pbhappliedsystems/quant_eval_run_provenance

quant_eval — Run provenance

One row per published run: model identity, contract identifiers, fixture hash, decoding conditions, licence, and the SHA-256 and byte size of both weight artifacts. Accompanied by the calibration lineage that informed each published run.

Part of the quant_eval public corpus: a per-case behavioral evaluation of full-weight and quantized large language models across eight agent-relevant task families, with paired statistical testing.

Cite this dataset: 10.5281/zenodo.22010462 — concept DOI, always resolves to the latest version. This exact deposit: 10.5281/zenodo.22010463 — version DOI, frozen. Cite this one where reported numbers must stay verifiable against the object referenced.

What this file contains

File	Rows	Columns
quant_eval_run_provenance.csv	6	41
calibration_lineage.csv	14	4

Supporting files: source_bundle_checksums.json.

Corpus scope

Run	Model	Baseline	Quantized	Substrate	Licence
Mistral_Nemo_Instruct_2407_20260814_030505	mistralai/Mistral-Nemo-Instruct-2407	gguf_f16	gguf_q4_k_m	local	Apache-2.0
Mistral_Nemo_Instruct_2407_20260815_113254	mistralai/Mistral-Nemo-Instruct-2407	gguf_f16	gguf_q5_k_m	local	Apache-2.0
Mistral_Nemo_Instruct_2407_20260816_084553	mistralai/Mistral-Nemo-Instruct-2407	gguf_f16	gguf_q8_0	local	Apache-2.0
Qwen2.5_14B_Instruct_1M_20260815_220633	Qwen/Qwen2.5-14B-Instruct-1M	modal_f16	modal_q4_k_m	Modal	Apache-2.0
Qwen2.5_32B_Instruct_20260815_081051	Qwen/Qwen2.5-32B-Instruct	modal_f16	modal_q4_k_m	Modal	Apache-2.0
Qwen2.5_7B_Instruct_20260814_234822	Qwen/Qwen2.5-7B-Instruct	gguf_f16	gguf_q4_k_m	local	Apache-2.0

Every run evaluates a full-weight baseline and a quantized variant of the same model against the identical locked fixture set, case for case. Statistical comparison is paired: the two-sided exact McNemar test on per-case outcomes, with Wilson intervals on the rates.

Columns

quant_eval_run_provenance.csv

  run_id                                        model_id                                      canonical_upstream_model_id
  adapter_id                                    adapter_reason                                version_tag
  evaluation_contract_id                        scoring_contract                              prompt_contract
  fixture_construction_contract                 fixtures_sha256                               fixture_version_label
  fixture_split                                 profile                                       run_purpose
  promotion_status                              publication_status                            release_validation_status
  seed                                          fixture_generation_seed                       timestamp
  baseline_quant_type                           quantized_quant_type                          baseline_runner
  quantized_runner                              execution_substrate                           decode_temperature
  decode_seed_status                            decode_context_size                           decode_top_p
  decode_top_k                                  license                                       spdx_license_id
  commercial_use_status                         baseline_artifact_sha256                      baseline_artifact_bytes
  quantized_artifact_sha256                     quantized_artifact_bytes                      upstream_revision
  upstream_revision_status                      rows

calibration_lineage.csv

  published_run_id                              calibration_run_id                            role
  published

Verification

This corpus is derived from sanitized publication bundles produced by the quant_eval harness. It is designed to be checked rather than trusted:

• source_bundle_checksums.json, included here, republishes, verbatim, the SHA-256 digest and byte length of every file in every source bundle. No source file was modified.
• Before this file was written, the builder verified all 72 source-file digests and independently recomputed all 96 family x runner pass rates from the raw per-case rows, matching the harness rollups exactly.
• The fields here are run-level metadata carried through from the source bundles unchanged, not statistics derived from per-case rows. They are traceable through the bundle digests above. Recomputable aggregates live in the paired degradation statistics (D5) and family pass rates (D6) datasets, both derived from the per-case results dataset (D1).

Limits you should know before using this

• Decoding conditions are not uniform across models. Temperature follows each publisher's own model card, so cross-model comparison of absolute pass rates is confounded. Within-run pairing is unaffected, which is what the paired test requires. The conditions are published per row and per run so they can be filtered on.
• Runs on the Modal substrate record seed status unsupported — the deployed method signature accepts no seed — so those runs are not exactly reproducible. Local runs applied a fixed seed.
• Runtime figures are observed harness wall time on the recorded hardware and backends. They are not a controlled throughput benchmark and not a general claim about quantization performance at any precision on any hardware. Direction is published as an explicit label because not every measured pair is a speedup.
• The fuzz family is an adaptive trajectory evaluated from identical starting fixtures. Its paired test compares complete case outcomes, not identical post-divergence prompts.
• upstream_revision is empty for 2 of 6 runs (Qwen2.5_14B_Instruct_1M_20260815_220633, Qwen2.5_7B_Instruct_20260814_234822). Where present, it is the exact upstream repository revision the evaluated weights were converted from. Where empty, upstream_revision_status records why — in this corpus, unavailable_for_pre_provenance_legacy_artifact. This is a documented absence, not a dropped measurement: weight identity for those runs is still established exactly, by the artifact SHA-256 recorded in this file, but not tied to a named upstream commit.
• Calibration runs are not published. Runs that informed a published run are disclosed by identifier in calibration_lineage.csv, included here, so the record is complete without releasing provisional numbers.

Citation

@dataset{pbh_quant_eval_d4,
  author    = {Hill, Patrick},
  title     = {quant_eval Run provenance},
  publisher = {PBH Applied Systems, LLC},
  year      = {2026},
  doi       = {10.5281/zenodo.22010462},
  note      = {Version DOI: 10.5281/zenodo.22010463},
  license   = {CC-BY-4.0}
}

Licence

Creative Commons Attribution 4.0 International (CC BY 4.0). See LICENSE. Commercial use is permitted; attribution is required.

This corpus describes third-party models and redistributes no model weights. Each evaluated model remains under its own licence, recorded per run in the run provenance dataset.

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Produced by build_datasets.py 2.4.0 from quant_eval publication bundles. Built 2026-08-19.