reasoning benchmark
Gorilla Benchmark API Bench is based on APIBench, a dataset of over 11,000 instruction-API pairs from HuggingFace, TorchHub, and TensorHub APIs.
Updated Sep 5, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelME | Score35.30% | Percentile100.00% | Participants3 | EvidenceC | Evaluated |
| Rank02 | ModelME | Score29.70% | Percentile50.00% | Participants3 | EvidenceC | Evaluated |
| Rank03 | ModelME | Score8.20% | Percentile0.00% | Participants3 | EvidenceC | Evaluated |
The leading models and scores on this benchmark.
A closer view of the leading scores on this benchmark.
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
What Gorilla Benchmark API Bench measures and how its scores work.
APIBench is a dataset of over 11,000 instruction-API pairs from HuggingFace, TorchHub, and TensorHub APIs.
It evaluates language models' ability to generate accurate API calls using the Score metric, reported as a ratio.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
LLM Stats. Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about Gorilla Benchmark API Bench.
Llama 3.1 405B Instruct is currently ranked first with 35.30%.
The current leaders are Llama 3.1 405B Instruct (35.30%), Llama 3.1 70B Instruct (29.70%), and Llama 3.1 8B Instruct (8.20%).
No matched official input price is currently available.
The fastest matched records are Llama 3.1 8B Instruct (2,047.00 tok/s via Cerebras), Llama 3.1 70B Instruct (1,204.00 tok/s via Cerebras), and Llama 3.1 405B Instruct (42.00 tok/s via Google).
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.
It evaluates language models' ability to generate accurate API calls using the Score metric, reported as a ratio.
Yes. Higher values rank better for this benchmark.
3 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.
Ranking basisThis gorilla benchmark api bench AI model leaderboard uses descending score in the benchmark original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
Selection summary
Llama 3.1 405B Instruct currently leads Gorilla Benchmark API Bench with 35.30%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price, and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.