AI benchmarks and leaderboards are different things
Learn the difference between a benchmark, an evaluation run and a leaderboard, and use each to answer the right question.
LLM Stats
BFCL v2
Berkeley Function Calling Leaderboard (BFCL) v2 is a comprehensive benchmark for evaluating large language models' function calling capabilities. It features 2,251 question-function-answer pairs with enterprise and OSS-contributed functions, addressing data contamination and bias through live, user-contributed scenarios. The benchmark evaluates AST accuracy, executable accuracy, irrelevance detection, and relevance detection across multiple programming languages (Python, Java, JavaScript) and includes complex real-world function calling scenarios with multi-lingual prompts.
Evaluation context and evidence
- Source
- LLM Stats
- Publisher
- Not recorded
- Benchmark release
- Not recorded
- Collected
- 2026-08-17
- Modality
- text
These are source-reported observations, not independent reruns by this site. Check the task version, evaluation protocol, unit and reporting date before comparing models. Results from different setups are not a universal ranking.
Original sources
Reported results 5
Shown in source observation order, not ranked. Dates retain the precision provided by the source.
| Model | Value | Unit | Protocol | Reported date and basis | Source |
|---|---|---|---|---|---|
| Llama 3.3 70B Instruct | 0.773 | Not recorded | Not recorded | 2024-12-06 · model_announcement | LLM Stats |
| Llama 3.1 Nemotron Ultra 253B v1 | 0.741 | Not recorded | Not recorded | 2025-04-07 · model_announcement | LLM Stats |
| Llama-3.3 Nemotron Super 49B v1 | 0.737 | Not recorded | Not recorded | 2025-03-18 · model_announcement | LLM Stats |
| Llama 3.2 3B Instruct | 0.67 | Not recorded | Not recorded | 2024-09-25 · model_announcement | LLM Stats |
| Llama 3.1 Nemotron Nano 8B V1 | 0.636 | Not recorded | Not recorded | 2025-03-18 · model_announcement | LLM Stats |