  "cpu_affinity": [
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+    "MKL_NUM_THREADS": "1",
+    "OPENBLAS_NUM_THREADS": "1"
+  },
+  "memory_before": {
+    "peak_rss_bytes": 31940608,
+    "VmSize_bytes": 131457024,
+    "VmRSS_bytes": 31940608,
+    "Rss_bytes": 31948800,
+    "Pss_bytes": 21704704,
+    "Shared_Clean_bytes": 10780672,
+    "Shared_Dirty_bytes": 0,
+    "Private_Clean_bytes": 856064,
+    "Private_Dirty_bytes": 20312064,
+    "Anonymous_bytes": 20312064
+  },
+  "label": "auto INT8 native/raw bundle selection",
+  "shape": [
+    1855907,
+    256
+  ],
+  "metadata": {
+    "schema_version": 1,
+    "shape": [
+      1855907,
+      256
+    ],
+    "encoding": "int8",
+    "byteorder": "little",
+    "backend": "raw_mmap",
+    "table_file": "table.rows",
+    "row_bytes": 260,
+    "storage": {
+      "artifact_bytes": 482535820,
+      "unique_rows": 1855907,
+      "row_map_bytes": 0,
+      "deduplicate": false
+    },
+    "source_float32_sha256": "0e5d4be0b156c5e9f0d745292876e48f78772c599d97902619123512955d82fc",
+    "decoded_float32_sha256": "035d3a5223898f4bf0552b1564a724a0c7f6458e4840887c6f6220d1d2dde286",
+    "table_sha256": "52fb9be46af385ca15a8174ceb87840a85c8532c5e2bfa9a1dd80cc27123893a",
+    "source_bytes_preserved": false,
+    "export_chunk_rows": 4096,
+    "int8_scale_bytes_per_physical_row": 4,
+    "rounding": "nearest-even; symmetric [-127,127] per-row scale",
+    "contract": "frozen original IDs; exact encoded representative bytes; quantization/sharing may change float32 rows",
+    "backend_policy": "auto_smallest_bundle",
+    "candidate_native_table_bytes": 488715334,
+    "backend_selection_note": "Choose smallest table + codec JSON including maps/descriptors; common keys cancel. Candidate construction still occurs. Latency is not the selection criterion."
+  },
+  "wall_seconds": 44.33001665980555,
+  "cpu_seconds": 43.961150704000005,
+  "memory_after": {
+    "peak_rss_bytes": 65236992,
+    "VmSize_bytes": 142094336,
+    "VmRSS_bytes": 42684416,
+    "Rss_bytes": 42774528,
+    "Pss_bytes": 32279552,
+    "Shared_Clean_bytes": 11059200,
+    "Shared_Dirty_bytes": 0,
+    "Private_Clean_bytes": 921600,
+    "Private_Dirty_bytes": 30793728,
+    "Anonymous_bytes": 30793728
+  },
+  "bundle_bytes": 482536985,
+  "auto_matches_verified_raw_source_decoded_and_table_hashes": true
+}
diff --git a/docs/quantized_capacity_evidence_20261031/auto-build.py b/docs/quantized_capacity_evidence_20261031/auto-build.py
new file mode 100644
index 0000000..0c94677
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/auto-build.py
@@ -0,0 +1,21 @@
+import json,sys,time
+from pathlib import Path
+root=Path('/llm-align/duyimin/ngram-scale-20261031')
+sys.path.insert(0,str(root/'source-auto'))
+from tools.benchmark_quantized_capacity import software_environment, memory
+from tools.quantized_memory import pack_quantized_file
+source=Path('/llm-align/duyimin/meft-cpu-capacity-20261030/training2/trained.f32')
+report=dict(status='running',**software_environment(),memory_before=memory(),
+            label='auto INT8 native/raw bundle selection',shape=[1855907,256])
+started,cpu=time.perf_counter(),time.process_time()
+metadata=pack_quantized_file(source,root/'auto-int8',256,'int8',native='auto',chunk_rows=4096,max_block_bytes=8192)
+report.update(status='passed',metadata=metadata,wall_seconds=time.perf_counter()-started,
+              cpu_seconds=time.process_time()-cpu,memory_after=memory(),
+              bundle_bytes=sum(p.stat().st_size for p in (root/'auto-int8').iterdir()))
+current=json.loads((root/'results/build-int8-raw.json').read_text())['metadata']
+for key in ('source_float32_sha256','decoded_float32_sha256','table_sha256'):
+ if current[key] != metadata[key]: raise AssertionError('auto/raw differs: '+key)
+if metadata['backend'] != 'raw_mmap': raise AssertionError('expected measured INT8 expansion to select raw')
+report['auto_matches_verified_raw_source_decoded_and_table_hashes']=True
+(root/'auto-build.json').write_text(json.dumps(report,indent=2)+'\n')
+print(json.dumps({k:report[k] for k in ('status','wall_seconds','cpu_seconds','memory_after','bundle_bytes','auto_matches_verified_raw_source_decoded_and_table_hashes')}))
diff --git a/docs/quantized_capacity_evidence_20261031/auto-run.log b/docs/quantized_capacity_evidence_20261031/auto-run.log
new file mode 100644
index 0000000..3d4a7aa
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/auto-run.log
@@ -0,0 +1 @@
+{"status": "passed", "wall_seconds": 44.33001665980555, "cpu_seconds": 43.961150704000005, "memory_after": {"peak_rss_bytes": 65236992, "VmSize_bytes": 142094336, "VmRSS_bytes": 42684416, "Rss_bytes": 42774528, "Pss_bytes": 32279552, "Shared_Clean_bytes": 11059200, "Shared_Dirty_bytes": 0, "Private_Clean_bytes": 921600, "Private_Dirty_bytes": 30793728, "Anonymous_bytes": 30793728}, "bundle_bytes": 482536985, "auto_matches_verified_raw_source_decoded_and_table_hashes": true}
diff --git a/docs/quantized_capacity_evidence_20261031/auto-tests.log b/docs/quantized_capacity_evidence_20261031/auto-tests.log
new file mode 100644
index 0000000..99095ad
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/auto-tests.log
@@ -0,0 +1,5 @@
+............
+----------------------------------------------------------------------
+Ran 12 tests in 2.355s
+
+OK
diff --git a/docs/quantized_capacity_evidence_20261031/auto-verify.json b/docs/quantized_capacity_evidence_20261031/auto-verify.json
new file mode 100644
index 0000000..280e41e
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/auto-verify.json
@@ -0,0 +1,303 @@
+{
+  "status": "passed",
+  "python": "3.11.15 (main, Mar 11 2026, 17:20:07) [GCC 14.3.0]",
+  "numpy": "2.2.6",
+  "os": "Linux-5.4.0-42-generic-x86_64-with-glibc2.35",
+  "cpu": "AMD EPYC 7742 64-Core Processor",
+  "command": "/llm-align/duyimin/miniconda3/envs/gemma4/bin/python -m tools.benchmark_quantized_capacity --phase verify --source /llm-align/duyimin/meft-cpu-capacity-20261030/training2/trained.f32 --bundle /llm-align/duyimin/ngram-scale-20261031/auto-int8 --dim 256 --encoding int8 --backend raw --worker-report /llm-align/duyimin/ngram-scale-20261031/auto-verify.json --native-library /llm-align/duyimin/ngram-scale-20261031/source/build/libmeft_rows.so --chunk-rows 4096 --query-manifest /llm-align/duyimin/ngram-scale-20261031/results/queries.json",
+  "source_commit": "9485969066ee4be466673cde07823330da1a7658",
+  "cuda_visible_devices": "",
+  "cpu_affinity": [
+    0,
+    1,
+    2,
+    3,
+    4,
+    5,
+    6,
+    7,
+    8,
+    9,
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+    50,
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+    52,
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+    55,
+    56,
+    57,
+    58,
+    59,
+    60,
+    61,
+    62,
+    63,
+    64,
+    65,
+    66,
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+    69,
+    70,
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+    78,
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+    80,
+    81,
+    82,
+    83,
+    84,
+    85,
+    86,
+    87,
+    88,
+    89,
+    90,
+    91,
+    92,
+    93,
+    94,
+    95,
+    96,
+    97,
+    98,
+    99,
+    100,
+    101,
+    102,
+    103,
+    104,
+    105,
+    106,
+    107,
+    108,
+    109,
+    110,
+    111,
+    112,
+    113,
+    114,
+    115,
+    116,
+    117,
+    118,
+    119,
+    120,
+    121,
+    122,
+    123,
+    124,
+    125,
+    126,
+    127,
+    128,
+    129,
+    130,
+    131,
+    132,
+    133,
+    134,
+    135,
+    136,
+    137,
+    138,
+    139,
+    140,
+    141,
+    142,
+    143,
+    144,
+    145,
+    146,
+    147,
+    148,
+    149,
+    150,
+    151,
+    152,
+    153,
+    154,
+    155,
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+    157,
+    158,
+    159,
+    160,
+    161,
+    162,
+    163,
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+    165,
+    166,
+    167,
+    168,
+    169,
+    170,
+    171,
+    172,
+    173,
+    174,
+    175,
+    176,
+    177,
+    178,
+    179,
+    180,
+    181,
+    182,
+    183,
+    184,
+    185,
+    186,
+    187,
+    188,
+    189,
+    190,
+    191,
+    192,
+    193,
+    194,
+    195,
+    196,
+    197,
+    198,
+    199,
+    200,
+    201,
+    202,
+    203,
+    204,
+    205,
+    206,
+    207,
+    208,
+    209,
+    210,
+    211,
+    212,
+    213,
+    214,
+    215,
+    216,
+    217,
+    218,
+    219,
+    220,
+    221,
+    222,
+    223,
+    224,
+    225,
+    226,
+    227,
+    228,
+    229,
+    230,
+    231,
+    232,
+    233,
+    234,
+    235,
+    236,
+    237,
+    238,
+    239,
+    240,
+    241,
+    242,
+    243,
+    244,
+    245,
+    246,
+    247,
+    248,
+    249,
+    250,
+    251,
+    252,
+    253,
+    254
+  ],
+  "pytorch_installed_not_used": "2.11.0",
+  "thread_environment": {
+    "OMP_NUM_THREADS": "1",
+    "MKL_NUM_THREADS": "1",
+    "OPENBLAS_NUM_THREADS": "1"
+  },
+  "rows_verified": 1855907,
+  "all_original_ids_encoded_byte_exact": true,
+  "all_decoded_rows_oracle_byte_exact": true,
+  "source_sha256": "0e5d4be0b156c5e9f0d745292876e48f78772c599d97902619123512955d82fc",
+  "encoded_original_id_sha256": "52fb9be46af385ca15a8174ceb87840a85c8532c5e2bfa9a1dd80cc27123893a",
+  "decoded_original_id_sha256": "035d3a5223898f4bf0552b1564a724a0c7f6458e4840887c6f6220d1d2dde286",
+  "verify_seconds": 13.402055673999712,
+  "relative_frobenius": 0.007792033224643991,
+  "row_relative_l2": {
+    "p50": 0.005593181978794904,
+    "p99": 0.00904459455787198,
+    "max": 0.011602407628381531
+  },
+  "cosine_distance": {
+    "p50": 1.5581723388335966e-05,
+    "p99": 4.074664666232847e-05,
+    "max": 6.695415484603284e-05
+  },
+  "memory_after": {
+    "peak_rss_bytes": 608174080,
+    "VmSize_bytes": 229896192,
+    "VmRSS_bytes": 129957888,
+    "Rss_bytes": 130179072,
+    "Pss_bytes": 119347200,
+    "Shared_Clean_bytes": 11440128,
+    "Shared_Dirty_bytes": 0,
+    "Private_Clean_bytes": 1028096,
+    "Private_Dirty_bytes": 117710848,
+    "Anonymous_bytes": 117710848
+  }
+}
diff --git a/docs/quantized_capacity_evidence_20261031/auto-verify.log b/docs/quantized_capacity_evidence_20261031/auto-verify.log
new file mode 100644
index 0000000..e69de29
diff --git a/docs/quantized_capacity_evidence_20261031/build.log b/docs/quantized_capacity_evidence_20261031/build.log
new file mode 100644
index 0000000..e69de29
diff --git a/docs/quantized_capacity_evidence_20261031/checks-ssh-timeout.txt b/docs/quantized_capacity_evidence_20261031/checks-ssh-timeout.txt
new file mode 100644
index 0000000..a6cd44d
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/checks-ssh-timeout.txt
@@ -0,0 +1,7 @@
+The local final-check launcher used a 60-second SSH-wrapper timeout and exited
+with subprocess.TimeoutExpired. The remote command continued and preserved
+final-tests.log: 140 tests ran in 66.453 seconds, OK (skipped=17).
+
+This was a launcher timeout, not a failed codec/capacity test. No successful
+benchmark result is inferred from this timeout; the separate run.sh/status and
+raw report record each experiment worker's return code and verification result.
diff --git a/docs/quantized_capacity_evidence_20261031/checks.sh b/docs/quantized_capacity_evidence_20261031/checks.sh
new file mode 100644
index 0000000..8f11cf3
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/checks.sh
@@ -0,0 +1,13 @@
+#!/bin/bash
+set -eu
+ROOT=/llm-align/duyimin/ngram-scale-20261031
+PY=/llm-align/duyimin/miniconda3/envs/gemma4/bin/python
+export CUDA_VISIBLE_DEVICES=""
+export OMP_NUM_THREADS=1 OPENBLAS_NUM_THREADS=1 MKL_NUM_THREADS=1
+mkdir "$ROOT/tmp"
+export TMPDIR="$ROOT/tmp"
+cd "$ROOT"
+git clone checks.bundle checks-source > checks-clone.log 2>&1
+cd checks-source
+nice -n 19 "$PY" -m unittest discover -s tests > "$ROOT/final-tests.log" 2>&1
+tail -8 "$ROOT/final-tests.log"
diff --git a/docs/quantized_capacity_evidence_20261031/compiler.txt b/docs/quantized_capacity_evidence_20261031/compiler.txt
new file mode 100644
index 0000000..533f9fc
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/compiler.txt
@@ -0,0 +1,5 @@
+cc (Ubuntu 11.4.0-1ubuntu1~22.04.3) 11.4.0
+Copyright (C) 2021 Free Software Foundation, Inc.
+This is free software; see the source for copying conditions.  There is NO
+warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
+
diff --git a/docs/quantized_capacity_evidence_20261031/local-tests.txt b/docs/quantized_capacity_evidence_20261031/local-tests.txt
new file mode 100644
index 0000000..634ef77
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/local-tests.txt
@@ -0,0 +1,5 @@
+...................ss.s.........ss...............................................................................sssssssssssssssssssss.......
+----------------------------------------------------------------------
+Ran 141 tests in 11.724s
+
+OK (skipped=26)
diff --git a/docs/quantized_capacity_evidence_20261031/old-build.json b/docs/quantized_capacity_evidence_20261031/old-build.json
new file mode 100644
index 0000000..15d848b
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/old-build.json
@@ -0,0 +1,340 @@
+{
+  "status": "passed",
+  "python": "3.11.15 (main, Mar 11 2026, 17:20:07) [GCC 14.3.0]",
+  "numpy": "2.2.6",
+  "os": "Linux-5.4.0-42-generic-x86_64-with-glibc2.35",
+  "cpu": "AMD EPYC 7742 64-Core Processor",
+  "command": "/llm-align/duyimin/miniconda3/envs/gemma4/bin/python /llm-align/duyimin/ngram-scale-20261031/old-build.py",
+  "source_commit": "13348839cc414cceba4477af2e07b04da23374da",
+  "cuda_visible_devices": "",
+  "cpu_affinity": [
+    0,
+    1,
+    2,
+    3,
+    4,
+    5,
+    6,
+    7,
+    8,
+    9,
+    10,
+    11,
+    12,
+    13,
+    14,
+    15,
+    16,
+    17,
+    18,
+    19,
+    20,
+    21,
+    22,
+    23,
+    24,
+    25,
+    26,
+    27,
+    28,
+    29,
+    30,
+    31,
+    32,
+    33,
+    34,
+    35,
+    36,
+    37,
+    38,
+    39,
+    40,
+    41,
+    42,
+    43,
+    44,
+    45,
+    46,
+    47,
+    48,
+    49,
+    50,
+    51,
+    52,
+    53,
+    54,
+    55,
+    56,
+    57,
+    58,
+    59,
+    60,
+    61,
+    62,
+    63,
+    64,
+    65,
+    66,
+    67,
+    68,
+    69,
+    70,
+    71,
+    72,
+    73,
+    74,
+    75,
+    76,
+    77,
+    78,
+    79,
+    80,
+    81,
+    82,
+    83,
+    84,
+    85,
+    86,
+    87,
+    88,
+    89,
+    90,
+    91,
+    92,
+    93,
+    94,
+    95,
+    96,
+    97,
+    98,
+    99,
+    100,
+    101,
+    102,
+    103,
+    104,
+    105,
+    106,
+    107,
+    108,
+    109,
+    110,
+    111,
+    112,
+    113,
+    114,
+    115,
+    116,
+    117,
+    118,
+    119,
+    120,
+    121,
+    122,
+    123,
+    124,
+    125,
+    126,
+    127,
+    128,
+    129,
+    130,
+    131,
+    132,
+    133,
+    134,
+    135,
+    136,
+    137,
+    138,
+    139,
+    140,
+    141,
+    142,
+    143,
+    144,
+    145,
+    146,
+    147,
+    148,
+    149,
+    150,
+    151,
+    152,
+    153,
+    154,
+    155,
+    156,
+    157,
+    158,
+    159,
+    160,
+    161,
+    162,
+    163,
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+    165,
+    166,
+    167,
+    168,
+    169,
+    170,
+    171,
+    172,
+    173,
+    174,
+    175,
+    176,
+    177,
+    178,
+    179,
+    180,
+    181,
+    182,
+    183,
+    184,
+    185,
+    186,
+    187,
+    188,
+    189,
+    190,
+    191,
+    192,
+    193,
+    194,
+    195,
+    196,
+    197,
+    198,
+    199,
+    200,
+    201,
+    202,
+    203,
+    204,
+    205,
+    206,
+    207,
+    208,
+    209,
+    210,
+    211,
+    212,
+    213,
+    214,
+    215,
+    216,
+    217,
+    218,
+    219,
+    220,
+    221,
+    222,
+    223,
+    224,
+    225,
+    226,
+    227,
+    228,
+    229,
+    230,
+    231,
+    232,
+    233,
+    234,
+    235,
+    236,
+    237,
+    238,
+    239,
+    240,
+    241,
+    242,
+    243,
+    244,
+    245,
+    246,
+    247,
+    248,
+    249,
+    250,
+    251,
+    252,
+    253,
+    254
+  ],
+  "memory_before": {
+    "peak_rss_bytes": 29913088,
+    "VmSize_bytes": 129892352,
+    "VmRSS_bytes": 29913088,
+    "Rss_bytes": 30007296,
+    "Pss_bytes": 20105216,
+    "Shared_Clean_bytes": 10424320,
+    "Shared_Dirty_bytes": 0,
+    "Private_Clean_bytes": 856064,
+    "Private_Dirty_bytes": 18726912,
+    "Anonymous_bytes": 18726912
+  },
+  "label": "pre-streaming main INT8 native export",
+  "shape": [
+    1855907,
+    256
+  ],
+  "metadata": {
+    "schema_version": 1,
+    "shape": [
+      1855907,
+      256
+    ],
+    "encoding": "int8",
+    "byteorder": "little",
+    "backend": "native",
+    "table_file": "table.men",
+    "row_bytes": 260,
+    "storage": {
+      "format": "MEFTNAT1",
+      "format_version": 2,
+      "input_bytes": 482535820,
+      "artifact_bytes": 488715334,
+      "unique_rows": 1855907,
+      "row_map_bytes": 14847256,
+      "n_rows": 1855907,
+      "row_bytes": 260,
+      "block_rows": 31,
+      "blocks": 59868,
+      "max_block_bytes": 8192,
+      "raw_blocks": 30,
+      "compressed_blocks": 59838,
+      "zlib_blocks": 59799,
+      "xor_blocks": 39,
+      "deduplicate": false,
+      "predictor": "xor",
+      "reordered": false,
+      "external_representatives": false,
+      "marked_rows": 1855907
+    },
+    "source_float32_sha256": "0e5d4be0b156c5e9f0d745292876e48f78772c599d97902619123512955d82fc",
+    "decoded_float32_sha256": "035d3a5223898f4bf0552b1564a724a0c7f6458e4840887c6f6220d1d2dde286",
+    "table_sha256": "c2fe87dd534c414adecbe640d94b551da9717e701ef88bb0409c94e002bd42d5",
+    "source_bytes_preserved": false,
+    "int8_scale_bytes_per_physical_row": 4,
+    "rounding": "nearest-even; symmetric [-127,127] per-row scale",
+    "contract": "frozen original IDs; exact encoded representative bytes; quantization/sharing may change float32 rows"
+  },
+  "wall_seconds": 45.10139607009478,
+  "cpu_seconds": 44.842845452,
+  "memory_after": {
+    "peak_rss_bytes": 9560866816,
+    "VmSize_bytes": 2052505600,
+    "VmRSS_bytes": 1955495936,
+    "Rss_bytes": 1955495936,
+    "Pss_bytes": 1945308160,
+    "Shared_Clean_bytes": 10739712,
+    "Shared_Dirty_bytes": 0,
+    "Private_Clean_bytes": 1901379584,
+    "Private_Dirty_bytes": 43376640,
+    "Anonymous_bytes": 43376640
+  },
+  "old_new_source_decoded_and_table_hashes_equal": true
+}
diff --git a/docs/quantized_capacity_evidence_20261031/old-build.py b/docs/quantized_capacity_evidence_20261031/old-build.py
new file mode 100644
index 0000000..1131105
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/old-build.py
@@ -0,0 +1,22 @@
+import json,sys,time
+from pathlib import Path
+root=Path('/llm-align/duyimin/ngram-scale-20261031')
+sys.path.insert(0,str(root/'source-old'))
+import numpy as np
+from tools.benchmark_memory_capacity import environment,memory
+from tools.quantized_memory import pack_quantized
+source=Path('/llm-align/duyimin/meft-cpu-capacity-20261030/training2/trained.f32')
+shape=(1855907,256)
+report=dict(status='running',**environment(),memory_before=memory(),
+            label='pre-streaming main INT8 native export',shape=list(shape))
+rows=np.memmap(source,mode='r',dtype='<f4',shape=shape)
+started,cpu=time.perf_counter(),time.process_time()
+metadata=pack_quantized(rows,root/'old-int8-native','int8',deduplicate=False,max_block_bytes=8192)
+report.update(status='passed',metadata=metadata,wall_seconds=time.perf_counter()-started,
+              cpu_seconds=time.process_time()-cpu,memory_after=memory())
+current=json.loads((root/'results/build-int8-native.json').read_text())['metadata']
+for key in ('source_float32_sha256','decoded_float32_sha256','table_sha256'):
+ if current[key] != metadata[key]: raise AssertionError('old/new export differs: '+key)
+report['old_new_source_decoded_and_table_hashes_equal']=True
+(root/'old-build.json').write_text(json.dumps(report,indent=2)+'\n')
+print(json.dumps({k:report[k] for k in ('status','wall_seconds','cpu_seconds','memory_after','old_new_source_decoded_and_table_hashes_equal')}))
diff --git a/docs/quantized_capacity_evidence_20261031/old-run.log b/docs/quantized_capacity_evidence_20261031/old-run.log
new file mode 100644
index 0000000..e7ba652
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/old-run.log
@@ -0,0 +1 @@
+{"status": "passed", "wall_seconds": 45.10139607009478, "cpu_seconds": 44.842845452, "memory_after": {"peak_rss_bytes": 9560866816, "VmSize_bytes": 2052505600, "VmRSS_bytes": 1955495936, "Rss_bytes": 1955495936, "Pss_bytes": 1945308160, "Shared_Clean_bytes": 10739712, "Shared_Dirty_bytes": 0, "Private_Clean_bytes": 1901379584, "Private_Dirty_bytes": 43376640, "Anonymous_bytes": 43376640}, "old_new_source_decoded_and_table_hashes_equal": true}
diff --git a/docs/quantized_capacity_evidence_20261031/old-run.sh b/docs/quantized_capacity_evidence_20261031/old-run.sh
new file mode 100644
index 0000000..80164a0
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/old-run.sh
@@ -0,0 +1,8 @@
+#!/bin/bash
+set -eu
+ROOT=/llm-align/duyimin/ngram-scale-20261031
+export CUDA_VISIBLE_DEVICES=""
+export OMP_NUM_THREADS=1 OPENBLAS_NUM_THREADS=1 MKL_NUM_THREADS=1
+cd "$ROOT/source-old"
+test "$(cat "$ROOT/status")" = completed
+nice -n 19 /llm-align/duyimin/miniconda3/envs/gemma4/bin/python "$ROOT/old-build.py"
diff --git a/docs/quantized_capacity_evidence_20261031/report.json.gz b/docs/quantized_capacity_evidence_20261031/report.json.gz
new file mode 100644
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diff --git a/docs/quantized_capacity_evidence_20261031/run.log b/docs/quantized_capacity_evidence_20261031/run.log
new file mode 100644
index 0000000..e3b2007
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/run.log
@@ -0,0 +1,62 @@
+{"phase": "verified", "variant": "fp32-raw"}
+{"phase": "verified", "variant": "fp32-native"}
+{"phase": "verified", "variant": "fp16-raw"}
+{"phase": "verified", "variant": "fp16-native"}
+{"phase": "verified", "variant": "int8-raw"}
+{"phase": "verified", "variant": "int8-native"}
+{"phase": "verified", "variant": "int8-native-rows-1"}
+{"phase": "verified", "variant": "int8-native-rows-4"}
+{"phase": "query-passed", "variant": "int8-native-rows-1-uniform-id-stress-0"}
+{"phase": "query-passed", "variant": "int8-native-rows-1-heldout-lexical-0"}
+{"phase": "query-passed", "variant": "fp16-raw-heldout-lexical-0"}
+{"phase": "query-passed", "variant": "int8-raw-uniform-id-stress-0"}
+{"phase": "query-passed", "variant": "fp16-raw-uniform-id-stress-0"}
+{"phase": "query-passed", "variant": "fp16-native-uniform-id-stress-0"}
+{"phase": "query-passed", "variant": "fp32-direct-heldout-lexical-0"}
+{"phase": "query-passed", "variant": "fp16-native-heldout-lexical-0"}
+{"phase": "query-passed", "variant": "int8-native-heldout-lexical-0"}
+{"phase": "query-passed", "variant": "int8-native-rows-4-uniform-id-stress-0"}
+{"phase": "query-passed", "variant": "fp32-raw-uniform-id-stress-0"}
+{"phase": "query-passed", "variant": "int8-native-uniform-id-stress-0"}
+{"phase": "query-passed", "variant": "fp32-native-heldout-lexical-0"}
+{"phase": "query-passed", "variant": "int8-native-rows-4-heldout-lexical-0"}
+{"phase": "query-passed", "variant": "fp32-direct-uniform-id-stress-0"}
+{"phase": "query-passed", "variant": "int8-raw-heldout-lexical-0"}
+{"phase": "query-passed", "variant": "fp32-raw-heldout-lexical-0"}
+{"phase": "query-passed", "variant": "fp32-native-uniform-id-stress-0"}
+{"phase": "query-passed", "variant": "int8-raw-heldout-lexical-1"}
+{"phase": "query-passed", "variant": "int8-native-rows-1-heldout-lexical-1"}
+{"phase": "query-passed", "variant": "int8-native-rows-1-uniform-id-stress-1"}
+{"phase": "query-passed", "variant": "fp32-native-heldout-lexical-1"}
+{"phase": "query-passed", "variant": "fp16-native-heldout-lexical-1"}
+{"phase": "query-passed", "variant": "fp32-native-uniform-id-stress-1"}
+{"phase": "query-passed", "variant": "int8-native-rows-4-uniform-id-stress-1"}
+{"phase": "query-passed", "variant": "fp32-raw-heldout-lexical-1"}
+{"phase": "query-passed", "variant": "fp32-direct-heldout-lexical-1"}
+{"phase": "query-passed", "variant": "int8-native-rows-4-heldout-lexical-1"}
+{"phase": "query-passed", "variant": "fp32-direct-uniform-id-stress-1"}
+{"phase": "query-passed", "variant": "int8-native-uniform-id-stress-1"}
+{"phase": "query-passed", "variant": "int8-native-heldout-lexical-1"}
+{"phase": "query-passed", "variant": "fp16-raw-uniform-id-stress-1"}
+{"phase": "query-passed", "variant": "fp16-native-uniform-id-stress-1"}
+{"phase": "query-passed", "variant": "fp16-raw-heldout-lexical-1"}
+{"phase": "query-passed", "variant": "int8-raw-uniform-id-stress-1"}
+{"phase": "query-passed", "variant": "fp32-raw-uniform-id-stress-1"}
+{"phase": "query-passed", "variant": "fp32-direct-uniform-id-stress-2"}
+{"phase": "query-passed", "variant": "fp16-raw-uniform-id-stress-2"}
+{"phase": "query-passed", "variant": "int8-raw-uniform-id-stress-2"}
+{"phase": "query-passed", "variant": "int8-native-rows-4-heldout-lexical-2"}
+{"phase": "query-passed", "variant": "int8-native-uniform-id-stress-2"}
+{"phase": "query-passed", "variant": "int8-raw-heldout-lexical-2"}
+{"phase": "query-passed", "variant": "fp16-native-uniform-id-stress-2"}
+{"phase": "query-passed", "variant": "int8-native-heldout-lexical-2"}
+{"phase": "query-passed", "variant": "fp32-raw-uniform-id-stress-2"}
+{"phase": "query-passed", "variant": "int8-native-rows-1-heldout-lexical-2"}
+{"phase": "query-passed", "variant": "fp32-raw-heldout-lexical-2"}
+{"phase": "query-passed", "variant": "fp16-raw-heldout-lexical-2"}
+{"phase": "query-passed", "variant": "int8-native-rows-4-uniform-id-stress-2"}
+{"phase": "query-passed", "variant": "fp16-native-heldout-lexical-2"}
+{"phase": "query-passed", "variant": "fp32-native-heldout-lexical-2"}
+{"phase": "query-passed", "variant": "fp32-native-uniform-id-stress-2"}
+{"phase": "query-passed", "variant": "fp32-direct-heldout-lexical-2"}
+{"phase": "query-passed", "variant": "int8-native-rows-1-uniform-id-stress-2"}
diff --git a/docs/quantized_capacity_evidence_20261031/run.sh b/docs/quantized_capacity_evidence_20261031/run.sh
new file mode 100644
index 0000000..7d5c7c9
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/run.sh
@@ -0,0 +1,17 @@
+#!/bin/bash
+set -eu
+ROOT=/llm-align/duyimin/ngram-scale-20261031
+PY=/llm-align/duyimin/miniconda3/envs/gemma4/bin/python
+export CUDA_VISIBLE_DEVICES=""
+export OMP_NUM_THREADS=1 OPENBLAS_NUM_THREADS=1 MKL_NUM_THREADS=1
+cd "$ROOT/source"
+echo running > "$ROOT/status"
+trap 'echo failed > "$ROOT/status"' ERR
+nice -n 19 "$PY" -m tools.benchmark_quantized_capacity \
+  --training-dir /llm-align/duyimin/meft-cpu-capacity-20261030/training2 \
+  --query-manifest /llm-align/duyimin/meft-cpu-capacity-20261030/capacity/queries-ordinary.json \
+  --output-dir "$ROOT/results" --native-library "$ROOT/source/build/libmeft_rows.so" \
+  --chunk-rows 4096 --max-block-bytes 8192 --cache-bytes 4194304 \
+  --repeat 20 --process-repeats 3 --seed 42 --scale-rows 100000 500000 \
+  --int8-extra-block-rows 1 4
+echo completed > "$ROOT/status"
diff --git a/docs/quantized_capacity_evidence_20261031/scale-performance.png b/docs/quantized_capacity_evidence_20261031/scale-performance.png
new file mode 100644
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diff --git a/docs/quantized_capacity_evidence_20261031/setup.sh b/docs/quantized_capacity_evidence_20261031/setup.sh
new file mode 100644
index 0000000..b328abf
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/setup.sh
@@ -0,0 +1,38 @@
+#!/bin/bash
+set -eu
+ROOT=/llm-align/duyimin/ngram-scale-20261031
+PY=/llm-align/duyimin/miniconda3/envs/gemma4/bin/python
+export CUDA_VISIBLE_DEVICES=""
+export OMP_NUM_THREADS=1 OPENBLAS_NUM_THREADS=1 MKL_NUM_THREADS=1
+test -x "$PY"
+cd "$ROOT"
+git clone source.bundle source > clone.log 2>&1
+cd source
+test "$(git rev-parse --short=7 HEAD)" = 20d111c
+mkdir build
+cc -std=c11 -O2 -fPIC -shared native/meft_rows.c -lz -o build/libmeft_rows.so > "$ROOT/build.log" 2>&1
+cc --version > "$ROOT/compiler.txt"
+nice -n 19 "$PY" -m unittest tests.test_quantized_capacity tests.test_quantized_memory > "$ROOT/tests.log" 2>&1
+cat > "$ROOT/run.sh" <<'RUN'
+#!/bin/bash
+set -eu
+ROOT=/llm-align/duyimin/ngram-scale-20261031
+PY=/llm-align/duyimin/miniconda3/envs/gemma4/bin/python
+export CUDA_VISIBLE_DEVICES=""
+export OMP_NUM_THREADS=1 OPENBLAS_NUM_THREADS=1 MKL_NUM_THREADS=1
+cd "$ROOT/source"
+echo running > "$ROOT/status"
+trap 'echo failed > "$ROOT/status"' ERR
+nice -n 19 "$PY" -m tools.benchmark_quantized_capacity \
+  --training-dir /llm-align/duyimin/meft-cpu-capacity-20261030/training2 \
+  --query-manifest /llm-align/duyimin/meft-cpu-capacity-20261030/capacity/queries-ordinary.json \
+  --output-dir "$ROOT/results" --native-library "$ROOT/source/build/libmeft_rows.so" \
+  --chunk-rows 4096 --max-block-bytes 8192 --cache-bytes 4194304 \
+  --repeat 20 --process-repeats 3 --seed 42 --scale-rows 100000 500000 \
+  --int8-extra-block-rows 1 4
+echo completed > "$ROOT/status"
+RUN
+nohup bash "$ROOT/run.sh" > "$ROOT/run.log" 2>&1 < /dev/null &
+echo "$!" > "$ROOT/run.pid"
+cat "$ROOT/tests.log"
+cat "$ROOT/run.pid"
diff --git a/docs/quantized_capacity_evidence_20261031/summary.json b/docs/quantized_capacity_evidence_20261031/summary.json
new file mode 100644
index 0000000..f10f247
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/summary.json
@@ -0,0 +1,6430 @@
+{
+  "status": "passed",
+  "source_commit": "20d111c0830239b7b19ba787479a00fdffb90b07",
+  "command": "/llm-align/duyimin/miniconda3/envs/gemma4/bin/python -m tools.benchmark_quantized_capacity --training-dir /llm-align/duyimin/meft-cpu-capacity-20261030/training2 --query-manifest /llm-align/duyimin/meft-cpu-capacity-20261030/capacity/queries-ordinary.json --output-dir /llm-align/duyimin/ngram-scale-20261031/results --native-library /llm-align/duyimin/ngram-scale-20261031/source/build/libmeft_rows.so --chunk-rows 4096 --max-block-bytes 8192 --cache-bytes 4194304 --repeat 20 --process-repeats 3 --seed 42 --scale-rows 100000 500000 --int8-extra-block-rows 1 4",
+  "shape": [
+    1855907,
+    256
+  ],
+  "source_bytes": 1900448768,
+  "source_sha256": "0e5d4be0b156c5e9f0d745292876e48f78772c599d97902619123512955d82fc",
+  "python": "3.11.15 (main, Mar 11 2026, 17:20:07) [GCC 14.3.0]",
+  "numpy": "2.2.6",
+  "os": "Linux-5.4.0-42-generic-x86_64-with-glibc2.35",
+  "cpu": "AMD EPYC 7742 64-Core Processor",
+  "settings": {
+    "chunk_rows": 4096,
+    "max_block_bytes": 8192,
+    "cache_bytes": 4194304,
+    "repeat": 20,
+    "process_repeats": 3,
+    "seed": 42,
+    "scale_rows": [
+      100000,
+      500000
+    ],
+    "int8_extra_block_rows": [
+      1,
+      4
+    ]
+  },
+  "limitations": [
+    "Shared CPU and filesystem; timing rounds randomize variant/trace order, no isolation guarantee.",
+    "Filesystem warmed by build/verification; first trace means fresh process/empty application cache, not disk-cold.",
+    "Uniform IDs are synthetic accesses on genuine vectors; original held-out lexical trace is reused.",
+    "FP16/INT8 are lossy relative to FP32; byte-exact claims apply to their encoded rows only.",
+    "No downstream task quality, GPU, cgroup memory cap, physical disk I/O or monetary cost measured.",
+    "Smaller prefixes reuse original trained rows without retraining and are storage scaling controls.",
+    "Chunking bounds codec working buffers, not native O(block count) descriptors or arbitrary optional planner indexes.",
+    "Complete bundle is table + codec metadata + common key registry; training source-ID provenance is separate."
+  ],
+  "native_library_sha256": "49aa8e7e82c83e3ec0b103af62eeb3638d98a18a780a35bb5c80e435fc791c51",
+  "keys_bytes": 21429556,
+  "keys_sha256": "addcb6e8300c27a5d8d43028d334f9d9e6f62dcf39f7590c0952a060ede8acc8",
+  "training_report_sha256": "2d6f5cbe67e7922ff0e28055be0cf1cf045c5f7f8cddd89b69b594e5408c0245",
+  "training": {
+    "status": "passed",
+    "category": "public-text finite CPU SGNS storage reference",
+    "source_commit": "3104f50470067049f5a57a574270d0b9d17c4fbf",
+    "command": "/llm-align/duyimin/meft-cuda-20261030/compat/bin/python /llm-align/duyimin/meft-cpu-capacity-20261030/source/tools/train_capacity_memory.py --corpus-zip /llm-align/duyimin/meft-cpu-capacity-20261030/enwik8.zip --output-dir /llm-align/duyimin/meft-cpu-capacity-20261030/training2 --order 12 --dim 256 --min-count 2 --epochs 3 --random-pairs 262144 --batch-size 128 --threads 4 --seed 42 --exclude-untrained",
+    "settings": {
+      "corpus_zip": "/llm-align/duyimin/meft-cpu-capacity-20261030/enwik8.zip",
+      "output_dir": "/llm-align/duyimin/meft-cpu-capacity-20261030/training2",
+      "order": 12,
+      "dim": 256,
+      "min_count": 2,
+      "epochs": 3,
+      "random_pairs": 262144,
+      "batch_size": 128,
+      "negatives": 5,
+      "lr": 0.02,
+      "threads": 4,
+      "seed": 42,
+      "exclude_untrained": true
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+    "torch": "2.11.0+cu130",
+    "numpy": "2.2.6",
+    "os": "Linux-5.4.0-42-generic-x86_64-with-glibc2.35",
+    "cuda_visible_devices": "",
+    "corpus_source": "https://mattmahoney.net/dc/enwik8.zip",
+    "corpus_license_note": "Wikipedia-derived benchmark XML; publish aggregates/hashes only, no text or weights.",
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+            "min": 686444544.0,
+            "max": 686723072.0,
+            "values": [
+              686571520,
+              686723072,
+              686444544
+            ]
+          },
+          "VmRSS_bytes": {
+            "median": 686571520.0,
+            "min": 686444544.0,
+            "max": 686723072.0,
+            "values": [
+              686571520,
+              686723072,
+              686444544
+            ]
+          }
+        }
+      }
+    }
+  },
+  "failures": []
+}
diff --git a/docs/quantized_capacity_evidence_20261031/supplement-run.log b/docs/quantized_capacity_evidence_20261031/supplement-run.log
new file mode 100644
index 0000000..e69de29
diff --git a/docs/quantized_capacity_evidence_20261031/supplement-run.sh b/docs/quantized_capacity_evidence_20261031/supplement-run.sh
new file mode 100644
index 0000000..c166be8
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/supplement-run.sh
@@ -0,0 +1,19 @@
+#!/bin/bash
+set -eu
+ROOT=/llm-align/duyimin/ngram-scale-20261031
+PY=/llm-align/duyimin/miniconda3/envs/gemma4/bin/python
+export CUDA_VISIBLE_DEVICES=""
+export OMP_NUM_THREADS=1 OPENBLAS_NUM_THREADS=1 MKL_NUM_THREADS=1
+export TMPDIR="$ROOT/tmp"
+echo running > "$ROOT/supplement-status"
+trap 'echo failed > "$ROOT/supplement-status"' ERR
+bash "$ROOT/old-run.sh" > "$ROOT/old-run.log" 2>&1
+cd "$ROOT/source-auto"
+nice -n 19 "$PY" "$ROOT/auto-build.py" > "$ROOT/auto-run.log" 2>&1
+nice -n 19 "$PY" -m tools.benchmark_quantized_capacity --phase verify \
+  --source /llm-align/duyimin/meft-cpu-capacity-20261030/training2/trained.f32 \
+  --bundle "$ROOT/auto-int8" --dim 256 --encoding int8 --backend raw \
+  --worker-report "$ROOT/auto-verify.json" \
+  --native-library "$ROOT/source/build/libmeft_rows.so" --chunk-rows 4096 \
+  --query-manifest "$ROOT/results/queries.json" > "$ROOT/auto-verify.log" 2>&1
+echo completed > "$ROOT/supplement-status"
diff --git a/docs/quantized_capacity_evidence_20261031/supplement-setup.sh b/docs/quantized_capacity_evidence_20261031/supplement-setup.sh
new file mode 100644
index 0000000..1c4e640
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/supplement-setup.sh
@@ -0,0 +1,61 @@
+#!/bin/bash
+set -eu
+ROOT=/llm-align/duyimin/ngram-scale-20261031
+PY=/llm-align/duyimin/miniconda3/envs/gemma4/bin/python
+export CUDA_VISIBLE_DEVICES=""
+export OMP_NUM_THREADS=1 OPENBLAS_NUM_THREADS=1 MKL_NUM_THREADS=1
+export TMPDIR="$ROOT/tmp"
+test "$(cat "$ROOT/status")" = completed
+cd "$ROOT"
+git clone auto.bundle source-auto > auto-clone.log 2>&1
+cd source-auto
+test "$(git rev-parse HEAD)" = 9485969066ee4be466673cde07823330da1a7658
+nice -n 19 "$PY" -m unittest tests.test_quantized_memory tests.test_quantized_capacity > "$ROOT/auto-tests.log" 2>&1
+cat > "$ROOT/auto-build.py" <<'PY'
+import json,sys,time
+from pathlib import Path
+root=Path('/llm-align/duyimin/ngram-scale-20261031')
+sys.path.insert(0,str(root/'source-auto'))
+from tools.benchmark_quantized_capacity import software_environment, memory
+from tools.quantized_memory import pack_quantized_file
+source=Path('/llm-align/duyimin/meft-cpu-capacity-20261030/training2/trained.f32')
+report=dict(status='running',**software_environment(),memory_before=memory(),
+            label='auto INT8 native/raw bundle selection',shape=[1855907,256])
+started,cpu=time.perf_counter(),time.process_time()
+metadata=pack_quantized_file(source,root/'auto-int8',256,'int8',native='auto',chunk_rows=4096,max_block_bytes=8192)
+report.update(status='passed',metadata=metadata,wall_seconds=time.perf_counter()-started,
+              cpu_seconds=time.process_time()-cpu,memory_after=memory(),
+              bundle_bytes=sum(p.stat().st_size for p in (root/'auto-int8').iterdir()))
+current=json.loads((root/'results/build-int8-raw.json').read_text())['metadata']
+for key in ('source_float32_sha256','decoded_float32_sha256','table_sha256'):
+ if current[key] != metadata[key]: raise AssertionError('auto/raw differs: '+key)
+if metadata['backend'] != 'raw_mmap': raise AssertionError('expected measured INT8 expansion to select raw')
+report['auto_matches_verified_raw_source_decoded_and_table_hashes']=True
+(root/'auto-build.json').write_text(json.dumps(report,indent=2)+'\n')
+print(json.dumps({k:report[k] for k in ('status','wall_seconds','cpu_seconds','memory_after','bundle_bytes','auto_matches_verified_raw_source_decoded_and_table_hashes')}))
+PY
+cat > "$ROOT/supplement-run.sh" <<'RUN'
+#!/bin/bash
+set -eu
+ROOT=/llm-align/duyimin/ngram-scale-20261031
+PY=/llm-align/duyimin/miniconda3/envs/gemma4/bin/python
+export CUDA_VISIBLE_DEVICES=""
+export OMP_NUM_THREADS=1 OPENBLAS_NUM_THREADS=1 MKL_NUM_THREADS=1
+export TMPDIR="$ROOT/tmp"
+echo running > "$ROOT/supplement-status"
+trap 'echo failed > "$ROOT/supplement-status"' ERR
+bash "$ROOT/old-run.sh" > "$ROOT/old-run.log" 2>&1
+cd "$ROOT/source-auto"
+nice -n 19 "$PY" "$ROOT/auto-build.py" > "$ROOT/auto-run.log" 2>&1
+nice -n 19 "$PY" -m tools.benchmark_quantized_capacity --phase verify \
+  --source /llm-align/duyimin/meft-cpu-capacity-20261030/training2/trained.f32 \
+  --bundle "$ROOT/auto-int8" --dim 256 --encoding int8 --backend raw \
+  --worker-report "$ROOT/auto-verify.json" \
+  --native-library "$ROOT/source/build/libmeft_rows.so" --chunk-rows 4096 \
+  --query-manifest "$ROOT/results/queries.json" > "$ROOT/auto-verify.log" 2>&1
+echo completed > "$ROOT/supplement-status"
+RUN
+nohup bash "$ROOT/supplement-run.sh" > "$ROOT/supplement-run.log" 2>&1 < /dev/null &
+echo "$!" > "$ROOT/supplement.pid"
+cat "$ROOT/auto-tests.log"
+cat "$ROOT/supplement.pid"
diff --git a/docs/quantized_capacity_evidence_20261031/tests.log b/docs/quantized_capacity_evidence_20261031/tests.log
new file mode 100644
index 0000000..b7ea89c
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/tests.log
@@ -0,0 +1,5 @@
+..........
+----------------------------------------------------------------------
+Ran 10 tests in 2.115s
+
+OK
diff --git a/docs/quantized_capacity_evidence_20261031/tests.txt b/docs/quantized_capacity_evidence_20261031/tests.txt
new file mode 100644
index 0000000..f88bac0
--- /dev/null
+++ b/docs/quantized_capacity_evidence_20261031/tests.txt
@@ -0,0 +1,12 @@
+...................ss.ss......../llm-align/duyimin/ngram-scale-20261031/checks-source/src/ftindex.cc: In function ‘FTIndex* ftindex_map_from_buffer(void*, size_t*)’:
+/llm-align/duyimin/ngram-scale-20261031/checks-source/mylib/include/pub/pub_malloc.h:16:82: warning: ISO C++ forbids converting a string constant to ‘char*’ [-Wwrite-strings]
+   16 | #define pub_calloc(num, size)                   pub_calloc_detail((num), (size), __FILE__, __FUNCTION__, __LINE__)
+      |                                                                                  ^~~~~~~~
+/llm-align/duyimin/ngram-scale-20261031/checks-source/src/ftindex.cc:461:31: note: in expansion of macro ‘pub_calloc’
+  461 |         if (!(fti = (FTIndex*)pub_calloc(1, sizeof(*fti)))) return NULL;
+      |                               ^~~~~~~~~~
+........................................................................................sssssssssssss.......
+----------------------------------------------------------------------
+Ran 140 tests in 66.453s
+
+OK (skipped=17)
diff --git a/tools/analyze_quantized_capacity.py b/tools/analyze_quantized_capacity.py
index b9c7229..c8917fe 100644
--- a/tools/analyze_quantized_capacity.py
+++ b/tools/analyze_quantized_capacity.py
@@ -103,14 +103,22 @@ def plot(summary, directory):
     query_names = ["fp32-direct"] + names
     for case, marker in (("heldout-lexical", "o"), ("uniform-id-stress", "s")):
         values = [summary["queries"][n][case]["first_trace"]["wall_p50_ms"]["median"] for n in query_names]
-        axes[1].plot(values, list(range(len(query_names))), marker=marker, label=case)
+        low = [summary["queries"][n][case]["first_trace"]["wall_p50_ms"]["min"] for n in query_names]
+        high = [summary["queries"][n][case]["first_trace"]["wall_p50_ms"]["max"] for n in query_names]
+        axes[1].errorbar(values, list(range(len(query_names))),
+                         xerr=[np.asarray(values) - low, np.asarray(high) - values],
+                         fmt=marker, capsize=2, label=case)
     axes[1].set_yticks(range(len(query_names)), [n.replace("fp32-direct", "FP32 direct mmap") for n in query_names])
     axes[1].set(xscale="log", xlabel="Fresh-process first-trace batch p50 (ms)", title="512-row CPU gather → FP32")
     axes[1].legend(fontsize=8)
     scale_names = ["int8-native-prefix-100000", "int8-native-prefix-500000", "int8-native"]
     scale_names = [n for n in scale_names if n in summary["builds"]]
-    axes[2].plot([summary["builds"][n]["rows"] / 1e6 for n in scale_names],
-                 [summary["builds"][n]["peak_rss_bytes"] / 2**20 for n in scale_names], "o-", color="#f28e2b")
+    scale_x = [summary["builds"][n]["rows"] / 1e6 for n in scale_names]
+    scale_y = [summary["builds"][n]["peak_rss_bytes"] / 2**20 for n in scale_names]
+    axes[2].plot(scale_x, scale_y, "o-", color="#f28e2b")
+    axes[2].set_ylim(0, max(scale_y) * 1.3)
+    for x, y in zip(scale_x, scale_y):
+        axes[2].annotate(f"{y:.1f}", (x, y), xytext=(0, 7), textcoords="offset points", ha="center", fontsize=8)
     axes[2].set(xlabel="Original trained rows (millions)", ylabel="Fresh builder peak RSS (MiB)",
                 title="INT8 streaming export, ≤8 KiB blocks")
     for ax in axes[:2]: