| --- |
| license: cc-by-4.0 |
| language: |
| - en |
| pretty_name: >- |
| quant_eval Throughput telemetry |
| size_categories: |
| - 10K<n<100K |
| 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_throughput_telemetry.jsonl |
| --- |
| |
| # quant_eval — Throughput telemetry |
| |
| **One record per generation call across all published runs, pooled into a single union schema. Carries token counts, timing, and the token-count source per call.** |
| |
| 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.22009987](https://doi.org/10.5281/zenodo.22009987) — concept DOI, always resolves to the latest version. |
| **This exact deposit:** [10.5281/zenodo.22009988](https://doi.org/10.5281/zenodo.22009988) — 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_throughput_telemetry.jsonl` | 27,370 | 31 | |
|
|
| Supporting files: `data_dictionary.json`, `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_throughput_telemetry.jsonl` |
| |
| ``` |
| attempt call call_id |
| case_id cumulative_generated_tokens cumulative_generation_seconds |
| cumulative_prompt_tokens cumulative_tokens_per_second evaluation_contract_id |
| event family finish_reason |
| fixtures_sha256 generated_tokens generation_seconds |
| max_new_tokens max_new_tokens_recorded model_id |
| prompt_tokens quant_type run_elapsed_seconds |
| run_id runner schema_version |
| scored stage timestamp_unix |
| token_count_source token_limit_reached tokens_per_second |
| version_tag |
| ``` |
| |
| `data_dictionary.json`, included here, documents every field: applicability, data type, evidence role, gate membership, the meaning of an empty value, and observed population counts. **An empty cell is not automatically a missing measurement** — several fields are conditional on task family, and their empty-value meaning is recorded explicitly. |
| |
| ## 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. |
| - Aggregates published elsewhere in this corpus — the paired degradation statistics (D5) and family pass rates (D6) datasets — are recomputable from the per-case results dataset (D1) using the gate definitions in `data_dictionary.json`, included here. |
| |
| ## 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. |
| - **Calibration runs are not published.** Runs that informed a published run are disclosed by identifier in `calibration_lineage.csv`, published in the run provenance dataset (D4), so the record is complete without releasing provisional numbers. |
| |
| ## Citation |
| |
| ```bibtex |
| @dataset{pbh_quant_eval_d2, |
| author = {Hill, Patrick}, |
| title = {quant_eval Throughput telemetry}, |
| publisher = {PBH Applied Systems, LLC}, |
| year = {2026}, |
| doi = {10.5281/zenodo.22009987}, |
| note = {Version DOI: 10.5281/zenodo.22009988}, |
| 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. |
| |
