Berkeley Function Calling Leaderboard (BFCL) V4

Name: Berkeley Function Calling Leaderboard (BFCL) V4 results
Creator: Berkeley Function Calling Leaderboard (BFCL) V4
License: https://github.com/ShishirPatil/gorilla/blob/main/LICENSE

BFCL's own weighted average across its test categories.

Data older than 90 days: last updated 16 Dec 2025

Results dated: 16 Dec 2025
Results: 109 configurations of 81 models
Unit: % correct
Licence: Apache License 2.0

Overall accuracy: Grok 4 (0709)

Top 15 of 109 results · % correct, higher is better. Choose a model to highlight it.Clear highlight

1 Claude Opus 4.5Function callingAnthropic 77.5%
2 Claude Sonnet 4.5Function callingAnthropic 73.2%
3 Gemini 3 Pro PreviewPromptingGoogle 72.5%
4 GLM-4.6 (reasoning on)Function callingZ.ai 72.4%
5 Grok 4.1 Fast (reasoning)Function callingxAI 69.6%
6 Claude Haiku 4.5Function callingAnthropic 68.7%
7 Gemini 3 Pro PreviewFunction callingGoogle 68.1%
8 o3PromptingOpenAI 63.1%
9 Grok 4 (0709)PromptingxAI 63.0%
10 Grok 4 (0709)Function callingxAI 61.4%
11 Kimi K2 (0711)Function callingMoonshot AI 59.1%
12 Grok 4.1 Fast (non-reasoning)Function callingxAI 58.3%
13 Command A ReasoningFunction callingCohere 57.1%
14 DeepSeek-V3.2-Exp (reasoning on)PromptingDeepSeek 56.7%
15 Gemini 2.5 FlashFunction callingGoogle 56.2%

Full results

BFCL: overall accuracy, % correct, higher is better
#	Model	Overall accuracy % correct, higher is better	Price $ per million tokens, in / out
1	Claude Opus 4.5Function callingAnthropic	77.5%	$5 / $25
2	Claude Sonnet 4.5Function callingAnthropic	73.2%	$3 / $15
3	Gemini 3 Pro PreviewPromptingGoogle	72.5%	–
4	GLM-4.6 (reasoning on)Function callingZ.ai	72.4%	$0.50 / $2
5	Grok 4.1 Fast (reasoning)Function callingxAI	69.6%	–
6	Claude Haiku 4.5Function callingAnthropic	68.7%	$1 / $5
7	Gemini 3 Pro PreviewFunction callingGoogle	68.1%	–
8	o3PromptingOpenAI	63.1%	$2 / $8
9	Grok 4 (0709)PromptingxAI	63.0%	–
10	Grok 4 (0709)Function callingxAI	61.4%	–
11	Kimi K2 (0711)Function callingMoonshot AI	59.1%	$0.57 / $2.30
12	Grok 4.1 Fast (non-reasoning)Function callingxAI	58.3%	–
13	Command A ReasoningFunction callingCohere	57.1%	–
14	DeepSeek-V3.2-Exp (reasoning on)PromptingDeepSeek	56.7%	$0.27 / $0.41
15	Gemini 2.5 FlashFunction callingGoogle	56.2%	$0.30 / $2.50
16	GPT-5.2Function callingOpenAI	55.9%	$1.75 / $14
17	GPT-5 miniFunction callingOpenAI	55.5%	$0.25 / $2
18	xLAM-2-32b-fc-rFunction callingSalesforce	54.7%	–
19	DeepSeek-V3.2-ExpFunction callingDeepSeek	54.1%	$0.27 / $0.41
20	GPT-4.1Function callingOpenAI	54.0%	$2 / $8
21	o4-miniFunction callingOpenAI	53.2%	$1.10 / $4.40
22	xLAM-2-70b-fc-rFunction callingSalesforce	53.1%	–
23	Qwen3-235B-A22B-Instruct-2507PromptingAlibaba	52.2%	$0.15 / $0.75
24	GPT-5 nanoFunction callingOpenAI	51.5%	$0.05 / $0.40
25	Nanbeige4-3B-Thinking (2511)Function callingNanbeige	51.4%	–
26	Gemini 2.5 FlashPromptingGoogle	50.9%	$0.30 / $2.50
27	GPT-4.1 miniFunction callingOpenAI	50.5%	$0.40 / $1.60
28	o4-miniPromptingOpenAI	50.3%	$1.10 / $4.40
29	Qwen3-32BFunction callingAlibaba	48.7%	$0.14 / $0.40
30	o3Function callingOpenAI	48.6%	$2 / $8
31	Qwen3-235B-A22B-Instruct-2507Function callingAlibaba	48.0%	$0.15 / $0.75
32	Nanbeige3.5-Pro-ThinkingFunction callingNanbeige	47.7%	–
33	Qwen3-32BPromptingAlibaba	46.8%	$0.14 / $0.40
34	xLAM-2-8b-fc-rFunction callingSalesforce	46.7%	–
35	Command AFunction callingCohere	46.5%	$2.50 / $10
36	BitAgent Bounty 8BMode not statedBittensor	46.2%	–
37	Arch-Agent-32BMode not statedKatanemo	45.4%	–
38	GPT-5.2PromptingOpenAI	45.3%	$1.75 / $14
39	Qwen3-8BFunction callingAlibaba	42.6%	$0.12 / $0.46
40	ToolACE-2-8BFunction callingHuawei Noah's Ark Lab and USTC	42.4%	–
41	Qwen3-30B-A3B-Instruct-2507Function callingAlibaba	41.4%	$0.09 / $0.30
42	xLAM-2-3b-fc-rFunction callingSalesforce	41.2%	–
43	Qwen3-14BFunction callingAlibaba	41.0%	$0.12 / $0.24
44	Qwen3-8BPromptingAlibaba	40.4%	$0.12 / $0.46
45	GPT-4.1PromptingOpenAI	39.4%	$2 / $8
46	Mistral Large 2.1 (2411)Function callingMistral AI	38.4%	–
47	Qwen3-14BPromptingAlibaba	37.8%	$0.12 / $0.24
48	Mistral Medium 3Mode not statedMistral AI	37.7%	$0.40 / $2
49	Mistral Medium 3Function callingMistral AI	37.6%	$0.40 / $2
50	Llama 4 Maverick 17B 128E Instruct (FP8)Function callingMeta	37.3%	–
51	Mistral Small 3.2 24BFunction callingMistral AI	37.2%	$0.094 / $0.25
52	Gemini 2.5 Flash-LiteFunction callingGoogle	36.9%	$0.10 / $0.40
53	Qwen3-30B-A3B-Instruct-2507PromptingAlibaba	36.7%	$0.09 / $0.30
54	Qwen3-4B-Instruct-2507Function callingAlibaba	35.7%	–
55	Qwen3-4B-Instruct-2507PromptingAlibaba	35.5%	–
56	Arch-Agent-3BMode not statedKatanemo	35.4%	–
57	Claude Opus 4.5PromptingAnthropic	33.5%	$5 / $25
58	GPT-4.1 nanoFunction callingOpenAI	33.1%	$0.10 / $0.40
59	Mistral Small 3.2 24BPromptingMistral AI	32.4%	$0.094 / $0.25
60	Arch-Agent-1.5BMode not statedKatanemo	32.1%	–
60	Command R7B (12-2024)Function callingCohere	32.1%	$0.037 / $0.15
62	Llama 3.3 70B InstructFunction callingMeta	31.9%	$0.59 / $0.79
63	Mistral Large 2.1 (2411)PromptingMistral AI	31.8%	–
64	Hammer2.1-7BFunction callingMadeAgents	31.7%	–
65	xLAM-2-1b-fc-rFunction callingSalesforce	30.4%	–
65	Gemma 3 12BPromptingGoogle	30.4%	$0.05 / $0.15
67	GPT-4.1 miniPromptingOpenAI	29.7%	$0.40 / $1.60
67	Hammer2.1-3BFunction callingMadeAgents	29.7%	–
69	Gemma 3 27BPromptingGoogle	29.5%	$0.12 / $0.20
70	Phi-4PromptingMicrosoft	28.8%	$0.07 / $0.14
71	Qwen3-1.7BFunction callingAlibaba	28.4%	–
72	Llama 4 ScoutFunction callingMeta	28.1%	$0.18 / $0.59
73	Gemini 2.5 Flash-LitePromptingGoogle	28.0%	$0.10 / $0.40
73	CoALM 70BMode not statedUIUC and Oumi	28.0%	–
75	Hammer2.1-1.5BFunction callingMadeAgents	27.9%	–
75	Palmyra X 004Function callingWriter	27.9%	–
77	GPT-5 miniPromptingOpenAI	27.8%	$0.25 / $2
78	Mistral NemoFunction callingMistral AI	27.6%	$0.023 / $0.03
78	GPT-5 nanoPromptingOpenAI	27.6%	$0.05 / $0.40
80	Nova 2 LiteFunction callingAmazon	27.1%	$0.30 / $2.50
80	Granite 3.1 8B InstructFunction callingIBM	27.1%	–
82	Falcon3 10B InstructFunction callingTII	27.0%	–
83	Granite 3.2 8B InstructFunction callingIBM	26.9%	–
84	CoALM 8BMode not statedUIUC and Oumi	26.8%	–
85	Llama 3.1 8B InstructPromptingMeta	25.8%	$0.05 / $0.08
86	MiniCPM3-4BFunction callingOpenBMB	25.6%	–
87	Claude Haiku 4.5PromptingAnthropic	25.3%	$1 / $5
88	Nova Pro 1.0Function callingAmazon	25.0%	$0.80 / $3.20
89	Claude Sonnet 4.5PromptingAnthropic	24.9%	$3 / $15
89	GPT-4.1 nanoPromptingOpenAI	24.9%	$0.10 / $0.40
91	Falcon3 7B InstructFunction callingTII	24.0%	–
92	Qwen3-0.6BFunction callingAlibaba	23.9%	–
93	Granite 20B FunctionCallingFunction callingIBM	23.2%	–
94	Qwen3-0.6BPromptingAlibaba	22.4%	–
95	Nova Micro 1.0Function callingAmazon	22.3%	$0.035 / $0.14
95	RZN-TPromptingPhronetic AI	22.3%	–
97	MiniCPM3-4BPromptingOpenBMB	22.1%	–
98	Llama 3.2 3B InstructFunction callingMeta	22.0%	$0.05 / $0.33
99	Bielik 11B v2.3 InstructPromptingSpeakLeash and ACK Cyfronet AGH	21.9%	–
100	Hammer2.1-0.5BFunction callingMadeAgents	21.2%	–
101	Gemma 3 4BPromptingGoogle	19.6%	$0.05 / $0.10
102	Mistral NemoPromptingMistral AI	19.3%	$0.023 / $0.03
103	Granite 4.0 350MFunction callingIBM	19.0%	–
104	Falcon3 3B InstructFunction callingTII	16.3%	–
105	Ministral 8B (2410)Function callingMistral AI	11.1%	–
105	Falcon3 1B InstructFunction callingTII	11.1%	–
107	Llama 3.2 1B InstructFunction callingMeta	10.8%	$0.027 / $0.20
108	Llama 3.1 Nemotron Ultra 253B v1Function callingNVIDIA	10.0%	–
109	Gemma 3 1BPromptingGoogle	7.2%	–

Swipe the table sideways for more columns.

Ranks follow the score as shown, so equal numbers share a rank. Results as published by Berkeley Function Calling Leaderboard (BFCL) V4; we do not re-run them.

Progress over time

Overall accuracy, plotted at each model's release date, higher is better. Each model counts once, at its best setting. Scores are today's, not launch day's; 38 models without a known release date are left off. Hover or tap a mark for its model.

Best score so far

Every model at its release date. The line moves each time a new release beats every earlier one, and each new best is named where there is room.

Best score by lab

Each lab's best so far, stepping whenever one of its releases beats its own earlier models. The 6 labs with the best scores today; 7 others not drawn.

AnthropicGoogleZ.aixAIOpenAIMoonshot AI

What it measures

BFCL's own weighted average across its test categories.

What it does not measure

Not a neutral average: the weighting is BFCL's. Not reliability on your own tools: BFCL's functions and queries are a fixed test set, and a correct call is judged by its form, not by what it achieved.

Source

Berkeley Function Calling Leaderboard (BFCL) V4 · Methodology

Berkeley Function Calling Leaderboard (BFCL) V4 by the UC Berkeley Gorilla team, Apache License 2.0.