Berkeley Function Calling Leaderboard (BFCL)
Model emits function calls for single, parallel, multi-turn and agentic scenarios. Scored by AST and execution checks.
Live benchmark. Nova 2 pins results to a 2025 commit, so versions matter.
- Level
- Everyday Most adults, without training
- Scored
- Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
- Answers
- Agent task Many steps in a terminal, browser, desktop, app, game or robot.
Llama 3.1-405B leads with 88.5%
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.
- 88.5
Llama 3.1-405B
- 84.8
Llama 3.1-70B
- 78.3
Hunyuan-A13B-Instruct
- 77.8 GLM-4.5
- 77.3
Llama 3.3 70B Instruct
- 77.2 Reka Flash 3
- 76.8
MiniMax-M2.5
- 76.4 GLM-4.5-Air
- 76.1
Llama 3.1-8B
- 74.4
LongCat-Flash-Thinking
- 74.1
Llama-3.1-Nemotron-Ultra-253B-v1
- 73.7
Llama-3.3-Nemotron-Super-49B-v1
- 73.7 Granite 4.1 30B
- 72.0
Qwen3-Next-80B-A3B
- 72.0
MAI-Thinking-1
- 71.9
Qwen3-235B-A22B-Thinking
- 71.9
Qwen3-VL-235B-A22B
- 71.8
Llama-3.3-Nemotron-Super-49B-v1.5
- 70.8
Qwen3-235B-A22B
- 70.5 GLM-Z1-32B-0414
- 70.4
Qwen3-14B
- 70.3
Phi-4 Mini
- 70.3
Qwen3-32B
- 70.3
Command A Reasoning
- 69.1
Qwen3-30B-A3B
- 68.8
Ring-1T
- 68.7
Qwen3-Coder-480B-A35B
- 68.1
Qwen3-8B
- 67.3
Nemotron 3.5 Bolt E4B
- 66.9 nvidia-nemotron-nano-9b-v2
- 65.9
Qwen3-4B
- 65.2
EXAONE 4.0 32B
- 65.0
ERNIE-4.5-21B-A3B-Thinking
- 64.7 Granite 4.0 H Small
- 64.4
Qwen3-Omni-30B-A3B
- 64.4 LFM2.5-8B-A1B
- 63.9
Solar Pro 2
- 63.8
Cohere Command A
- 63.7
Amazon Nova Premier
- 61.1
Nemotron 3 Nano 4B
- 59.7
Trinity Mini
- 57.9 ChatGLM3-6B
- 57.0 LFM2.5-1.2B-Thinking
- 56.6
Qwen3-1.7B
- 54.8 granite-4.0-1b
- 49.1 LFM2.5-1.2B-Instruct
- 37.0
DeepSeek-R1
- 1
Llama 3.1-405B 88.5%
- 2
Llama 3.1-70B 84.8%
- 3
Hunyuan-A13B-Instruct 78.3%
- 4 GLM-4.5 77.8%
- 5
Llama 3.3 70B Instruct 77.3%
- 6 Reka Flash 3 77.2%
- 7
MiniMax-M2.5 76.8%
- 8 GLM-4.5-Air 76.4%
- 9
Llama 3.1-8B 76.1%
- 10
LongCat-Flash-Thinking 74.4%
- 11
Llama-3.1-Nemotron-Ultra-253B-v1 74.1%
- 12
Llama-3.3-Nemotron-Super-49B-v1 73.7%
- 13 Granite 4.1 30B 73.7%
- 14
Qwen3-Next-80B-A3B 72%
- 15
MAI-Thinking-1 72%
- 16
Qwen3-235B-A22B-Thinking Jul 2025 71.9%
- 17
Qwen3-VL-235B-A22B 71.9%
- 18
Llama-3.3-Nemotron-Super-49B-v1.5 71.8%
- 19
Qwen3-235B-A22B 70.8%
- 20 GLM-Z1-32B-0414 70.5%
- 21
Qwen3-14B 70.4%
- 22
Phi-4 Mini 70.3%
- 23
Qwen3-32B 70.3%
- 24
Command A Reasoning 70.3%
- 25
Qwen3-30B-A3B 69.1%
- 26
Ring-1T 68.8%
- 27
Qwen3-Coder-480B-A35B 68.7%
- 28
Qwen3-8B 68.1%
- 29
Nemotron 3.5 Bolt E4B 67.3%
- 30 nvidia-nemotron-nano-9b-v2 66.9%
- 31
Qwen3-4B 65.9%
- 32
EXAONE 4.0 32B 65.2%
- 33
ERNIE-4.5-21B-A3B-Thinking 65%
- 34 Granite 4.0 H Small 64.7%
- 35
Qwen3-Omni-30B-A3B 64.4%
- 36 LFM2.5-8B-A1B 64.4%
- 37
Solar Pro 2 63.9%
- 38
Cohere Command A 63.8%
- 39
Amazon Nova Premier 63.7%
- 40
Nemotron 3 Nano 4B 61.1%
- 41
Trinity Mini 59.7%
- 42 ChatGLM3-6B 57.9%
- 43 LFM2.5-1.2B-Thinking 57%
- 44
Qwen3-1.7B 56.6%
- 45 granite-4.0-1b 54.8%
- 46 LFM2.5-1.2B-Instruct 49.1%
- 47
DeepSeek-R1 37%
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | | 88.5% | Jul 2024 | Model card | |
| 2 | | 84.8% | Jul 2024 | Model card | |
| 3 | | 78.3% | Jun 2025 | Model card | |
| 4 | GLM-4.5 | 77.8% | Jul 2025 | Model card | |
| 5 | | 77.3% | Dec 2024 | Model card | |
| 6 | Reka Flash 3 | 77.2% | Mar 2025 | Model card | |
| 7 | | 76.8% | Feb 2026 | Model card | |
| 8 | GLM-4.5-Air | 76.4% | Aug 2025 | Model card | |
| 9 | | 76.1% | Jul 2024 | Model card | |
| 10 | | 74.4% | Sep 2025 | Model card | |
| 11 | | 74.1% | Apr 2025 | Model card | |
| 12 | | 73.7% | Mar 2025 | Model card | |
| 13 | Granite 4.1 30B | 73.7% | Apr 2026 | Model card | |
| 14 | | 72% | Sep 2025 | Model card | |
| 15 | | 72% | Jun 2026 | Model card | |
| 16 | | 71.9% | Jul 2025 | Model card | |
| 17 | | 71.9% | Sep 2025 | Model card | |
| 18 | | 71.8% | Jul 2025 | Model card | |
| 19 | | 70.8% | Apr 2025 | Model card | |
| 20 | GLM-Z1-32B-0414 | 70.5% | Apr 2025 | Model card | |
| 21 | | 70.4% | May 2025 | Model card | |
| 22 | | 70.3% | Mar 2025 | Model card | |
| 23 | | 70.3% | May 2025 | Model card | |
| 24 | | 70.3% | Aug 2025 | Model card | |
| 25 | | 69.1% | May 2025 | Model card | |
| 26 | | 68.8% | Oct 2025 | Model card | |
| 27 | | 68.7% | Jul 2025 | Model card | |
| 28 | | 68.1% | May 2025 | Model card | |
| 29 | | 67.3% | Oct 2026 | Model card | |
| 30 | nvidia-nemotron-nano-9b-v2 | 66.9% | Aug 2025 | Model card | |
| 31 | | 65.9% | May 2025 | Model card | |
| 32 | | 65.2% | Jul 2025 | Model card | |
| 33 | | 65% | Sep 2025 | Model card | |
| 34 | Granite 4.0 H Small | 64.7% | Oct 2025 | Model card | |
| 35 | | 64.4% | Sep 2025 | Model card | |
| 36 | LFM2.5-8B-A1B | 64.4% | May 2026 | Model card | |
| 37 | | 63.9% | Jul 2025 | Model card | |
| 38 | | 63.8% | Apr 2025 | Model card | |
| 39 | | 63.7% | Apr 2025 | Model card | |
| 40 | | 61.1% | Mar 2026 | Model card | |
| 41 | | 59.7% | Dec 2025 | Model card | |
| 42 | ChatGLM3-6B | 57.9% | Jun 2024 | Model card | |
| 43 | LFM2.5-1.2B-Thinking | 57% | Jan 2026 | Model card | |
| 44 | | 56.6% | May 2025 | Model card | |
| 45 | granite-4.0-1b | 54.8% | Oct 2025 | Model card | |
| 46 | LFM2.5-1.2B-Instruct | 49.1% | Jan 2026 | Model card | |
| 47 | | 37% | May 2025 | Model card |
The benchmark's own leaderboard has 89 entries, 67 of them models we track. We plot every source in the charts below.
4 models have held number one since its release in Feb 2024
Lab claims count from the day the card came out, independent runs from the model’s release. We draw one row each for the benchmark’s own leaderboard and what labs claim in their cards.
The best score passed 85% in Jul 2024
All the scores we have, one dot each, so a model tested at several settings appears more than once.
2 labs put it in a launch post in the last six months
Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| 23 Oct 2026 | 67.3 | BFCL-v3 | |
| 2 Jun 2026 | 72 | BFCL v3 | |
| 28 May 2026 | LFM2.5-8B-A1B | 64.4 | BFCLv3 |
| 29 Apr 2026 | Granite 4.1 30B | 73.7 | BFCL v3 |
| 16 Mar 2026 | 61.1 | BFCL v3 | |
| 12 Feb 2026 | 76.8 | BFCL multi-turn | |
| 20 Jan 2026 | LFM2.5-1.2B-Thinking | 57 | BFCLv3 |
| 5 Jan 2026 | LFM2.5-1.2B-Instruct | 49.1 | BFCLv3 |
| 1 Dec 2025 | 59.7 | BFCL V3 | |
| 28 Oct 2025 | granite-4.0-1b | 54.8 | BFCL v3 |
| 2 Oct 2025 | Granite 4.0 H Small | 64.7 | BFCL v3 |
| 23 Sep 2025 | 71.9 | BFCL | |
| 22 Sep 2025 | 64.4 | BFCL-v3 | |
| 21 Sep 2025 | 74.4 | BFCL V3(full) | |
| 11 Sep 2025 | 72 | BFCL-v3 | |
| 9 Sep 2025 | 65 | BFCL (Accuracy) | |
| 21 Aug 2025 | 70.3 | BFCL-v3 (FC setting) | |
| 18 Aug 2025 | 66.9 | BFCL v3 | |
| 28 Jul 2025 | GLM-4.5 | 77.8 | BFCL v3 (Full) |
| 25 Jul 2025 | 71.8 | BFCL v3 | |
| 25 Jul 2025 | 71.9 | BFCL-v3 | |
| 22 Jul 2025 | 68.7 | BFCL-v3 | |
| 15 Jul 2025 | 65.2 | BFCL-v3 65.2 non-reasoning (63.9 reasoning) | |
| 10 Jul 2025 | 63.9 | BFCL.v3 | |
| 27 Jun 2025 | 78.3 | BFCL v3 | |
| 28 May 2025 | 37 | BFCL_v3_MultiTurn (Acc) | |
| 30 Apr 2025 | 63.7 | BFCL (2025-04-25) | |
| 29 Apr 2025 | 70.8 | BFCL v3 | |
| 14 Apr 2025 | GLM-Z1-32B-0414 | 70.5 | BFCL (v3) |
| 7 Apr 2025 | 74.1 | BFCL V2 Live (reasoning on) | |
| 18 Mar 2025 | 73.7 | BFCL V2 Live (reasoning off) | |
| 13 Mar 2025 | BFCL (BFCL-v3, 2025-03-12, chart only) | ||
| 10 Mar 2025 | Reka Flash 3 | 77.2 | BFCL v2 |
| 6 Mar 2025 | BFCL | ||
| 6 Dec 2024 | 77.3 | BFCL v2, overall_ast_summary/macro_avg/valid | |
| 23 Jul 2024 | 88.5 | BFCL |
31 system cards report it, from 11 labs
Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| 23 Oct 2026 | | 67.3 | BFCL-v3, released Q4_K_M imatrix checkpoint (Table 5). BF16 68.51 (Table 3) | Capabilities |
| 2 Jun 2026 | | 72 | BFCL v3 (Table 12, rounded) | Capabilities |
| 26 Nov 2025 | | 71.8 | BFCL-v3 (Table 6) | Capabilities |
| 21 Oct 2025 | | 68.8 | BFCL v3 (Table 1) | Capabilities |
| 23 Sep 2025 | | 74.4 | BFCL V3(full) (Table 2) | Capabilities |
| 22 Sep 2025 | | 64.4 | BFCL-v3, Instruct (Table 4). Thinking 63.2 (Table 5) | Capabilities |
| 20 Aug 2025 | | 66.9 | BFCLv3, NVIDIA-Nemotron-Nano-9B-v2 (Figure 1) | Capabilities |
| 8 Aug 2025 | GLM-4.5 technical report | 77.8 | BFCL V3 (Table 3) | Capabilities |
| 8 Aug 2025 | GLM-4.5-Air technical report | 76.4 | BFCL V3 (Table 3) | Capabilities |
| 15 Jul 2025 | | 63.9 | BFCL-v3 (Table 3, Reasoning). Non-reasoning 65.2 (Table 4) | Capabilities |
| 26 Jun 2025 | | 78.3 | BFCL v3, slow-thinking (Table 3). Fast-thinking 65.9 (Table 4) | Capabilities |
| 14 May 2025 | | 68.1 | BFCL v3, thinking mode (Table 17). Non-thinking 60.2 (Table 18) | Capabilities |
| 14 May 2025 | | 65.9 | BFCL v3, thinking mode (Table 17). Non-thinking 57.6 (Table 18) | Capabilities |
| 14 May 2025 | | 70.3 | BFCL v3, thinking mode (Table 13). Non-thinking 63.0 (Table 14) | Capabilities |
| 14 May 2025 | | 69.1 | BFCL v3, thinking mode (Table 15). Non-thinking 58.6 (Table 16) | Capabilities |
| 14 May 2025 | | 70.8 | BFCL v3, thinking mode (Table 11). Non-thinking 68.0 (Table 12) | Capabilities |
| 14 May 2025 | | 70.4 | BFCL v3, thinking mode (Table 15). Non-thinking 61.5 (Table 16) | Capabilities |
| 14 May 2025 | | 56.6 | BFCL v3, thinking mode (Table 19). Non-thinking 52.2 (Table 20) | Capabilities |
| 2 May 2025 | | 73.7 | BFCL V2 Live, reasoning on, reasoning off 73.9 (Table 4) | Capabilities |
| 2 May 2025 | | 74.1 | BFCL V2 Live, reasoning on, reasoning off 73.6 (Table 5) | Capabilities |
| 30 Apr 2025 | | 63.7 | BFCL (2025-04-25), BFCL V3 overall accuracy (Table 1) | Capabilities |
| 1 Apr 2025 | | 63.8 | BFCL Overall from the official leaderboard (Table 5). Live AST 80.5, Multi-turn 25.5 | Capabilities |
| 3 Mar 2025 | | 70.3 | BFCL (0-shot), version not stated (Table 7) | Capabilities |
| 6 Dec 2024 | | 77.3 | BFCL v2, 0-shot, overall_ast_summary/macro_avg/valid (Instruction tuned models table) | Capabilities |
| 23 Nov 2024 | | 76.1 | BFCL, post-trained (Table 2, Table 22) | Capabilities |
| 23 Nov 2024 | | 84.8 | BFCL, post-trained (Table 2, Table 22) | Capabilities |
| 23 Nov 2024 | | 88.5 | BFCL, post-trained (Table 2, Table 22) | Capabilities |
| 23 Jul 2024 | | 76.1 | BFCL, 0-shot, acc, instruction tuned (Instruction tuned models table) | Capabilities |
| 23 Jul 2024 | | 84.8 | BFCL, 0-shot, acc, instruction tuned (Instruction tuned models table) | Capabilities |
| 23 Jul 2024 | | 88.5 | BFCL, 0-shot, acc, instruction tuned (Instruction tuned models table) | Capabilities |
| 18 Jun 2024 | ChatGLM3-6B technical report | 57.9 | ChatGLM3-6B, Berkeley Function Call Leaderboard Overall (Table 7) | Capabilities |
Versions
We switch the top row to each new version when it comes out. Open it for one row per version. An old version stays in play while people still test it, so whoever first takes it past 85% gets credit for closing it out.
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