agents benchmark
BFCL-V4
Berkeley Function Calling Leaderboard V4 (BFCL-V4) evaluates LLMs on their ability to accurately call functions and APIs, including simple, multiple, parallel, and nested function calls across diverse programming scenarios.
Updated Aug 11, 2026
Models13
Model coverage13
MetricScore
EvidenceB
BFCL-V4 Ranking
Higher score ranks better on this benchmark.
| 01 | AC | 75.0% | 100.0% | 13 | C | |
| 02 | AC | 72.9% | 91.7% | 13 | C | |
| 03 | AC | 72.9% | 83.3% | 13 | C | |
| 04 | AC | 72.2% | 75.0% | 13 | C | |
| 05 | AC | 68.5% | 66.7% | 13 | C | |
| 06 | AC | 67.3% | 58.3% | 13 | C | |
| 07 | AC | 66.1% | 50.0% | 13 | C | |
| 08 | AM Nova 2 ProAmazon | 61.6% | 41.7% | 13 | C | |
| 09 | AMNova 2 LiteAmazon | 60.3% | 33.3% | 13 | C | |
| 10 | AMNova 2 OmniAmazon | 58.3% | 25.0% | 13 | C | |
| 11 | AC | 50.3% | 16.7% | 13 | C | |
| 12 | AC | 43.6% | 8.3% | 13 | C | |
| 13 | AC | 25.3% | 0.0% | 13 | C |
BFCL-V4 Score Distribution
A closer view of the leading scores on this benchmark.
BFCL-V4 Highlights
The leading models and scores on this benchmark.
What is BFCL-V4?
What BFCL-V4 measures and how its scores work.
Berkeley Function Calling Leaderboard V4 (BFCL-V4) evaluates LLMs on their ability to accurately call functions and APIs, including simple, multiple, parallel, and nested function calls across diverse programming scenarios.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- BFCL-V4
- Modality
- text
- Primary category
- agents
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- bfcl-v4|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about BFCL-V4.
Which model scores highest on BFCL-V4?
Qwen3.7 Max is currently ranked first with 75.0%.
What does BFCL-V4 measure?
Berkeley Function Calling Leaderboard V4 (BFCL-V4) evaluates LLMs on their ability to accurately call functions and APIs, including simple, multiple, parallel, and nested function calls across diverse programming scenarios.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
13 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.