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QuantCall Results
Community-submitted benchmark results for the QuantCall benchmark.
This dataset is currently empty. Run the benchmark on your GPU and submit a PR to populate the leaderboard.
Schema
Each row represents one benchmark run. File: data/results.csv.
| Column | Type | Description |
|---|---|---|
model |
string | Model identifier (HF repo ID or local path) |
quant |
string | Quantization level: fp16, Q8_0, Q5_K_M, Q4_K_M, AWQ, GPTQ |
backend |
string | Inference backend: llama-cpp, transformers, vllm, openai |
svr |
float | Schema-Validity Rate [0, 1] |
tsa |
float | Tool-Selection Accuracy [0, 1] |
ac |
float | Argument Correctness [0, 1] |
abstention |
float | Abstention Accuracy [0, 1] |
fcr |
float | Function-Calling Reliability — 0.25 × (SVR + TSA + AC + Abst) |
delta_fcr |
float | FCR degradation vs fp16 baseline (null if no baseline) |
vram_gb |
float | Peak VRAM usage in GB (null if not measured) |
eta |
float | Efficiency: FCR / peak VRAM (null if vram_gb is null) |
git_commit |
string | QuantCall repo commit SHA used for this run |
config_sha256 |
string | SHA-256 of the run config YAML |
dataset_sha256 |
string | SHA-256 of the evaluation sample |
tiers |
string | Comma-separated tier list: T0, T1, T2, T3, T4, T5, T6 |
sample_size |
int | Number of instances evaluated per tier |
timestamp |
string | ISO-8601 UTC timestamp of the run |
How to Submit
- Run the benchmark on your hardware following docs/RUN_REAL.md.
- Verify your
result.jsoncontains amanifestblock with git SHA and hashes. - Open a PR on GitHub adding your result file under
results/. - CI will validate the manifest and regenerate this dataset and the leaderboard.
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