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.
- Made by
- UC Berkeley (Gorilla)
- Released
- February 2024
- Kind
- Function calling
- Level
- Everyday
- Scored
- Checked automatically
- Answers
- Agent task
- Tasks
- All public
- Strongest model tested
-
Qwen3-235B-A22B-Thinking Jul 2025 #107 on the capability index
- Last in a launch post
- October 2026
- Last model added
- October 2026
- Scores refreshed
- November 12th, 2026
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.
Llama-xLAM-2-70b-fc-r leads with 78.5% across all independent runs
Best score per model across the official leaderboard, Epoch AI’s own runs and any board Epoch AI copied. Each bar and row names its source.
Llama 3.1-405B leads with 88.5%, claims included
Best score per model from every source, including labs’ own numbers and claims Epoch AI collected from reports and papers. Labs pick their own settings, so a claim can beat an independent run of the same model.
- 88.5
Llama 3.1-405B
- 84.8
Llama 3.1-70B
- 78.3
Hunyuan-A13B-Instruct
- 77.8 GLM-4.5
- 76.4 GLM-4.5-Air
- 76.1
Llama 3.1-8B
- 74.4
LongCat-Flash-Thinking
- 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
- 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 GLM-4.5-Air 76.4%
- 6
Llama 3.1-8B 76.1%
- 7
LongCat-Flash-Thinking 74.4%
- 8 Granite 4.1 30B 73.7%
- 9
Qwen3-Next-80B-A3B 72%
- 10
MAI-Thinking-1 72%
- 11
Qwen3-235B-A22B-Thinking Jul 2025 71.9%
- 12
Qwen3-VL-235B-A22B 71.9%
- 13
Llama-3.3-Nemotron-Super-49B-v1.5 71.8%
- 14
Qwen3-235B-A22B 70.8%
- 15 GLM-Z1-32B-0414 70.5%
- 16
Qwen3-14B 70.4%
- 17
Phi-4 Mini 70.3%
- 18
Qwen3-32B 70.3%
- 19
Command A Reasoning 70.3%
- 20
Qwen3-30B-A3B 69.1%
- 21
Ring-1T 68.8%
- 22
Qwen3-Coder-480B-A35B 68.7%
- 23
Qwen3-8B 68.1%
- 24
Nemotron 3.5 Bolt E4B 67.3%
- 25 nvidia-nemotron-nano-9b-v2 66.9%
- 26
Qwen3-4B 65.9%
- 27
EXAONE 4.0 32B 65.2%
- 28
ERNIE-4.5-21B-A3B-Thinking 65%
- 29 Granite 4.0 H Small 64.7%
- 30
Qwen3-Omni-30B-A3B 64.4%
- 31 LFM2.5-8B-A1B 64.4%
- 32
Solar Pro 2 63.9%
- 33
Cohere Command A 63.8%
- 34
Amazon Nova Premier 63.7%
- 35
Nemotron 3 Nano 4B 61.1%
- 36
Trinity Mini 59.7%
- 37 ChatGLM3-6B 57.9%
- 38 LFM2.5-1.2B-Thinking 57%
- 39
Qwen3-1.7B 56.6%
- 40 granite-4.0-1b 54.8%
- 41 LFM2.5-1.2B-Instruct 49.1%
Source: Labs’ model cards
- 78.5
Llama-xLAM-2-70b-fc-r
- 76.4
xLAM-2-32b-fc-r
- 72.0
Llama-xLAM-2-8b-fc-r
- 71.7 GPT-4o
- 70.3 GPT-4.5
- 69.3
Qwen3-32B
- 68.9 GPT-4.1
- 68.0
Qwen3-14B
- 67.9
Qwen3-235B-A22B
- 67.8 o1
- 66.3
Qwen3-8B
- 65.7
Qwen3-30B-A3B
- 65.2 GPT-4.1 mini
- 64.8
xLAM-2-3b-fc-r
- 64.7
DeepSeek-V3
- 64.6 o3-mini
- 64.4
Cohere Command A
- 64.0 GPT-4o mini
- 63.8
DeepSeek-R1
- 63.4
Qwen3-4B
- 63.3 Grok 3
- 61.2
Gemini 2.0 Flash
- 60.8
Amazon Nova Pro
- 59.9
Gemini 2.5 Pro
- 59.1
Gemma 3 27B
- 58.7
Gemini 2.0 Flash Thinking
- 58.6 Claude 3.7 Sonnet
- 58.3
QwQ-32B
- 58.2
xLAM-2-1b-fc-r
- 58.0
Mistral Large 2
- 57.7
Mistral Small 3.1
- 57.0 Claude 3 Opus
- 56.9 Claude 3.5 Sonnet (October 2024)
- 56.8 Palmyra X4
- 56.7
Llama-3.1-Nemotron-Ultra-253B-v1
- 56.4
Gemini 2.0 Flash-Lite
- 55.9
Amazon Nova Lite
- 54.7
Qwen3-1.7B
- 53.7 Claude 3.5 Haiku
- 53.6
Llama 3.1-70B
- 53.0 Grok-3 mini
- 53.0 GPT-4.1 nano
- 52.9
Llama 4 Maverick
- 52.2
Llama 3.3 70B Instruct
- 51.8
Amazon Nova Micro
- 51.7
Command R7B
- 51.5
Ministral 8B
- 51.5
Mistral NeMo
- 50.6
Gemma 3 12B
- 50.3
MiniCPM3-4B
- 49.6
Llama 3.1-8B
- 48.9 Granite-20B-FunctionCalling
- 48.0
Command R+
- 47.3
Qwen3-0.6B
- 47.0
Phi-4
- 45.9
Llama 3.2 3B
- 45.4
Llama 4 Scout
- 45.1
Falcon3-10B-Instruct
- 43.6
Falcon3-7B-Instruct
- 39.6
Gemma 3 4B
- 39.2
DBRX
- 39.1 GLM-4-9B-Chat
- 32.5
Falcon3-3B-Instruct
- 31.3
Phi-4 Mini
- 21.9
Llama 3.2 1B
- 19.7
Falcon3-1B-Instruct
- 16.3
Gemma 3 1B
- 1
Llama-xLAM-2-70b-fc-r 78.5%
- 2
xLAM-2-32b-fc-r 76.4%
- 3
Llama-xLAM-2-8b-fc-r 72%
- 4 GPT-4o Nov 2024 71.7%
- 5 GPT-4.5 70.3%
- 6
Qwen3-32B 69.3%
- 7 GPT-4.1 68.9%
- 8
Qwen3-14B 68%
- 9
Qwen3-235B-A22B 67.9%
- 10 o1 67.8%
- 11
Qwen3-8B 66.3%
- 12
Qwen3-30B-A3B 65.7%
- 13 GPT-4.1 mini 65.2%
- 14
xLAM-2-3b-fc-r 64.8%
- 15
DeepSeek-V3 Mar 2025 64.7%
- 16 o3-mini 64.6%
- 17
Cohere Command A 64.4%
- 18 GPT-4o mini 64%
- 19
DeepSeek-R1 May 2025 63.8%
- 20
Qwen3-4B 63.4%
- 21 Grok 3 63.3%
- 22
Gemini 2.0 Flash Feb 2025 61.2%
- 23
Amazon Nova Pro 60.8%
- 24
Gemini 2.5 Pro May 2025 59.9%
- 25
Gemma 3 27B 59.1%
- 26
Gemini 2.0 Flash Thinking Jan 2025 58.7%
- 27 Claude 3.7 Sonnet 58.6%
- 28
QwQ-32B 58.3%
- 29
xLAM-2-1b-fc-r 58.2%
- 30
Mistral Large 2 Nov 2024 58%
- 31
Mistral Small 3.1 57.7%
- 32 Claude 3 Opus 57%
- 33 Claude 3.5 Sonnet (October 2024) 56.9%
- 34 Palmyra X4 56.8%
- 35
Llama-3.1-Nemotron-Ultra-253B-v1 56.7%
- 36
Gemini 2.0 Flash-Lite 56.4%
- 37
Amazon Nova Lite 55.9%
- 38
Qwen3-1.7B 54.7%
- 39 Claude 3.5 Haiku 53.7%
- 40
Llama 3.1-70B 53.6%
- 41 Grok-3 mini 53%
- 42 GPT-4.1 nano 53%
- 43
Llama 4 Maverick 52.9%
- 44
Llama 3.3 70B Instruct 52.2%
- 45
Amazon Nova Micro 51.8%
- 46
Command R7B 51.7%
- 47
Ministral 8B 51.5%
- 48
Mistral NeMo 51.5%
- 49
Gemma 3 12B 50.6%
- 50
MiniCPM3-4B 50.3%
- 51
Llama 3.1-8B 49.6%
- 52 Granite-20B-FunctionCalling 48.9%
- 53
Command R+ 48%
- 54
Qwen3-0.6B 47.3%
- 55
Phi-4 47%
- 56
Llama 3.2 3B 45.9%
- 57
Llama 4 Scout 45.4%
- 58
Falcon3-10B-Instruct 45.1%
- 59
Falcon3-7B-Instruct 43.6%
- 60
Gemma 3 4B 39.6%
- 61
DBRX 39.2%
- 62 GLM-4-9B-Chat 39.1%
- 63
Falcon3-3B-Instruct 32.5%
- 64
Phi-4 Mini 31.3%
- 65
Llama 3.2 1B 21.9%
- 66
Falcon3-1B-Instruct 19.7%
- 67
Gemma 3 1B 16.3%
Source: Official Berkeley Function Calling Leaderboard (BFCL) leaderboard
- 88.5
Llama 3.1-405B
- 84.8
Llama 3.1-70B
- 78.5
Llama-xLAM-2-70b-fc-r
- 78.3
Hunyuan-A13B-Instruct
- 77.8 GLM-4.5
- 76.4
xLAM-2-32b-fc-r
- 76.4 GLM-4.5-Air
- 76.1
Llama 3.1-8B
- 74.4
LongCat-Flash-Thinking
- 73.7 Granite 4.1 30B
- 72.0
Llama-xLAM-2-8b-fc-r
- 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
- 71.7 GPT-4o
- 70.8
Qwen3-235B-A22B
- 70.5 GLM-Z1-32B-0414
- 70.4
Qwen3-14B
- 70.3 GPT-4.5
- 70.3
Phi-4 Mini
- 70.3
Qwen3-32B
- 70.3
Command A Reasoning
- 69.1
Qwen3-30B-A3B
- 68.9 GPT-4.1
- 68.8
Ring-1T
- 68.7
Qwen3-Coder-480B-A35B
- 68.1
Qwen3-8B
- 67.8 o1
- 67.3
Nemotron 3.5 Bolt E4B
- 66.9 nvidia-nemotron-nano-9b-v2
- 65.9
Qwen3-4B
- 65.2
EXAONE 4.0 32B
- 65.2 GPT-4.1 mini
- 65.0
ERNIE-4.5-21B-A3B-Thinking
- 64.8
xLAM-2-3b-fc-r
- 64.7
DeepSeek-V3
- 64.7 Granite 4.0 H Small
- 64.6 o3-mini
- 64.4
Qwen3-Omni-30B-A3B
- 64.4
Cohere Command A
- 64.4 LFM2.5-8B-A1B
- 64.0 GPT-4o mini
- 63.9
Solar Pro 2
- 63.8
DeepSeek-R1
- 63.7
Amazon Nova Premier
- 63.3 Grok 3
- 61.2
Gemini 2.0 Flash
- 61.1
Nemotron 3 Nano 4B
- 60.8
Amazon Nova Pro
- 59.9
Gemini 2.5 Pro
- 59.7
Trinity Mini
- 59.1
Gemma 3 27B
- 58.7
Gemini 2.0 Flash Thinking
- 58.6 Claude 3.7 Sonnet
- 58.3
QwQ-32B
- 58.2
xLAM-2-1b-fc-r
- 58.0
Mistral Large 2
- 57.9 ChatGLM3-6B
- 57.7
Mistral Small 3.1
- 57.0 LFM2.5-1.2B-Thinking
- 57.0 Claude 3 Opus
- 56.9 Claude 3.5 Sonnet (October 2024)
- 56.8 Palmyra X4
- 56.7
Llama-3.1-Nemotron-Ultra-253B-v1
- 56.6
Qwen3-1.7B
- 56.4
Gemini 2.0 Flash-Lite
- 55.9
Amazon Nova Lite
- 54.8 granite-4.0-1b
- 53.7 Claude 3.5 Haiku
- 53.0 Grok-3 mini
- 53.0 GPT-4.1 nano
- 52.9
Llama 4 Maverick
- 52.2
Llama 3.3 70B Instruct
- 51.8
Amazon Nova Micro
- 51.7
Command R7B
- 51.5
Ministral 8B
- 51.5
Mistral NeMo
- 50.6
Gemma 3 12B
- 50.3
MiniCPM3-4B
- 49.1 LFM2.5-1.2B-Instruct
- 48.9 Granite-20B-FunctionCalling
- 48.0
Command R+
- 47.3
Qwen3-0.6B
- 47.0
Phi-4
- 45.9
Llama 3.2 3B
- 45.4
Llama 4 Scout
- 45.1
Falcon3-10B-Instruct
- 43.6
Falcon3-7B-Instruct
- 39.6
Gemma 3 4B
- 39.2
DBRX
- 39.1 GLM-4-9B-Chat
- 32.5
Falcon3-3B-Instruct
- 21.9
Llama 3.2 1B
- 19.7
Falcon3-1B-Instruct
- 16.3
Gemma 3 1B
- 1
Llama 3.1-405B 88.5%
- 2
Llama 3.1-70B 84.8%
- 3
Llama-xLAM-2-70b-fc-r 78.5%
- 4
Hunyuan-A13B-Instruct 78.3%
- 5 GLM-4.5 77.8%
- 6
xLAM-2-32b-fc-r 76.4%
- 7 GLM-4.5-Air 76.4%
- 8
Llama 3.1-8B 76.1%
- 9
LongCat-Flash-Thinking 74.4%
- 10 Granite 4.1 30B 73.7%
- 11
Llama-xLAM-2-8b-fc-r 72%
- 12
Qwen3-Next-80B-A3B 72%
- 13
MAI-Thinking-1 72%
- 14
Qwen3-235B-A22B-Thinking Jul 2025 71.9%
- 15
Qwen3-VL-235B-A22B 71.9%
- 16
Llama-3.3-Nemotron-Super-49B-v1.5 71.8%
- 17 GPT-4o Nov 2024 71.7%
- 18
Qwen3-235B-A22B 70.8%
- 19 GLM-Z1-32B-0414 70.5%
- 20
Qwen3-14B 70.4%
- 21 GPT-4.5 70.3%
- 22
Phi-4 Mini 70.3%
- 23
Qwen3-32B 70.3%
- 24
Command A Reasoning 70.3%
- 25
Qwen3-30B-A3B 69.1%
- 26 GPT-4.1 68.9%
- 27
Ring-1T 68.8%
- 28
Qwen3-Coder-480B-A35B 68.7%
- 29
Qwen3-8B 68.1%
- 30 o1 67.8%
- 31
Nemotron 3.5 Bolt E4B 67.3%
- 32 nvidia-nemotron-nano-9b-v2 66.9%
- 33
Qwen3-4B 65.9%
- 34
EXAONE 4.0 32B 65.2%
- 35 GPT-4.1 mini 65.2%
- 36
ERNIE-4.5-21B-A3B-Thinking 65%
- 37
xLAM-2-3b-fc-r 64.8%
- 38
DeepSeek-V3 Mar 2025 64.7%
- 39 Granite 4.0 H Small 64.7%
- 40 o3-mini 64.6%
- 41
Qwen3-Omni-30B-A3B 64.4%
- 42
Cohere Command A 64.4%
- 43 LFM2.5-8B-A1B 64.4%
- 44 GPT-4o mini 64%
- 45
Solar Pro 2 63.9%
- 46
DeepSeek-R1 May 2025 63.8%
- 47
Amazon Nova Premier 63.7%
- 48 Grok 3 63.3%
- 49
Gemini 2.0 Flash Feb 2025 61.2%
- 50
Nemotron 3 Nano 4B 61.1%
- 51
Amazon Nova Pro 60.8%
- 52
Gemini 2.5 Pro May 2025 59.9%
- 53
Trinity Mini 59.7%
- 54
Gemma 3 27B 59.1%
- 55
Gemini 2.0 Flash Thinking Jan 2025 58.7%
- 56 Claude 3.7 Sonnet 58.6%
- 57
QwQ-32B 58.3%
- 58
xLAM-2-1b-fc-r 58.2%
- 59
Mistral Large 2 Nov 2024 58%
- 60 ChatGLM3-6B 57.9%
- 61
Mistral Small 3.1 57.7%
- 62 LFM2.5-1.2B-Thinking 57%
- 63 Claude 3 Opus 57%
- 64 Claude 3.5 Sonnet (October 2024) 56.9%
- 65 Palmyra X4 56.8%
- 66
Llama-3.1-Nemotron-Ultra-253B-v1 56.7%
- 67
Qwen3-1.7B 56.6%
- 68
Gemini 2.0 Flash-Lite 56.4%
- 69
Amazon Nova Lite 55.9%
- 70 granite-4.0-1b 54.8%
- 71 Claude 3.5 Haiku 53.7%
- 72 Grok-3 mini 53%
- 73 GPT-4.1 nano 53%
- 74
Llama 4 Maverick 52.9%
- 75
Llama 3.3 70B Instruct 52.2%
- 76
Amazon Nova Micro 51.8%
- 77
Command R7B 51.7%
- 78
Ministral 8B 51.5%
- 79
Mistral NeMo 51.5%
- 80
Gemma 3 12B 50.6%
- 81
MiniCPM3-4B 50.3%
- 82 LFM2.5-1.2B-Instruct 49.1%
- 83 Granite-20B-FunctionCalling 48.9%
- 84
Command R+ 48%
- 85
Qwen3-0.6B 47.3%
- 86
Phi-4 47%
- 87
Llama 3.2 3B 45.9%
- 88
Llama 4 Scout 45.4%
- 89
Falcon3-10B-Instruct 45.1%
- 90
Falcon3-7B-Instruct 43.6%
- 91
Gemma 3 4B 39.6%
- 92
DBRX 39.2%
- 93 GLM-4-9B-Chat 39.1%
- 94
Falcon3-3B-Instruct 32.5%
- 95
Llama 3.2 1B 21.9%
- 96
Falcon3-1B-Instruct 19.7%
- 97
Gemma 3 1B 16.3%
Sources: Labs’ model cards and official Berkeley Function Calling Leaderboard (BFCL) leaderboard
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | | 88.5% | Jul 2024 | Lab model card | |
| 2 | | 84.8% | Jul 2024 | Lab model card | |
| 3 | | 78.3% | Jun 2025 | Lab model card | |
| 4 | GLM-4.5 | 77.8% | Jul 2025 | Lab model card | |
| 5 | GLM-4.5-Air | 76.4% | Aug 2025 | Lab model card | |
| 6 | | 76.1% | Jul 2024 | Lab model card | |
| 7 | | 74.4% | Sep 2025 | Lab model card | |
| 8 | Granite 4.1 30B | 73.7% | Apr 2026 | Lab model card | |
| 9 | | 72% | Sep 2025 | Lab model card | |
| 10 | | 72% | Jun 2026 | Lab model card | |
| 11 | | 71.9% | Jul 2025 | Lab model card | |
| 12 | | 71.9% | Sep 2025 | Lab model card | |
| 13 | | 71.8% | Jul 2025 | Lab model card | |
| 14 | | 70.8% | Apr 2025 | Lab model card | |
| 15 | GLM-Z1-32B-0414 | 70.5% | Apr 2025 | Lab model card | |
| 16 | | 70.4% | May 2025 | Lab model card | |
| 17 | | 70.3% | Mar 2025 | Lab model card | |
| 18 | | 70.3% | May 2025 | Lab model card | |
| 19 | | 70.3% | Aug 2025 | Lab model card | |
| 20 | | 69.1% | May 2025 | Lab model card | |
| 21 | | 68.8% | Oct 2025 | Lab model card | |
| 22 | | 68.7% | Jul 2025 | Lab model card | |
| 23 | | 68.1% | May 2025 | Lab model card | |
| 24 | | 67.3% | Oct 2026 | Lab model card | |
| 25 | nvidia-nemotron-nano-9b-v2 | 66.9% | Aug 2025 | Lab model card | |
| 26 | | 65.9% | May 2025 | Lab model card | |
| 27 | | 65.2% | Jul 2025 | Lab model card | |
| 28 | | 65% | Sep 2025 | Lab model card | |
| 29 | Granite 4.0 H Small | 64.7% | Oct 2025 | Lab model card | |
| 30 | | 64.4% | Sep 2025 | Lab model card | |
| 31 | LFM2.5-8B-A1B | 64.4% | May 2026 | Lab model card | |
| 32 | | 63.9% | Jul 2025 | Lab model card | |
| 33 | | 63.8% | Apr 2025 | Lab model card | |
| 34 | | 63.7% | Apr 2025 | Lab model card | |
| 35 | | 61.1% | Mar 2026 | Lab model card | |
| 36 | | 59.7% | Dec 2025 | Lab model card | |
| 37 | ChatGLM3-6B | 57.9% | Jun 2024 | Lab model card | |
| 38 | LFM2.5-1.2B-Thinking | 57% | Jan 2026 | Lab model card | |
| 39 | | 56.6% | May 2025 | Lab model card | |
| 40 | granite-4.0-1b | 54.8% | Oct 2025 | Lab model card | |
| 41 | LFM2.5-1.2B-Instruct | 49.1% | Jan 2026 | Lab model card |
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | | 78.5% | native function calling | Mar 2025 | Official leaderboard |
| 2 | | 76.4% | native function calling | Mar 2025 | Official leaderboard |
| 3 | | 72% | native function calling | Mar 2025 | Official leaderboard |
| 4 | GPT-4o Nov 2024 | 71.7% | native function calling | Nov 2024 | Official leaderboard |
| 5 | GPT-4.5 | 70.3% | native function calling | Feb 2025 | Official leaderboard |
| 6 | | 69.3% | native function calling | Apr 2025 | Official leaderboard |
| 7 | GPT-4.1 | 68.9% | native function calling | Apr 2025 | Official leaderboard |
| 8 | | 68% | native function calling | Apr 2025 | Official leaderboard |
| 9 | | 67.9% | native function calling | Apr 2025 | Official leaderboard |
| 10 | o1 | 67.8% | prompted | Dec 2024 | Official leaderboard |
| 11 | | 66.3% | native function calling | Apr 2025 | Official leaderboard |
| 12 | | 65.7% | native function calling | Apr 2025 | Official leaderboard |
| 13 | GPT-4.1 mini | 65.2% | native function calling | Apr 2025 | Official leaderboard |
| 14 | | 64.8% | native function calling | Mar 2025 | Official leaderboard |
| 15 | | 64.7% | native function calling | Mar 2025 | Official leaderboard |
| 16 | o3-mini | 64.6% | prompted | Jan 2025 | Official leaderboard |
| 17 | | 64.4% | native function calling | Mar 2025 | Official leaderboard |
| 18 | GPT-4o mini | 64% | native function calling | Jul 2024 | Official leaderboard |
| 19 | | 63.8% | native function calling | May 2025 | Official leaderboard |
| 20 | | 63.4% | native function calling | Apr 2025 | Official leaderboard |
| 21 | Grok 3 | 63.3% | native function calling | Apr 2025 | Official leaderboard |
| 22 | | 61.2% | native function calling | Feb 2025 | Official leaderboard |
| 23 | | 60.8% | native function calling | Dec 2024 | Official leaderboard |
| 24 | | 59.9% | native function calling | May 2025 | Official leaderboard |
| 25 | | 59.1% | prompted | Mar 2025 | Official leaderboard |
| 26 | | 58.7% | prompted | Jan 2025 | Official leaderboard |
| 27 | Claude 3.7 Sonnet | 58.6% | native function calling | Feb 2025 | Official leaderboard |
| 28 | | 58.3% | native function calling | Mar 2025 | Official leaderboard |
| 29 | | 58.2% | native function calling | Mar 2025 | Official leaderboard |
| 30 | | 58% | native function calling | Nov 2024 | Official leaderboard |
| 31 | | 57.7% | native function calling | Mar 2025 | Official leaderboard |
| 32 | Claude 3 Opus | 57% | native function calling | Feb 2024 | Official leaderboard |
| 33 | Claude 3.5 Sonnet (October 2024) | 56.9% | native function calling | Oct 2024 | Official leaderboard |
| 34 | Palmyra X4 | 56.8% | native function calling | Oct 2024 | Official leaderboard |
| 35 | | 56.7% | native function calling | Apr 2025 | Official leaderboard |
| 36 | | 56.4% | prompted | Feb 2025 | Official leaderboard |
| 37 | | 55.9% | native function calling | Dec 2024 | Official leaderboard |
| 38 | | 54.7% | native function calling | Apr 2025 | Official leaderboard |
| 39 | Claude 3.5 Haiku | 53.7% | prompted | Oct 2024 | Official leaderboard |
| 40 | | 53.6% | prompted | Jul 2024 | Official leaderboard |
| 41 | Grok-3 mini | 53% | native function calling | Apr 2025 | Official leaderboard |
| 42 | GPT-4.1 nano | 53% | native function calling | Apr 2025 | Official leaderboard |
| 43 | | 52.9% | native function calling | Apr 2025 | Official leaderboard |
| 44 | | 52.2% | native function calling | Dec 2024 | Official leaderboard |
| 45 | | 51.8% | native function calling | Dec 2024 | Official leaderboard |
| 46 | | 51.7% | native function calling | Dec 2024 | Official leaderboard |
| 47 | | 51.5% | native function calling | Oct 2024 | Official leaderboard |
| 48 | | 51.5% | native function calling | Jul 2024 | Official leaderboard |
| 49 | | 50.6% | prompted | Mar 2025 | Official leaderboard |
| 50 | | 50.3% | native function calling | Sep 2024 | Official leaderboard |
| 51 | | 49.6% | prompted | Jul 2024 | Official leaderboard |
| 52 | Granite-20B-FunctionCalling | 48.9% | native function calling | Jul 2024 | Official leaderboard |
| 53 | | 48% | native function calling | Aug 2024 | Official leaderboard |
| 54 | | 47.3% | native function calling | Apr 2025 | Official leaderboard |
| 55 | | 47% | prompted | Dec 2024 | Official leaderboard |
| 56 | | 45.9% | native function calling | Sep 2024 | Official leaderboard |
| 57 | | 45.4% | native function calling | Apr 2025 | Official leaderboard |
| 58 | | 45.1% | native function calling | Dec 2024 | Official leaderboard |
| 59 | | 43.6% | native function calling | Dec 2024 | Official leaderboard |
| 60 | | 39.6% | prompted | Mar 2025 | Official leaderboard |
| 61 | | 39.2% | prompted | Mar 2024 | Official leaderboard |
| 62 | GLM-4-9B-Chat | 39.1% | native function calling | Jun 2024 | Official leaderboard |
| 63 | | 32.5% | native function calling | Dec 2024 | Official leaderboard |
| 64 | | 31.3% | prompted | Feb 2025 | Official leaderboard |
| 65 | | 21.9% | native function calling | Sep 2024 | Official leaderboard |
| 66 | | 19.7% | native function calling | Dec 2024 | Official leaderboard |
| 67 | | 16.3% | prompted | Mar 2025 | Official leaderboard |
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | | 88.5% | Jul 2024 | Lab model card | |
| 2 | | 84.8% | Jul 2024 | Lab model card | |
| 3 | | 78.5% | native function calling | Mar 2025 | Official leaderboard |
| 4 | | 78.3% | Jun 2025 | Lab model card | |
| 5 | GLM-4.5 | 77.8% | Jul 2025 | Lab model card | |
| 6 | | 76.4% | native function calling | Mar 2025 | Official leaderboard |
| 7 | GLM-4.5-Air | 76.4% | Aug 2025 | Lab model card | |
| 8 | | 76.1% | Jul 2024 | Lab model card | |
| 9 | | 74.4% | Sep 2025 | Lab model card | |
| 10 | Granite 4.1 30B | 73.7% | Apr 2026 | Lab model card | |
| 11 | | 72% | native function calling | Mar 2025 | Official leaderboard |
| 12 | | 72% | Sep 2025 | Lab model card | |
| 13 | | 72% | Jun 2026 | Lab model card | |
| 14 | | 71.9% | Jul 2025 | Lab model card | |
| 15 | | 71.9% | Sep 2025 | Lab model card | |
| 16 | | 71.8% | Jul 2025 | Lab model card | |
| 17 | GPT-4o Nov 2024 | 71.7% | native function calling | Nov 2024 | Official leaderboard |
| 18 | | 70.8% | Apr 2025 | Lab model card | |
| 19 | GLM-Z1-32B-0414 | 70.5% | Apr 2025 | Lab model card | |
| 20 | | 70.4% | May 2025 | Lab model card | |
| 21 | GPT-4.5 | 70.3% | native function calling | Feb 2025 | Official leaderboard |
| 22 | | 70.3% | Mar 2025 | Lab model card | |
| 23 | | 70.3% | May 2025 | Lab model card | |
| 24 | | 70.3% | Aug 2025 | Lab model card | |
| 25 | | 69.1% | May 2025 | Lab model card | |
| 26 | GPT-4.1 | 68.9% | native function calling | Apr 2025 | Official leaderboard |
| 27 | | 68.8% | Oct 2025 | Lab model card | |
| 28 | | 68.7% | Jul 2025 | Lab model card | |
| 29 | | 68.1% | May 2025 | Lab model card | |
| 30 | o1 | 67.8% | prompted | Dec 2024 | Official leaderboard |
| 31 | | 67.3% | Oct 2026 | Lab model card | |
| 32 | nvidia-nemotron-nano-9b-v2 | 66.9% | Aug 2025 | Lab model card | |
| 33 | | 65.9% | May 2025 | Lab model card | |
| 34 | | 65.2% | Jul 2025 | Lab model card | |
| 35 | GPT-4.1 mini | 65.2% | native function calling | Apr 2025 | Official leaderboard |
| 36 | | 65% | Sep 2025 | Lab model card | |
| 37 | | 64.8% | native function calling | Mar 2025 | Official leaderboard |
| 38 | | 64.7% | native function calling | Mar 2025 | Official leaderboard |
| 39 | Granite 4.0 H Small | 64.7% | Oct 2025 | Lab model card | |
| 40 | o3-mini | 64.6% | prompted | Jan 2025 | Official leaderboard |
| 41 | | 64.4% | Sep 2025 | Lab model card | |
| 42 | | 64.4% | native function calling | Mar 2025 | Official leaderboard |
| 43 | LFM2.5-8B-A1B | 64.4% | May 2026 | Lab model card | |
| 44 | GPT-4o mini | 64% | native function calling | Jul 2024 | Official leaderboard |
| 45 | | 63.9% | Jul 2025 | Lab model card | |
| 46 | | 63.8% | native function calling | May 2025 | Official leaderboard |
| 47 | | 63.7% | Apr 2025 | Lab model card | |
| 48 | Grok 3 | 63.3% | native function calling | Apr 2025 | Official leaderboard |
| 49 | | 61.2% | native function calling | Feb 2025 | Official leaderboard |
| 50 | | 61.1% | Mar 2026 | Lab model card | |
| 51 | | 60.8% | native function calling | Dec 2024 | Official leaderboard |
| 52 | | 59.9% | native function calling | May 2025 | Official leaderboard |
| 53 | | 59.7% | Dec 2025 | Lab model card | |
| 54 | | 59.1% | prompted | Mar 2025 | Official leaderboard |
| 55 | | 58.7% | prompted | Jan 2025 | Official leaderboard |
| 56 | Claude 3.7 Sonnet | 58.6% | native function calling | Feb 2025 | Official leaderboard |
| 57 | | 58.3% | native function calling | Mar 2025 | Official leaderboard |
| 58 | | 58.2% | native function calling | Mar 2025 | Official leaderboard |
| 59 | | 58% | native function calling | Nov 2024 | Official leaderboard |
| 60 | ChatGLM3-6B | 57.9% | Jun 2024 | Lab model card | |
| 61 | | 57.7% | native function calling | Mar 2025 | Official leaderboard |
| 62 | LFM2.5-1.2B-Thinking | 57% | Jan 2026 | Lab model card | |
| 63 | Claude 3 Opus | 57% | native function calling | Feb 2024 | Official leaderboard |
| 64 | Claude 3.5 Sonnet (October 2024) | 56.9% | native function calling | Oct 2024 | Official leaderboard |
| 65 | Palmyra X4 | 56.8% | native function calling | Oct 2024 | Official leaderboard |
| 66 | | 56.7% | native function calling | Apr 2025 | Official leaderboard |
| 67 | | 56.6% | May 2025 | Lab model card | |
| 68 | | 56.4% | prompted | Feb 2025 | Official leaderboard |
| 69 | | 55.9% | native function calling | Dec 2024 | Official leaderboard |
| 70 | granite-4.0-1b | 54.8% | Oct 2025 | Lab model card | |
| 71 | Claude 3.5 Haiku | 53.7% | prompted | Oct 2024 | Official leaderboard |
| 72 | Grok-3 mini | 53% | native function calling | Apr 2025 | Official leaderboard |
| 73 | GPT-4.1 nano | 53% | native function calling | Apr 2025 | Official leaderboard |
| 74 | | 52.9% | native function calling | Apr 2025 | Official leaderboard |
| 75 | | 52.2% | native function calling | Dec 2024 | Official leaderboard |
| 76 | | 51.8% | native function calling | Dec 2024 | Official leaderboard |
| 77 | | 51.7% | native function calling | Dec 2024 | Official leaderboard |
| 78 | | 51.5% | native function calling | Oct 2024 | Official leaderboard |
| 79 | | 51.5% | native function calling | Jul 2024 | Official leaderboard |
| 80 | | 50.6% | prompted | Mar 2025 | Official leaderboard |
| 81 | | 50.3% | native function calling | Sep 2024 | Official leaderboard |
| 82 | LFM2.5-1.2B-Instruct | 49.1% | Jan 2026 | Lab model card | |
| 83 | Granite-20B-FunctionCalling | 48.9% | native function calling | Jul 2024 | Official leaderboard |
| 84 | | 48% | native function calling | Aug 2024 | Official leaderboard |
| 85 | | 47.3% | native function calling | Apr 2025 | Official leaderboard |
| 86 | | 47% | prompted | Dec 2024 | Official leaderboard |
| 87 | | 45.9% | native function calling | Sep 2024 | Official leaderboard |
| 88 | | 45.4% | native function calling | Apr 2025 | Official leaderboard |
| 89 | | 45.1% | native function calling | Dec 2024 | Official leaderboard |
| 90 | | 43.6% | native function calling | Dec 2024 | Official leaderboard |
| 91 | | 39.6% | prompted | Mar 2025 | Official leaderboard |
| 92 | | 39.2% | prompted | Mar 2024 | Official leaderboard |
| 93 | GLM-4-9B-Chat | 39.1% | native function calling | Jun 2024 | Official leaderboard |
| 94 | | 32.5% | native function calling | Dec 2024 | Official leaderboard |
| 95 | | 21.9% | native function calling | Sep 2024 | Official leaderboard |
| 96 | | 19.7% | native function calling | Dec 2024 | Official leaderboard |
| 97 | | 16.3% | prompted | Mar 2025 | Official leaderboard |
The benchmark's own leaderboard has 89 entries, 67 of them models we track. Switch the scores above to rank them together.
Of runs with a cost, the best scores 71.7% for $0.008 a task
Runs on the cost frontier score higher than any run that's cheaper. The costs are the leaderboard's own estimates, so compare them only within this benchmark.
Source: Official Berkeley Function Calling Leaderboard (BFCL) leaderboard
| Model | Effort | Harness | Score | Cost per task | Output tokens |
|---|---|---|---|---|---|
| | native function calling | 78.5% | |||
| | native function calling | 76.4% | |||
| | native function calling | 72% | |||
| GPT-4o Nov 2024 | native function calling | 71.7% | $0.008 | ||
| GPT-4o Nov 2024 | prompted | 70.4% | $0.01 | ||
| GPT-4.5 | native function calling | 70.3% | $0.24 | ||
| | native function calling | 69.3% | |||
| GPT-4.1 | native function calling | 68.9% | $0.007 | ||
| GPT-4.1 | prompted | 68% | $0.01 | ||
| | native function calling | 68% | |||
| | native function calling | 67.9% | |||
| o1 | prompted | 67.8% | $0.10 | ||
| | native function calling | 66.3% | |||
| | native function calling | 65.7% | |||
| GPT-4.1 mini | native function calling | 65.2% | $0.001 | ||
| | native function calling | 64.8% | |||
| | native function calling | 64.7% | |||
| o3-mini | prompted | 64.6% | $0.008 | ||
| | native function calling | 64.4% | $0.007 | ||
| GPT-4o mini | native function calling | 64% | $0.0005 | ||
| | native function calling | 63.8% | |||
| | native function calling | 63.4% | |||
| Grok 3 | native function calling | 63.3% | $0.02 | ||
| GPT-4.5 | prompted | 62.6% | $0.47 | ||
| GPT-4o mini | prompted | 61.8% | $0.0009 | ||
| | native function calling | 61.2% | $0.0006 | ||
| | native function calling | 60.8% | $0.005 | ||
| GPT-4.1 mini | prompted | 60.6% | $0.002 | ||
| | prompted | 60% | $0.0008 | ||
| | native function calling | 59.9% | |||
| | prompted | 59.1% | |||
| | prompted | 58.7% | |||
| Claude 3.7 Sonnet | native function calling | 58.6% | $0.003 | ||
| | native function calling | 58.3% | |||
| | native function calling | 58.2% | |||
| | native function calling | 58% | $0.007 | ||
| | native function calling | 57.7% | $0.0004 | ||
| Claude 3 Opus | native function calling | 57% | $0.02 | ||
| Claude 3.5 Sonnet (October 2024) | native function calling | 56.9% | $0.002 | ||
| Palmyra X4 | native function calling | 56.8% | $0.03 | ||
| | native function calling | 56.7% | |||
| | prompted | 56.4% | $0.0003 | ||
| | native function calling | 56.2% | $0.0003 | ||
| Grok 3 | prompted | 56.1% | $0.02 | ||
| o1 | native function calling | 56.1% | $0.07 | ||
| | native function calling | 55.9% | $0.0004 | ||
| | native function calling | 54.7% | |||
| Claude 3.5 Haiku | prompted | 53.7% | $0.0005 | ||
| | prompted | 53.6% | |||
| Grok-3 mini | native function calling | 53% | $0.001 | ||
| GPT-4.1 nano | native function calling | 53% | $0.0004 | ||
| | native function calling | 52.9% | |||
| Claude 3.5 Haiku | native function calling | 52.5% | $0.0008 | ||
| | native function calling | 52.2% | |||
| | native function calling | 51.8% | $0.0002 | ||
| | native function calling | 51.7% | $0.0001 | ||
| | native function calling | 51.5% | |||
| | native function calling | 51.5% | $0.0006 | ||
| o3-mini | native function calling | 51.3% | $0.005 | ||
| | prompted | 50.6% | |||
| Claude 3.5 Sonnet (October 2024) | prompted | 50.5% | $0.001 | ||
| | native function calling | 50.3% | |||
| Claude 3.7 Sonnet | prompted | 50% | $0.001 | ||
| Claude 3 Opus | prompted | 49.7% | $0.01 | ||
| | prompted | 49.6% | |||
| GPT-4.1 nano | prompted | 49.4% | $0.0006 | ||
| Granite-20B-FunctionCalling | native function calling | 48.9% | |||
| | native function calling | 48% | $0.008 | ||
| | native function calling | 47.3% | |||
| | prompted | 47% | |||
| | native function calling | 45.9% | |||
| | native function calling | 45.4% | |||
| | native function calling | 45.1% | |||
| | native function calling | 43.6% | |||
| | prompted | 40.9% | |||
| | prompted | 39.7% | $0.0009 | ||
| | prompted | 39.6% | |||
| | prompted | 39.2% | $0.009 | ||
| GLM-4-9B-Chat | native function calling | 39.1% | |||
| | native function calling | 32.5% | |||
| | prompted | 31.3% | |||
| | native function calling | 28.2% | |||
| | native function calling | 27.1% | |||
| | native function calling | 25.9% | |||
| | native function calling | 21.9% | |||
| | native function calling | 19.7% | |||
| | prompted | 16.3% |
2 models have held number one in labs’ own numbers since its release in February 2024 4 models have held number one across all independent runs since its release in February 2024 4 models have held number one with claims included since its release in February 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.
Sources: Official Berkeley Function Calling Leaderboard (BFCL) leaderboard and labs’ model cards
Meta’s own number for Llama 3.1-405B passed 85% in July 2024
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Sources: Official Berkeley Function Calling Leaderboard (BFCL) leaderboard and labs’ model cards
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 |
|---|---|---|---|
| Oct 23, 2026 | 67.3 | BFCL-v3 | |
| Jun 2, 2026 | 72 | BFCL v3 | |
| May 28, 2026 | LFM2.5-8B-A1B | 64.4 | BFCLv3 |
| Apr 29, 2026 | Granite 4.1 30B | 73.7 | BFCL v3 |
| Mar 16, 2026 | 61.1 | BFCL v3 | |
| Feb 12, 2026 | BFCL multi-turn | ||
| Jan 20, 2026 | LFM2.5-1.2B-Thinking | 57 | BFCLv3 |
| Jan 5, 2026 | LFM2.5-1.2B-Instruct | 49.1 | BFCLv3 |
| Dec 1, 2025 | 59.7 | BFCL V3 | |
| Oct 28, 2025 | granite-4.0-1b | 54.8 | BFCL v3 |
| Oct 2, 2025 | Granite 4.0 H Small | 64.7 | BFCL v3 |
| Sep 23, 2025 | 71.9 | BFCL | |
| Sep 22, 2025 | 64.4 | BFCL-v3 | |
| Sep 21, 2025 | 74.4 | BFCL V3(full) | |
| Sep 11, 2025 | 72 | BFCL-v3 | |
| Sep 9, 2025 | 65 | BFCL (Accuracy) | |
| Aug 21, 2025 | 70.3 | BFCL-v3 (FC setting) | |
| Aug 18, 2025 | 66.9 | BFCL v3 | |
| Jul 28, 2025 | GLM-4.5 | 77.8 | BFCL v3 (Full) |
| Jul 25, 2025 | 71.8 | BFCL v3 | |
| Jul 25, 2025 | 71.9 | BFCL-v3 | |
| Jul 22, 2025 | 68.7 | BFCL-v3 | |
| Jul 15, 2025 | 65.2 | BFCL-v3 65.2 non-reasoning (63.9 reasoning) | |
| Jul 10, 2025 | 63.9 | BFCL.v3 | |
| Jun 27, 2025 | 78.3 | BFCL v3 | |
| May 28, 2025 | BFCL_v3_MultiTurn (Acc) | ||
| Apr 30, 2025 | 63.7 | BFCL (2025-04-25) | |
| Apr 29, 2025 | 70.8 | BFCL v3 | |
| Apr 14, 2025 | GLM-Z1-32B-0414 | 70.5 | BFCL (v3) |
| Apr 7, 2025 | BFCL V2 Live (reasoning on) | ||
| Mar 18, 2025 | BFCL V2 Live (reasoning off) | ||
| Mar 13, 2025 | BFCL (BFCL-v3, 2025-03-12, chart only) | ||
| Mar 10, 2025 | Reka Flash 3 | BFCL v2 | |
| Mar 6, 2025 | BFCL | ||
| Dec 6, 2024 | BFCL v2, overall_ast_summary/macro_avg/valid | ||
| Jul 23, 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 |
|---|---|---|---|---|
| Oct 23, 2026 | | 67.3 | BFCL-v3, released Q4_K_M imatrix checkpoint (Table 5). BF16 68.51 (Table 3) | Capabilities |
| Jun 2, 2026 | | 72 | BFCL v3 (Table 12, rounded) | Capabilities |
| Nov 26, 2025 | | 71.8 | BFCL-v3 (Table 6) | Capabilities |
| Oct 21, 2025 | | 68.8 | BFCL v3 (Table 1) | Capabilities |
| Sep 23, 2025 | | 74.4 | BFCL V3(full) (Table 2) | Capabilities |
| Sep 22, 2025 | | 64.4 | BFCL-v3, Instruct (Table 4). Thinking 63.2 (Table 5) | Capabilities |
| Aug 20, 2025 | | 66.9 | BFCLv3, NVIDIA-Nemotron-Nano-9B-v2 (Figure 1) | Capabilities |
| Aug 8, 2025 | GLM-4.5 technical report | 77.8 | BFCL V3 (Table 3) | Capabilities |
| Aug 8, 2025 | GLM-4.5-Air technical report | 76.4 | BFCL V3 (Table 3) | Capabilities |
| Jul 15, 2025 | | 63.9 | BFCL-v3 (Table 3, Reasoning). Non-reasoning 65.2 (Table 4) | Capabilities |
| Jun 26, 2025 | | 78.3 | BFCL v3, slow-thinking (Table 3). Fast-thinking 65.9 (Table 4) | Capabilities |
| May 14, 2025 | | 68.1 | BFCL v3, thinking mode (Table 17). Non-thinking 60.2 (Table 18) | Capabilities |
| May 14, 2025 | | 65.9 | BFCL v3, thinking mode (Table 17). Non-thinking 57.6 (Table 18) | Capabilities |
| May 14, 2025 | | 70.3 | BFCL v3, thinking mode (Table 13). Non-thinking 63.0 (Table 14) | Capabilities |
| May 14, 2025 | | 69.1 | BFCL v3, thinking mode (Table 15). Non-thinking 58.6 (Table 16) | Capabilities |
| May 14, 2025 | | 70.8 | BFCL v3, thinking mode (Table 11). Non-thinking 68.0 (Table 12) | Capabilities |
| May 14, 2025 | | 70.4 | BFCL v3, thinking mode (Table 15). Non-thinking 61.5 (Table 16) | Capabilities |
| May 14, 2025 | | 56.6 | BFCL v3, thinking mode (Table 19). Non-thinking 52.2 (Table 20) | Capabilities |
| May 2, 2025 | | BFCL V2 Live, reasoning on, reasoning off 73.9 (Table 4) | Capabilities | |
| May 2, 2025 | | BFCL V2 Live, reasoning on, reasoning off 73.6 (Table 5) | Capabilities | |
| Apr 30, 2025 | | 63.7 | BFCL (2025-04-25), BFCL V3 overall accuracy (Table 1) | Capabilities |
| Apr 1, 2025 | | 63.8 | BFCL Overall from the official leaderboard (Table 5). Live AST 80.5, Multi-turn 25.5 | Capabilities |
| Mar 3, 2025 | | 70.3 | BFCL (0-shot), version not stated (Table 7) | Capabilities |
| Dec 6, 2024 | | BFCL v2, 0-shot, overall_ast_summary/macro_avg/valid (Instruction tuned models table) | Capabilities | |
| Nov 23, 2024 | | 76.1 | BFCL, post-trained (Table 2, Table 22) | Capabilities |
| Nov 23, 2024 | | 84.8 | BFCL, post-trained (Table 2, Table 22) | Capabilities |
| Nov 23, 2024 | | 88.5 | BFCL, post-trained (Table 2, Table 22) | Capabilities |
| Jul 23, 2024 | | 76.1 | BFCL, 0-shot, acc, instruction tuned (Instruction tuned models table) | Capabilities |
| Jul 23, 2024 | | 84.8 | BFCL, 0-shot, acc, instruction tuned (Instruction tuned models table) | Capabilities |
| Jul 23, 2024 | | 88.5 | BFCL, 0-shot, acc, instruction tuned (Instruction tuned models table) | Capabilities |
| Jun 18, 2024 | ChatGLM3-6B technical report | 57.9 | ChatGLM3-6B, Berkeley Function Call Leaderboard Overall (Table 7) | Capabilities |
The lab's number comes out ahead in 10 of 11 pairs that differ
Each score a lab reported for its own model, beside the same model's best score on the leaderboard. Gaps mostly come from different harnesses, effort levels and task subsets. Every benchmark.
| Model | Lab says | Board says | Gap |
|---|---|---|---|
| | 70.3% BFCL (0-shot), version not stated (Table 7) | 31.3% Leaderboard, prompted | +39 pts |
| | 84.8% BFCL, 0-shot, acc, instruction tuned (Instruction tuned models table) | 53.6% Leaderboard, prompted | +31 pts |
| | 76.1% BFCL, 0-shot, acc, instruction tuned (Instruction tuned models table) | 49.6% Leaderboard, prompted | +27 pts |
| | 69.1% BFCL v3, thinking mode (Table 15). Non-thinking 58.6 (Table 16) | 65.7% Leaderboard, native function calling | +3.4 pts |
| | 70.8% BFCL v3 | 67.9% Leaderboard, native function calling | +2.9 pts |
| | 65.9% BFCL v3, thinking mode (Table 17). Non-thinking 57.6 (Table 18) | 63.4% Leaderboard, native function calling | +2.5 pts |
| | 70.4% BFCL v3, thinking mode (Table 15). Non-thinking 61.5 (Table 16) | 68% Leaderboard, native function calling | +2.4 pts |
| | 56.6% BFCL v3, thinking mode (Table 19). Non-thinking 52.2 (Table 20) | 54.7% Leaderboard, native function calling | +1.9 pts |
| | 68.1% BFCL v3, thinking mode (Table 17). Non-thinking 60.2 (Table 18) | 66.3% Leaderboard, native function calling | +1.8 pts |
| | 70.3% BFCL v3, thinking mode (Table 13). Non-thinking 63.0 (Table 14) | 69.3% Leaderboard, native function calling | +1.0 pts |
| | 63.8% BFCL Overall from the official leaderboard (Table 5). Live AST 80.5, Multi-turn 25.5 | 64.4% Leaderboard, native function calling | −0.6 pts |
5 logged changes that move scores
Changes by the maintainers, so a score from before a change may not compare with one from after it. Newest first, each with the maintainers' own source. The list may be incomplete. What we log.
- Grader changed October 30th, 2024
The maintainers required multi-turn answers to pass both response and state checks. Earlier evaluations checked state alone. Source
- Questions corrected October 16th, 2024
The maintainers corrected questions and reference answers across six categories. Earlier evaluations used different task definitions. Source
- Tasks changed September 19th, 2024
The maintainers added multi-turn tasks and state-based evaluation in BFCL V3. Its coverage differs from earlier versions. Source
- Tasks changed August 19th, 2024
The maintainers added user-contributed live tasks in BFCL V2. Its coverage differs from V1. Source
- Questions corrected July 6th, 2024
The maintainers corrected reference answers for 39 parallel-call tasks. Earlier scores used different answer keys. Source
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.
Source: Labs’ model cards
More in Tool use
- AutomationBench In use Agent completes end-to-end business workflows inside a simulated company exposing dozens of REST APIs. Graded on resulting state.
Gemini 4 Carbon 53.9%
- MCP Atlas In use Multi-step workflows over real MCP servers. Scores tool-use competency on realistic tasks.
Gemini 4 Argon 90.7%
- τ³-bench Banking In use Agents act as banking customer-service reps over many turns with a simulated user, following policy. Pass^1 on the final database state.
Qwen 3.8 Max 55.1%
- Toolathlon-Verified In use 108 long-horizon tasks across 32 apps through about 600 MCP tools. Execution-based checkers inspect final environment state. GLM-5.3-Flash 78.4%
- DeepSearchQA In use Questions that need multi-step search and synthesis. Final answers graded against references. Kimi K3 95%
- Claw-Eval In use 300 human-verified agent tasks (service orchestration, multimodal, multi-turn dialogue) audited via traces and snapshots. Rubric scores with Pass^3 consistency. Claude Sonnet 4.6 81.4%