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license: cc-by-4.0
language:
- en
pretty_name: >-
quant_eval Run provenance
size_categories:
- n<1K
tags:
- quantization
- large-language-models
- gguf
- agent-evaluation
- tool-calling
- behavioral-evaluation
- mcnemar
- llama-cpp
- model-evaluation
- reproducibility
annotations_creators:
- machine-generated
source_datasets:
- original
configs:
- config_name: default
data_files:
- split: train
path: quant_eval_run_provenance.csv
---
# 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](https://doi.org/10.5281/zenodo.22010462) — concept DOI, always resolves to the latest version.
**This exact deposit:** [10.5281/zenodo.22010463](https://doi.org/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
```bibtex
@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.
---
Produced by build_datasets.py 2.4.0 from quant_eval publication bundles. Built 2026-08-19.
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