HumanEval
164 hand-written Python function problems. Generated code is scored pass@1 against unit tests.
Saturated. Reported only for DeepSeek-V4 base model.
- Made by
- OpenAI
- Released
- July 2021
- Kind
- Function-level problems
- Level
- School
- Scored
- Checked automatically
- Answers
- Code
- Tasks
- All public
- Strongest model tested
-
DeepSeek V4.1 Flash #34 on the capability index
- Last in a launch post
- September 2026, dropped after it saturated
- Last model added
- October 2026
- Scores refreshed
- November 12th, 2026
In the authors’ words
We introduce Codex, a GPT language model fine-tuned on publicly available code from GitHub, and study its Python code-writing capabilities. A distinct production version of Codex powers GitHub Copilot. On HumanEval, a new evaluation set we release to measure functional correctness for synthesizing programs from docstrings, our model solves 28.8% of the problems, while GPT-3 solves 0% and GPT-J solves 11.4%. Furthermore, we find that repeated sampling from the model is a surprisingly effective strategy for producing working solutions to difficult prompts. Using this method, we solve 70.2% of our problems with 100 samples per problem. Careful investigation of our model reveals its limitations, including difficulty with docstrings describing long chains of operations and with binding operations to variables. Finally, we discuss the potential broader impacts of deploying powerful code generation technologies, covering safety, security, and economics.
Solar Pro 2 leads with 98.8%
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.
o1-mini leads with 96.3% across all independent runs
Best score per model across EvalPlus’s leaderboard, Epoch AI’s own runs and any board Epoch AI copied. Each bar and row names its source.
Solar Pro 2 leads with 98.8%, 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.
- 98.8
Solar Pro 2
- 98.2
InternVL3.5-241B-A28B
- 96.3 Reka Flash 3
- 95.9
Tulu 3 405B
- 94.5
DiffusionGemma 26B A4B
- 93.7 Claude 3.5 Sonnet (October 2024)
- 92.1
Mistral Medium 3
- 92.1 Sarvam 30B
- 92.0 Claude 3.5 Sonnet
- 92.0
Mistral Large 2
- 91.0
Hunyuan-TurboS
- 90.2 GPT-4o
- 90.0 Mercury Coder Small
- 89.7 Granite 3.3 8B Instruct
- 89.3 Granite 3.2 8B Instruct
- 89.0
Llama 3.1-405B
- 89.0
DeepSeek-V2.5
- 88.4
Mistral Small 3.1
- 88.4 Granite 4.1 30B
- 88.4 Grok-2
- 88.4
Llama 3.3 70B Instruct
- 88.4
Qwen2.5-32B
- 88.4
Qwen2.5-14B-Instruct-1M
- 88.2 GPT-4 Turbo
- 88.1 Claude 3.5 Haiku
- 88.0 Sarvam-M
- 88.0 Granite 4.0 H Small
- 87.8
Qwen2.5-VL-72B
- 87.8
Gemma 3 27B
- 87.3 Beam 1.0 Base
- 87.2 GPT-4o mini
- 87.2
Falcon-H1-34B
- 86.9
MiniMax-Text-01
- 86.6
Qwen2.5-72B
- 86.6
Qwen-Turbo
- 86.6
Codestral
- 86.0
Qwen2-72B
- 85.4
Gemma 3 12B
- 85.4
Cohere Command A
- 85.0 Mercury
- 84.9 Claude 3 Opus
- 84.8
Qwen2.5-7B
- 84.8
Mistral Small 3
- 84.8
Seed-Coder-8B-Instruct
- 84.1
Gemini 1.5 Pro
- 83.8
Nemotron 3 Ultra 550B-A55B Base
- 83.5
Qwen2.5-14B
- 82.8
Seed Diffusion Preview
- 82.6
Phi-4
- 82.3
InternLM3-8B-Instruct
- 81.7
Llama 3-70B
- 81.3
Nemotron 3.5 Super 120B-A12B Base
- 81.1
DeepSeek-V2 (MoE-236B, May 2024)
- 80.5
Llama 3.1-70B
- 79.4
DeepSeek V4.1 Flash
- 79.4
DeepSeek-V4.1-Flash Base
- 78.7
Qwen2.5-Omni-7B
- 78.0
Nemotron 3 Nano 30B-A3B Base
- 76.9
Nemotron 3.5 Lightning 30B-A3B Base
- 76.8
DeepSeek-V4-Pro
- 75.9 Claude 3 Haiku
- 75.0
Gemma 3n E4B
- 74.4
Gemini 1.0 Ultra
- 74.4
Phi-4 Mini
- 74.1 Grok-1.5
- 74.0 granite-4.0-1b
- 73.8
DeepSeek LLM 67B
- 73.0 Claude 3 Sonnet
- 73.0
Apertus 70B
- 72.6
Llama 3.1-8B
- 72.0 GLM-4
- 71.9
Gemini 1.5 Pro
- 71.3
Gemma 3 4B
- 71.2 Claude 2
- 70.7
Phi-3.5-MoE
- 67.0 GPT-4
- 65.2
DeepSeek-V3
- 63.2 Grok-1
- 62.2
Llama 3-8B
- 62.2
phi-3-medium 14B
- 61.5
Phi-3.5-mini
- 61.0
phi-3-small 7.4B
- 58.5 ChatGLM3-6B
- 58.5
phi-3-mini 3.8B
- 51.8
Gemma 2 27B
- 48.1 Moonlight-16B-A3B
- 45.1
Mistral Large
- 43.9
Qwen-14B
- 41.5
Qwen1.5-72B
- 41.5
Gemma 3 1B
- 40.2
Mixtral 8x7B
- 40.2
Gemma 2 9B
- 37.2
Qwen-7B
- 32.3
Gemma 7B
- 30.5
Mistral 7B v0.1
- 29.9
Llama 2-70B
- 22.6
Llama 2-34B
- 22.0
Gemma 2B
- 18.3
Llama 2-13B
- 14.6 Qwen-1_8B
- 12.8
Llama 2-7B
- 1
Solar Pro 2 98.8%
- 2
InternVL3.5-241B-A28B 98.2%
- 3 Reka Flash 3 96.3%
- 4
Tulu 3 405B 95.9%
- 5
DiffusionGemma 26B A4B 94.5%
- 6 Claude 3.5 Sonnet (October 2024) 93.7%
- 7
Mistral Medium 3 92.1%
- 8 Sarvam 30B 92.1%
- 9 Claude 3.5 Sonnet 92%
- 10
Mistral Large 2 Jul 2024 92%
- 11
Hunyuan-TurboS 91%
- 12 GPT-4o May 2024 90.2%
- 13 Mercury Coder Small 90%
- 14 Granite 3.3 8B Instruct 89.7%
- 15 Granite 3.2 8B Instruct 89.3%
- 16
Llama 3.1-405B 89%
- 17
DeepSeek-V2.5 Sep 2024 89%
- 18
Mistral Small 3.1 88.4%
- 19 Granite 4.1 30B 88.4%
- 20 Grok-2 Aug 2024 88.4%
- 21
Llama 3.3 70B Instruct 88.4%
- 22
Qwen2.5-32B 88.4%
- 23
Qwen2.5-14B-Instruct-1M 88.4%
- 24 GPT-4 Turbo Apr 2024 88.2%
- 25 Claude 3.5 Haiku 88.1%
- 26 Sarvam-M 88%
- 27 Granite 4.0 H Small 88%
- 28
Qwen2.5-VL-72B 87.8%
- 29
Gemma 3 27B 87.8%
- 30 Beam 1.0 Base 87.3%
- 31 GPT-4o mini 87.2%
- 32
Falcon-H1-34B 87.2%
- 33
MiniMax-Text-01 86.9%
- 34
Qwen2.5-72B 86.6%
- 35
Qwen-Turbo 86.6%
- 36
Codestral 86.6%
- 37
Qwen2-72B 86%
- 38
Gemma 3 12B 85.4%
- 39
Cohere Command A 85.4%
- 40 Mercury 85%
- 41 Claude 3 Opus 84.9%
- 42
Qwen2.5-7B 84.8%
- 43
Mistral Small 3 84.8%
- 44
Seed-Coder-8B-Instruct 84.8%
- 45
Gemini 1.5 Pro May 2024 84.1%
- 46
Nemotron 3 Ultra 550B-A55B Base 83.8%
- 47
Qwen2.5-14B 83.5%
- 48
Seed Diffusion Preview 82.8%
- 49
Phi-4 82.6%
- 50
InternLM3-8B-Instruct 82.3%
- 51
Llama 3-70B 81.7%
- 52
Nemotron 3.5 Super 120B-A12B Base 81.3%
- 53
DeepSeek-V2 (MoE-236B, May 2024) 81.1%
- 54
Llama 3.1-70B 80.5%
- 55
DeepSeek V4.1 Flash 79.4%
- 56
DeepSeek-V4.1-Flash Base 79.4%
- 57
Qwen2.5-Omni-7B 78.7%
- 58
Nemotron 3 Nano 30B-A3B Base 78%
- 59
Nemotron 3.5 Lightning 30B-A3B Base 76.9%
- 60
DeepSeek-V4-Pro 76.8%
- 61 Claude 3 Haiku 75.9%
- 62
Gemma 3n E4B 75%
- 63
Gemini 1.0 Ultra 74.4%
- 64
Phi-4 Mini 74.4%
- 65 Grok-1.5 74.1%
- 66 granite-4.0-1b 74%
- 67
DeepSeek LLM 67B 73.8%
- 68 Claude 3 Sonnet 73%
- 69
Apertus 70B 73%
- 70
Llama 3.1-8B 72.6%
- 71 GLM-4 72%
- 72
Gemini 1.5 Pro Feb 2024 71.9%
- 73
Gemma 3 4B 71.3%
- 74 Claude 2 71.2%
- 75
Phi-3.5-MoE 70.7%
- 76 GPT-4 Mar 2023 67%
- 77
DeepSeek-V3 65.2%
- 78 Grok-1 63.2%
- 79
Llama 3-8B 62.2%
- 80
phi-3-medium 14B 62.2%
- 81
Phi-3.5-mini 61.5%
- 82
phi-3-small 7.4B 61%
- 83 ChatGLM3-6B 58.5%
- 84
phi-3-mini 3.8B 58.5%
- 85
Gemma 2 27B 51.8%
- 86 Moonlight-16B-A3B 48.1%
- 87
Mistral Large 45.1%
- 88
Qwen-14B 43.9%
- 89
Qwen1.5-72B 41.5%
- 90
Gemma 3 1B 41.5%
- 91
Mixtral 8x7B 40.2%
- 92
Gemma 2 9B 40.2%
- 93
Qwen-7B 37.2%
- 94
Gemma 7B 32.3%
- 95
Mistral 7B v0.1 30.5%
- 96
Llama 2-70B 29.9%
- 97
Llama 2-34B 22.6%
- 98
Gemma 2B 22%
- 99
Llama 2-13B 18.3%
- 100 Qwen-1_8B 14.6%
- 101
Llama 2-7B 12.8%
Source: Labs’ model cards
- 96.3 o1-mini
- 96.3 o1-preview
- 92.7 GPT-4o
- 92.1
Qwen2.5-Coder-32B-Instruct
- 91.5
DeepSeek-V3
- 90.2 GPT-4 Turbo
- 90.2
DeepSeek-V2.5
- 89.0
Gemini 1.5 Pro
- 88.4 GPT-4
- 88.4 GPT-4o mini
- 87.2 Claude 3.5 Sonnet
- 85.4 GPT-4 Turbo
- 85.4
DeepSeek-Coder-V2 236B
- 82.9 Claude 3 Opus
- 82.3
Gemini 1.5 Flash
- 77.4
Llama 3-70B
- 76.8 GPT-3.5 Turbo
- 76.8 Claude 3 Haiku
- 76.2
Mixtral 8x22B
- 75.0
DBRX
- 73.2 GPT-3.5 Turbo (Mar 2023)
- 72.0
Code Llama 70B Instruct
- 70.7 Claude 3 Sonnet
- 69.5 Claude 2
- 69.5
Mistral Large
- 69.5
Llama 3.1-8B
- 68.3
Qwen1.5-72B
- 64.6
phi-3-mini 3.8B
- 63.4
Gemini 1.0 Pro
- 61.6
Llama 3-8B
- 57.3 Claude Instant
- 51.8 CodeQwen1.5-7B
- 49.4
Phi-2
- 46.3
StarCoder 2 15B
- 45.1
Mixtral 8x7B
- 43.3
SOLAR-10.7B-Instruct-v1.0
- 42.7
Gemma 1.1 7B IT
- 42.1
Mistral-7B-Instruct-v0.2
- 35.4
StarCoder 2 7B
- 35.4
Gemma 7B
- 31.7
StarCoder 2 3B
- 28.7
Mistral 7B v0.1
- 25.0
Gemma 2B
- 22.6
Gemma 1.1 2B IT
- 12.2 GPT-J-6B
- 7.90 GPT-Neo-2.7B
- 1 o1-mini 96.3%
- 2 o1-preview 96.3%
- 3 GPT-4o Aug 2024 92.7%
- 4
Qwen2.5-Coder-32B-Instruct 92.1%
- 5
DeepSeek-V3 91.5%
- 6 GPT-4 Turbo Apr 2024 90.2%
- 7
DeepSeek-V2.5 Sep 2024 90.2%
- 8
Gemini 1.5 Pro Sep 2024 89%
- 9 GPT-4 Mar 2023 88.4%
- 10 GPT-4o mini 88.4%
- 11 Claude 3.5 Sonnet 87.2%
- 12 GPT-4 Turbo Nov 2023 85.4%
- 13
DeepSeek-Coder-V2 236B 85.4%
- 14 Claude 3 Opus 82.9%
- 15
Gemini 1.5 Flash Sep 2024 82.3%
- 16
Llama 3-70B 77.4%
- 17 GPT-3.5 Turbo Nov 2023 76.8%
- 18 Claude 3 Haiku 76.8%
- 19
Mixtral 8x22B 76.2%
- 20
DBRX 75%
- 21 GPT-3.5 Turbo (Mar 2023) 73.2%
- 22
Code Llama 70B Instruct 72%
- 23 Claude 3 Sonnet 70.7%
- 24 Claude 2 69.5%
- 25
Mistral Large 69.5%
- 26
Llama 3.1-8B 69.5%
- 27
Qwen1.5-72B 68.3%
- 28
phi-3-mini 3.8B 64.6%
- 29
Gemini 1.0 Pro 63.4%
- 30
Llama 3-8B 61.6%
- 31 Claude Instant 57.3%
- 32 CodeQwen1.5-7B 51.8%
- 33
Phi-2 49.4%
- 34
StarCoder 2 15B 46.3%
- 35
Mixtral 8x7B 45.1%
- 36
SOLAR-10.7B-Instruct-v1.0 43.3%
- 37
Gemma 1.1 7B IT 42.7%
- 38
Mistral-7B-Instruct-v0.2 42.1%
- 39
StarCoder 2 7B 35.4%
- 40
Gemma 7B 35.4%
- 41
StarCoder 2 3B 31.7%
- 42
Mistral 7B v0.1 28.7%
- 43
Gemma 2B 25%
- 44
Gemma 1.1 2B IT 22.6%
- 45 GPT-J-6B 12.2%
- 46 GPT-Neo-2.7B 7.90%
Source: EvalPlus’s leaderboard
- 98.8
Solar Pro 2
- 98.2
InternVL3.5-241B-A28B
- 96.3 o1-mini
- 96.3 o1-preview
- 96.3 Reka Flash 3
- 95.9
Tulu 3 405B
- 94.5
DiffusionGemma 26B A4B
- 93.7 Claude 3.5 Sonnet (October 2024)
- 92.7 GPT-4o
- 92.1
Qwen2.5-Coder-32B-Instruct
- 92.1
Mistral Medium 3
- 92.1 Sarvam 30B
- 92.0 Claude 3.5 Sonnet
- 92.0
Mistral Large 2
- 91.5
DeepSeek-V3
- 91.0
Hunyuan-TurboS
- 90.2 GPT-4 Turbo
- 90.2 GPT-4o
- 90.2
DeepSeek-V2.5
- 90.0 Mercury Coder Small
- 89.7 Granite 3.3 8B Instruct
- 89.3 Granite 3.2 8B Instruct
- 89.0
Llama 3.1-405B
- 89.0
Gemini 1.5 Pro
- 88.4
Mistral Small 3.1
- 88.4 Granite 4.1 30B
- 88.4 GPT-4
- 88.4 GPT-4o mini
- 88.4 Grok-2
- 88.4
Llama 3.3 70B Instruct
- 88.4
Qwen2.5-32B
- 88.4
Qwen2.5-14B-Instruct-1M
- 88.1 Claude 3.5 Haiku
- 88.0 Sarvam-M
- 88.0 Granite 4.0 H Small
- 87.8
Qwen2.5-VL-72B
- 87.8
Gemma 3 27B
- 87.3 Beam 1.0 Base
- 87.2
Falcon-H1-34B
- 86.9
MiniMax-Text-01
- 86.6
Qwen2.5-72B
- 86.6
Qwen-Turbo
- 86.6
Codestral
- 86.0
Qwen2-72B
- 85.4 GPT-4 Turbo
- 85.4
DeepSeek-Coder-V2 236B
- 85.4
Gemma 3 12B
- 85.4
Cohere Command A
- 85.0 Mercury
- 84.9 Claude 3 Opus
- 84.8
Qwen2.5-7B
- 84.8
Mistral Small 3
- 84.8
Seed-Coder-8B-Instruct
- 84.1
Gemini 1.5 Pro
- 83.8
Nemotron 3 Ultra 550B-A55B Base
- 83.5
Qwen2.5-14B
- 82.8
Seed Diffusion Preview
- 82.6
Phi-4
- 82.3
Gemini 1.5 Flash
- 82.3
InternLM3-8B-Instruct
- 81.7
Llama 3-70B
- 81.3
Nemotron 3.5 Super 120B-A12B Base
- 81.1
DeepSeek-V2 (MoE-236B, May 2024)
- 80.5
Llama 3.1-70B
- 79.4
DeepSeek V4.1 Flash
- 79.4
DeepSeek-V4.1-Flash Base
- 78.7
Qwen2.5-Omni-7B
- 78.0
Nemotron 3 Nano 30B-A3B Base
- 76.9
Nemotron 3.5 Lightning 30B-A3B Base
- 76.8 GPT-3.5 Turbo
- 76.8 Claude 3 Haiku
- 76.8
DeepSeek-V4-Pro
- 76.2
Mixtral 8x22B
- 75.0
DBRX
- 75.0
Gemma 3n E4B
- 74.4
Gemini 1.0 Ultra
- 74.4
Phi-4 Mini
- 74.1 Grok-1.5
- 74.0 granite-4.0-1b
- 73.8
DeepSeek LLM 67B
- 73.2 GPT-3.5 Turbo (Mar 2023)
- 73.0 Claude 3 Sonnet
- 73.0
Apertus 70B
- 72.6
Llama 3.1-8B
- 72.0 GLM-4
- 72.0
Code Llama 70B Instruct
- 71.9
Gemini 1.5 Pro
- 71.3
Gemma 3 4B
- 71.2 Claude 2
- 70.7
Phi-3.5-MoE
- 69.5
Mistral Large
- 68.3
Qwen1.5-72B
- 64.6
phi-3-mini 3.8B
- 63.4
Gemini 1.0 Pro
- 63.2 Grok-1
- 62.2
Llama 3-8B
- 62.2
phi-3-medium 14B
- 61.5
Phi-3.5-mini
- 61.0
phi-3-small 7.4B
- 58.5 ChatGLM3-6B
- 57.3 Claude Instant
- 51.8 CodeQwen1.5-7B
- 51.8
Gemma 2 27B
- 49.4
Phi-2
- 48.1 Moonlight-16B-A3B
- 46.3
StarCoder 2 15B
- 45.1
Mixtral 8x7B
- 43.9
Qwen-14B
- 43.3
SOLAR-10.7B-Instruct-v1.0
- 42.7
Gemma 1.1 7B IT
- 42.1
Mistral-7B-Instruct-v0.2
- 41.5
Gemma 3 1B
- 40.2
Gemma 2 9B
- 37.2
Qwen-7B
- 35.4
StarCoder 2 7B
- 35.4
Gemma 7B
- 31.7
StarCoder 2 3B
- 30.5
Mistral 7B v0.1
- 29.9
Llama 2-70B
- 25.0
Gemma 2B
- 22.6
Llama 2-34B
- 22.6
Gemma 1.1 2B IT
- 18.3
Llama 2-13B
- 14.6 Qwen-1_8B
- 12.8
Llama 2-7B
- 12.2 GPT-J-6B
- 7.90 GPT-Neo-2.7B
- 1
Solar Pro 2 98.8%
- 2
InternVL3.5-241B-A28B 98.2%
- 3 o1-mini 96.3%
- 4 o1-preview 96.3%
- 5 Reka Flash 3 96.3%
- 6
Tulu 3 405B 95.9%
- 7
DiffusionGemma 26B A4B 94.5%
- 8 Claude 3.5 Sonnet (October 2024) 93.7%
- 9 GPT-4o Aug 2024 92.7%
- 10
Qwen2.5-Coder-32B-Instruct 92.1%
- 11
Mistral Medium 3 92.1%
- 12 Sarvam 30B 92.1%
- 13 Claude 3.5 Sonnet 92%
- 14
Mistral Large 2 Jul 2024 92%
- 15
DeepSeek-V3 91.5%
- 16
Hunyuan-TurboS 91%
- 17 GPT-4 Turbo Apr 2024 90.2%
- 18 GPT-4o May 2024 90.2%
- 19
DeepSeek-V2.5 Sep 2024 90.2%
- 20 Mercury Coder Small 90%
- 21 Granite 3.3 8B Instruct 89.7%
- 22 Granite 3.2 8B Instruct 89.3%
- 23
Llama 3.1-405B 89%
- 24
Gemini 1.5 Pro Sep 2024 89%
- 25
Mistral Small 3.1 88.4%
- 26 Granite 4.1 30B 88.4%
- 27 GPT-4 Mar 2023 88.4%
- 28 GPT-4o mini 88.4%
- 29 Grok-2 Aug 2024 88.4%
- 30
Llama 3.3 70B Instruct 88.4%
- 31
Qwen2.5-32B 88.4%
- 32
Qwen2.5-14B-Instruct-1M 88.4%
- 33 Claude 3.5 Haiku 88.1%
- 34 Sarvam-M 88%
- 35 Granite 4.0 H Small 88%
- 36
Qwen2.5-VL-72B 87.8%
- 37
Gemma 3 27B 87.8%
- 38 Beam 1.0 Base 87.3%
- 39
Falcon-H1-34B 87.2%
- 40
MiniMax-Text-01 86.9%
- 41
Qwen2.5-72B 86.6%
- 42
Qwen-Turbo 86.6%
- 43
Codestral 86.6%
- 44
Qwen2-72B 86%
- 45 GPT-4 Turbo Nov 2023 85.4%
- 46
DeepSeek-Coder-V2 236B 85.4%
- 47
Gemma 3 12B 85.4%
- 48
Cohere Command A 85.4%
- 49 Mercury 85%
- 50 Claude 3 Opus 84.9%
- 51
Qwen2.5-7B 84.8%
- 52
Mistral Small 3 84.8%
- 53
Seed-Coder-8B-Instruct 84.8%
- 54
Gemini 1.5 Pro May 2024 84.1%
- 55
Nemotron 3 Ultra 550B-A55B Base 83.8%
- 56
Qwen2.5-14B 83.5%
- 57
Seed Diffusion Preview 82.8%
- 58
Phi-4 82.6%
- 59
Gemini 1.5 Flash Sep 2024 82.3%
- 60
InternLM3-8B-Instruct 82.3%
- 61
Llama 3-70B 81.7%
- 62
Nemotron 3.5 Super 120B-A12B Base 81.3%
- 63
DeepSeek-V2 (MoE-236B, May 2024) 81.1%
- 64
Llama 3.1-70B 80.5%
- 65
DeepSeek V4.1 Flash 79.4%
- 66
DeepSeek-V4.1-Flash Base 79.4%
- 67
Qwen2.5-Omni-7B 78.7%
- 68
Nemotron 3 Nano 30B-A3B Base 78%
- 69
Nemotron 3.5 Lightning 30B-A3B Base 76.9%
- 70 GPT-3.5 Turbo Nov 2023 76.8%
- 71 Claude 3 Haiku 76.8%
- 72
DeepSeek-V4-Pro 76.8%
- 73
Mixtral 8x22B 76.2%
- 74
DBRX 75%
- 75
Gemma 3n E4B 75%
- 76
Gemini 1.0 Ultra 74.4%
- 77
Phi-4 Mini 74.4%
- 78 Grok-1.5 74.1%
- 79 granite-4.0-1b 74%
- 80
DeepSeek LLM 67B 73.8%
- 81 GPT-3.5 Turbo (Mar 2023) 73.2%
- 82 Claude 3 Sonnet 73%
- 83
Apertus 70B 73%
- 84
Llama 3.1-8B 72.6%
- 85 GLM-4 72%
- 86
Code Llama 70B Instruct 72%
- 87
Gemini 1.5 Pro Feb 2024 71.9%
- 88
Gemma 3 4B 71.3%
- 89 Claude 2 71.2%
- 90
Phi-3.5-MoE 70.7%
- 91
Mistral Large 69.5%
- 92
Qwen1.5-72B 68.3%
- 93
phi-3-mini 3.8B 64.6%
- 94
Gemini 1.0 Pro 63.4%
- 95 Grok-1 63.2%
- 96
Llama 3-8B 62.2%
- 97
phi-3-medium 14B 62.2%
- 98
Phi-3.5-mini 61.5%
- 99
phi-3-small 7.4B 61%
- 100 ChatGLM3-6B 58.5%
- 101 Claude Instant 57.3%
- 102 CodeQwen1.5-7B 51.8%
- 103
Gemma 2 27B 51.8%
- 104
Phi-2 49.4%
- 105 Moonlight-16B-A3B 48.1%
- 106
StarCoder 2 15B 46.3%
- 107
Mixtral 8x7B 45.1%
- 108
Qwen-14B 43.9%
- 109
SOLAR-10.7B-Instruct-v1.0 43.3%
- 110
Gemma 1.1 7B IT 42.7%
- 111
Mistral-7B-Instruct-v0.2 42.1%
- 112
Gemma 3 1B 41.5%
- 113
Gemma 2 9B 40.2%
- 114
Qwen-7B 37.2%
- 115
StarCoder 2 7B 35.4%
- 116
Gemma 7B 35.4%
- 117
StarCoder 2 3B 31.7%
- 118
Mistral 7B v0.1 30.5%
- 119
Llama 2-70B 29.9%
- 120
Gemma 2B 25%
- 121
Llama 2-34B 22.6%
- 122
Gemma 1.1 2B IT 22.6%
- 123
Llama 2-13B 18.3%
- 124 Qwen-1_8B 14.6%
- 125
Llama 2-7B 12.8%
- 126 GPT-J-6B 12.2%
- 127 GPT-Neo-2.7B 7.90%
Sources: Labs’ model cards and EvalPlus’s leaderboard
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | | 98.8% | Jul 2025 | Lab model card | |
| 2 | | 98.2% | Aug 2025 | Lab model card | |
| 3 | Reka Flash 3 | 96.3% | Mar 2025 | Lab model card | |
| 4 | | 95.9% | Jan 2025 | Lab model card | |
| 5 | | 94.5% | Jul 2026 | Lab model card | |
| 6 | Claude 3.5 Sonnet (October 2024) | 93.7% | Oct 2024 | Lab model card | |
| 7 | | 92.1% | May 2025 | Lab model card | |
| 8 | Sarvam 30B | 92.1% | Mar 2026 | Lab model card | |
| 9 | Claude 3.5 Sonnet | 92% | Jun 2024 | Lab model card | |
| 10 | | 92% | Jul 2024 | Lab model card | |
| 11 | | 91% | Feb 2025 | Lab model card | |
| 12 | GPT-4o May 2024 | 90.2% | May 2024 | Lab model card | |
| 13 | Mercury Coder Small | 90% | Feb 2025 | Lab model card | |
| 14 | Granite 3.3 8B Instruct | 89.7% | Apr 2025 | Lab model card | |
| 15 | Granite 3.2 8B Instruct | 89.3% | Feb 2025 | Lab model card | |
| 16 | | 89% | Jul 2024 | Lab model card | |
| 17 | | 89% | Sep 2024 | Lab model card | |
| 18 | | 88.4% | Mar 2025 | Lab model card | |
| 19 | Granite 4.1 30B | 88.4% | Apr 2026 | Lab model card | |
| 20 | Grok-2 Aug 2024 | 88.4% | Aug 2024 | Lab model card | |
| 21 | | 88.4% | Dec 2024 | Lab model card | |
| 22 | | 88.4% | Dec 2024 | Lab model card | |
| 23 | | 88.4% | Jan 2025 | Lab model card | |
| 24 | GPT-4 Turbo Apr 2024 | 88.2% | Apr 2024 | Lab model card | |
| 25 | Claude 3.5 Haiku | 88.1% | Oct 2024 | Lab model card | |
| 26 | Sarvam-M | 88% | May 2025 | Lab model card | |
| 27 | Granite 4.0 H Small | 88% | Oct 2025 | Lab model card | |
| 28 | | 87.8% | Feb 2025 | Lab model card | |
| 29 | | 87.8% | Mar 2025 | Lab model card | |
| 30 | Beam 1.0 Base | 87.3% | Oct 2026 | Lab model card | |
| 31 | GPT-4o mini | 87.2% | Jul 2024 | Lab model card | |
| 32 | | 87.2% | May 2025 | Lab model card | |
| 33 | | 86.9% | Jan 2025 | Lab model card | |
| 34 | | 86.6% | Sep 2024 | Lab model card | |
| 35 | | 86.6% | Dec 2024 | Lab model card | |
| 36 | | 86.6% | Jan 2025 | Lab model card | |
| 37 | | 86% | Jun 2024 | Lab model card | |
| 38 | | 85.4% | Mar 2025 | Lab model card | |
| 39 | | 85.4% | Apr 2025 | Lab model card | |
| 40 | Mercury | 85% | Jun 2025 | Lab model card | |
| 41 | Claude 3 Opus | 84.9% | Mar 2024 | Lab model card | |
| 42 | | 84.8% | Dec 2024 | Lab model card | |
| 43 | | 84.8% | Jan 2025 | Lab model card | |
| 44 | | 84.8% | May 2025 | Lab model card | |
| 45 | | 84.1% | May 2024 | Lab model card | |
| 46 | | 83.8% | Jun 2026 | Lab model card | |
| 47 | | 83.5% | Dec 2024 | Lab model card | |
| 48 | | 82.8% | Jul 2025 | Lab model card | |
| 49 | | 82.6% | Dec 2024 | Lab model card | |
| 50 | | 82.3% | Jan 2025 | Lab model card | |
| 51 | | 81.7% | Apr 2024 | Lab model card | |
| 52 | | 81.3% | Oct 2026 | Lab model card | |
| 53 | | 81.1% | May 2024 | Lab model card | |
| 54 | | 80.5% | Jul 2024 | Lab model card | |
| 55 | | 79.4% | Sep 2026 | Lab model card | |
| 56 | | 79.4% | Sep 2026 | Lab model card | |
| 57 | | 78.7% | Mar 2025 | Lab model card | |
| 58 | | 78% | Dec 2025 | Lab model card | |
| 59 | | 76.9% | Oct 2026 | Lab model card | |
| 60 | | 76.8% | Apr 2026 | Lab model card | |
| 61 | Claude 3 Haiku | 75.9% | Mar 2024 | Lab model card | |
| 62 | | 75% | Jun 2025 | Lab model card | |
| 63 | | 74.4% | Dec 2023 | Lab model card | |
| 64 | | 74.4% | Mar 2025 | Lab model card | |
| 65 | Grok-1.5 | 74.1% | Mar 2024 | Lab model card | |
| 66 | granite-4.0-1b | 74% | Oct 2025 | Lab model card | |
| 67 | | 73.8% | Nov 2023 | Lab model card | |
| 68 | Claude 3 Sonnet | 73% | Mar 2024 | Lab model card | |
| 69 | | 73% | Sep 2025 | Lab model card | |
| 70 | | 72.6% | Jul 2024 | Lab model card | |
| 71 | GLM-4 | 72% | Jan 2024 | Lab model card | |
| 72 | | 71.9% | Feb 2024 | Lab model card | |
| 73 | | 71.3% | Mar 2025 | Lab model card | |
| 74 | Claude 2 | 71.2% | Jul 2023 | Lab model card | |
| 75 | | 70.7% | Aug 2024 | Lab model card | |
| 76 | GPT-4 Mar 2023 | 67% | Mar 2023 | Lab model card | |
| 77 | | 65.2% | Dec 2024 | Lab model card | |
| 78 | Grok-1 | 63.2% | Nov 2023 | Lab model card | |
| 79 | | 62.2% | Apr 2024 | Lab model card | |
| 80 | | 62.2% | Aug 2024 | Lab model card | |
| 81 | | 61.5% | Aug 2024 | Lab model card | |
| 82 | | 61% | Aug 2024 | Lab model card | |
| 83 | ChatGLM3-6B | 58.5% | Jun 2024 | Lab model card | |
| 84 | | 58.5% | Aug 2024 | Lab model card | |
| 85 | | 51.8% | Jun 2024 | Lab model card | |
| 86 | Moonlight-16B-A3B | 48.1% | Feb 2025 | Lab model card | |
| 87 | | 45.1% | Feb 2024 | Lab model card | |
| 88 | | 43.9% | Sep 2023 | Lab model card | |
| 89 | | 41.5% | Feb 2024 | Lab model card | |
| 90 | | 41.5% | Mar 2025 | Lab model card | |
| 91 | | 40.2% | Dec 2023 | Lab model card | |
| 92 | | 40.2% | Jul 2024 | Lab model card | |
| 93 | | 37.2% | Sep 2023 | Lab model card | |
| 94 | | 32.3% | Feb 2024 | Lab model card | |
| 95 | | 30.5% | Sep 2023 | Lab model card | |
| 96 | | 29.9% | Jul 2023 | Lab model card | |
| 97 | | 22.6% | Jul 2023 | Lab model card | |
| 98 | | 22% | Mar 2024 | Lab model card | |
| 99 | | 18.3% | Jul 2023 | Lab model card | |
| 100 | Qwen-1_8B | 14.6% | Sep 2023 | Lab model card | |
| 101 | | 12.8% | Jul 2023 | Lab model card |
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | o1-mini | 96.3% | Sep 2024 | Official leaderboard | |
| 2 | o1-preview | 96.3% | Sep 2024 | Official leaderboard | |
| 3 | GPT-4o Aug 2024 | 92.7% | Aug 2024 | Official leaderboard | |
| 4 | | 92.1% | Nov 2024 | Official leaderboard | |
| 5 | | 91.5% | Dec 2024 | Official leaderboard | |
| 6 | GPT-4 Turbo Apr 2024 | 90.2% | Apr 2024 | Official leaderboard | |
| 7 | | 90.2% | Sep 2024 | Official leaderboard | |
| 8 | | 89% | Sep 2024 | Official leaderboard | |
| 9 | GPT-4 Mar 2023 | 88.4% | Mar 2023 | Official leaderboard | |
| 10 | GPT-4o mini | 88.4% | Jul 2024 | Official leaderboard | |
| 11 | Claude 3.5 Sonnet | 87.2% | Jun 2024 | Official leaderboard | |
| 12 | GPT-4 Turbo Nov 2023 | 85.4% | Nov 2023 | Official leaderboard | |
| 13 | | 85.4% | Jun 2024 | Official leaderboard | |
| 14 | Claude 3 Opus | 82.9% | Feb 2024 | Official leaderboard | |
| 15 | | 82.3% | Aug 2024 | Official leaderboard | |
| 16 | | 77.4% | Apr 2024 | Official leaderboard | |
| 17 | GPT-3.5 Turbo Nov 2023 | 76.8% | Nov 2023 | Official leaderboard | |
| 18 | Claude 3 Haiku | 76.8% | Mar 2024 | Official leaderboard | |
| 19 | | 76.2% | Apr 2024 | Official leaderboard | |
| 20 | | 75% | Mar 2024 | Official leaderboard | |
| 21 | GPT-3.5 Turbo (Mar 2023) | 73.2% | Mar 2023 | Official leaderboard | |
| 22 | | 72% | Jan 2024 | Official leaderboard | |
| 23 | Claude 3 Sonnet | 70.7% | Feb 2024 | Official leaderboard | |
| 24 | Claude 2 | 69.5% | Jul 2023 | Official leaderboard | |
| 25 | | 69.5% | Feb 2024 | Official leaderboard | |
| 26 | | 69.5% | Jul 2024 | Official leaderboard | |
| 27 | | 68.3% | Feb 2024 | Official leaderboard | |
| 28 | | 64.6% | Apr 2024 | Official leaderboard | |
| 29 | | 63.4% | Dec 2023 | Official leaderboard | |
| 30 | | 61.6% | Apr 2024 | Official leaderboard | |
| 31 | Claude Instant | 57.3% | Aug 2023 | Official leaderboard | |
| 32 | CodeQwen1.5-7B | 51.8% | Apr 2024 | Official leaderboard | |
| 33 | | 49.4% | Dec 2023 | Official leaderboard | |
| 34 | | 46.3% | Feb 2024 | Official leaderboard | |
| 35 | | 45.1% | Dec 2023 | Official leaderboard | |
| 36 | | 43.3% | Dec 2023 | Official leaderboard | |
| 37 | | 42.7% | Apr 2024 | Official leaderboard | |
| 38 | | 42.1% | Dec 2023 | Official leaderboard | |
| 39 | | 35.4% | Feb 2024 | Official leaderboard | |
| 40 | | 35.4% | Feb 2024 | Official leaderboard | |
| 41 | | 31.7% | Feb 2024 | Official leaderboard | |
| 42 | | 28.7% | Sep 2023 | Official leaderboard | |
| 43 | | 25% | Feb 2024 | Official leaderboard | |
| 44 | | 22.6% | Apr 2024 | Official leaderboard | |
| 45 | GPT-J-6B | 12.2% | Aug 2021 | Official leaderboard | |
| 46 | GPT-Neo-2.7B | 7.90% | Mar 2021 | Official leaderboard |
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | | 98.8% | Jul 2025 | Lab model card | |
| 2 | | 98.2% | Aug 2025 | Lab model card | |
| 3 | o1-mini | 96.3% | Sep 2024 | Official leaderboard | |
| 4 | o1-preview | 96.3% | Sep 2024 | Official leaderboard | |
| 5 | Reka Flash 3 | 96.3% | Mar 2025 | Lab model card | |
| 6 | | 95.9% | Jan 2025 | Lab model card | |
| 7 | | 94.5% | Jul 2026 | Lab model card | |
| 8 | Claude 3.5 Sonnet (October 2024) | 93.7% | Oct 2024 | Lab model card | |
| 9 | GPT-4o Aug 2024 | 92.7% | Aug 2024 | Official leaderboard | |
| 10 | | 92.1% | Nov 2024 | Official leaderboard | |
| 11 | | 92.1% | May 2025 | Lab model card | |
| 12 | Sarvam 30B | 92.1% | Mar 2026 | Lab model card | |
| 13 | Claude 3.5 Sonnet | 92% | Jun 2024 | Lab model card | |
| 14 | | 92% | Jul 2024 | Lab model card | |
| 15 | | 91.5% | Dec 2024 | Official leaderboard | |
| 16 | | 91% | Feb 2025 | Lab model card | |
| 17 | GPT-4 Turbo Apr 2024 | 90.2% | Apr 2024 | Official leaderboard | |
| 18 | GPT-4o May 2024 | 90.2% | May 2024 | Lab model card | |
| 19 | | 90.2% | Sep 2024 | Official leaderboard | |
| 20 | Mercury Coder Small | 90% | Feb 2025 | Lab model card | |
| 21 | Granite 3.3 8B Instruct | 89.7% | Apr 2025 | Lab model card | |
| 22 | Granite 3.2 8B Instruct | 89.3% | Feb 2025 | Lab model card | |
| 23 | | 89% | Jul 2024 | Lab model card | |
| 24 | | 89% | Sep 2024 | Official leaderboard | |
| 25 | | 88.4% | Mar 2025 | Lab model card | |
| 26 | Granite 4.1 30B | 88.4% | Apr 2026 | Lab model card | |
| 27 | GPT-4 Mar 2023 | 88.4% | Mar 2023 | Official leaderboard | |
| 28 | GPT-4o mini | 88.4% | Jul 2024 | Official leaderboard | |
| 29 | Grok-2 Aug 2024 | 88.4% | Aug 2024 | Lab model card | |
| 30 | | 88.4% | Dec 2024 | Lab model card | |
| 31 | | 88.4% | Dec 2024 | Lab model card | |
| 32 | | 88.4% | Jan 2025 | Lab model card | |
| 33 | Claude 3.5 Haiku | 88.1% | Oct 2024 | Lab model card | |
| 34 | Sarvam-M | 88% | May 2025 | Lab model card | |
| 35 | Granite 4.0 H Small | 88% | Oct 2025 | Lab model card | |
| 36 | | 87.8% | Feb 2025 | Lab model card | |
| 37 | | 87.8% | Mar 2025 | Lab model card | |
| 38 | Beam 1.0 Base | 87.3% | Oct 2026 | Lab model card | |
| 39 | | 87.2% | May 2025 | Lab model card | |
| 40 | | 86.9% | Jan 2025 | Lab model card | |
| 41 | | 86.6% | Sep 2024 | Lab model card | |
| 42 | | 86.6% | Dec 2024 | Lab model card | |
| 43 | | 86.6% | Jan 2025 | Lab model card | |
| 44 | | 86% | Jun 2024 | Lab model card | |
| 45 | GPT-4 Turbo Nov 2023 | 85.4% | Nov 2023 | Official leaderboard | |
| 46 | | 85.4% | Jun 2024 | Official leaderboard | |
| 47 | | 85.4% | Mar 2025 | Lab model card | |
| 48 | | 85.4% | Apr 2025 | Lab model card | |
| 49 | Mercury | 85% | Jun 2025 | Lab model card | |
| 50 | Claude 3 Opus | 84.9% | Mar 2024 | Lab model card | |
| 51 | | 84.8% | Dec 2024 | Lab model card | |
| 52 | | 84.8% | Jan 2025 | Lab model card | |
| 53 | | 84.8% | May 2025 | Lab model card | |
| 54 | | 84.1% | May 2024 | Lab model card | |
| 55 | | 83.8% | Jun 2026 | Lab model card | |
| 56 | | 83.5% | Dec 2024 | Lab model card | |
| 57 | | 82.8% | Jul 2025 | Lab model card | |
| 58 | | 82.6% | Dec 2024 | Lab model card | |
| 59 | | 82.3% | Aug 2024 | Official leaderboard | |
| 60 | | 82.3% | Jan 2025 | Lab model card | |
| 61 | | 81.7% | Apr 2024 | Lab model card | |
| 62 | | 81.3% | Oct 2026 | Lab model card | |
| 63 | | 81.1% | May 2024 | Lab model card | |
| 64 | | 80.5% | Jul 2024 | Lab model card | |
| 65 | | 79.4% | Sep 2026 | Lab model card | |
| 66 | | 79.4% | Sep 2026 | Lab model card | |
| 67 | | 78.7% | Mar 2025 | Lab model card | |
| 68 | | 78% | Dec 2025 | Lab model card | |
| 69 | | 76.9% | Oct 2026 | Lab model card | |
| 70 | GPT-3.5 Turbo Nov 2023 | 76.8% | Nov 2023 | Official leaderboard | |
| 71 | Claude 3 Haiku | 76.8% | Mar 2024 | Official leaderboard | |
| 72 | | 76.8% | Apr 2026 | Lab model card | |
| 73 | | 76.2% | Apr 2024 | Official leaderboard | |
| 74 | | 75% | Mar 2024 | Official leaderboard | |
| 75 | | 75% | Jun 2025 | Lab model card | |
| 76 | | 74.4% | Dec 2023 | Lab model card | |
| 77 | | 74.4% | Mar 2025 | Lab model card | |
| 78 | Grok-1.5 | 74.1% | Mar 2024 | Lab model card | |
| 79 | granite-4.0-1b | 74% | Oct 2025 | Lab model card | |
| 80 | | 73.8% | Nov 2023 | Lab model card | |
| 81 | GPT-3.5 Turbo (Mar 2023) | 73.2% | Mar 2023 | Official leaderboard | |
| 82 | Claude 3 Sonnet | 73% | Mar 2024 | Lab model card | |
| 83 | | 73% | Sep 2025 | Lab model card | |
| 84 | | 72.6% | Jul 2024 | Lab model card | |
| 85 | GLM-4 | 72% | Jan 2024 | Lab model card | |
| 86 | | 72% | Jan 2024 | Official leaderboard | |
| 87 | | 71.9% | Feb 2024 | Lab model card | |
| 88 | | 71.3% | Mar 2025 | Lab model card | |
| 89 | Claude 2 | 71.2% | Jul 2023 | Lab model card | |
| 90 | | 70.7% | Aug 2024 | Lab model card | |
| 91 | | 69.5% | Feb 2024 | Official leaderboard | |
| 92 | | 68.3% | Feb 2024 | Official leaderboard | |
| 93 | | 64.6% | Apr 2024 | Official leaderboard | |
| 94 | | 63.4% | Dec 2023 | Official leaderboard | |
| 95 | Grok-1 | 63.2% | Nov 2023 | Lab model card | |
| 96 | | 62.2% | Apr 2024 | Lab model card | |
| 97 | | 62.2% | Aug 2024 | Lab model card | |
| 98 | | 61.5% | Aug 2024 | Lab model card | |
| 99 | | 61% | Aug 2024 | Lab model card | |
| 100 | ChatGLM3-6B | 58.5% | Jun 2024 | Lab model card | |
| 101 | Claude Instant | 57.3% | Aug 2023 | Official leaderboard | |
| 102 | CodeQwen1.5-7B | 51.8% | Apr 2024 | Official leaderboard | |
| 103 | | 51.8% | Jun 2024 | Lab model card | |
| 104 | | 49.4% | Dec 2023 | Official leaderboard | |
| 105 | Moonlight-16B-A3B | 48.1% | Feb 2025 | Lab model card | |
| 106 | | 46.3% | Feb 2024 | Official leaderboard | |
| 107 | | 45.1% | Dec 2023 | Official leaderboard | |
| 108 | | 43.9% | Sep 2023 | Lab model card | |
| 109 | | 43.3% | Dec 2023 | Official leaderboard | |
| 110 | | 42.7% | Apr 2024 | Official leaderboard | |
| 111 | | 42.1% | Dec 2023 | Official leaderboard | |
| 112 | | 41.5% | Mar 2025 | Lab model card | |
| 113 | | 40.2% | Jul 2024 | Lab model card | |
| 114 | | 37.2% | Sep 2023 | Lab model card | |
| 115 | | 35.4% | Feb 2024 | Official leaderboard | |
| 116 | | 35.4% | Feb 2024 | Official leaderboard | |
| 117 | | 31.7% | Feb 2024 | Official leaderboard | |
| 118 | | 30.5% | Sep 2023 | Lab model card | |
| 119 | | 29.9% | Jul 2023 | Lab model card | |
| 120 | | 25% | Feb 2024 | Official leaderboard | |
| 121 | | 22.6% | Jul 2023 | Lab model card | |
| 122 | | 22.6% | Apr 2024 | Official leaderboard | |
| 123 | | 18.3% | Jul 2023 | Lab model card | |
| 124 | Qwen-1_8B | 14.6% | Sep 2023 | Lab model card | |
| 125 | | 12.8% | Jul 2023 | Lab model card | |
| 126 | GPT-J-6B | 12.2% | Aug 2021 | Official leaderboard | |
| 127 | GPT-Neo-2.7B | 7.90% | Mar 2021 | Official leaderboard |
EvalPlus’s leaderboard has 125 entries, 46 of them models we track. Switch the scores above to rank them together.
12 models have held number one in labs’ own numbers since 2023 6 models have held number one across all independent runs since 2023 8 models have held number one with claims included since 2023
Lab claims count from the day the card came out, independent runs from the model’s release. We draw one row each for EvalPlus’s leaderboard and what labs claim in their cards.
Sources: EvalPlus’s leaderboard and labs’ model cards
GPT-4 on the official leaderboard passed 85% in March 2023
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Sources: EvalPlus’s leaderboard and labs’ model cards
Labs headline it less often now, last in September 2026
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 |
|---|---|---|---|
| Sep 10, 2026 | 79.4 | HumanEval (Pass@1) | |
| Apr 29, 2026 | Granite 4.1 30B | 88.4 | HumanEval (pass@1) |
| Apr 24, 2026 | 76.8 | HumanEval (Pass@1) | |
| Mar 6, 2026 | Sarvam 30B | 92.1 | Humaneval |
| Oct 28, 2025 | granite-4.0-1b | 74 | HumanEval (pass@1) |
| Oct 2, 2025 | Granite 4.0 H Small | 88 | HumanEval (pass@1) |
| Jul 31, 2025 | 82.8 | Human Eval (Figure 1) | |
| Jul 10, 2025 | 98.8 | HumanEval (0-shot) | |
| Jun 26, 2025 | 75 | HumanEval pass@1 0-shot (IT) | |
| Jun 26, 2025 | Mercury | 85 | HumanEval (% accuracy) |
| May 23, 2025 | Sarvam-M | 88 | HumanEval (0.88) |
| May 20, 2025 | 87.2 | HumanEval | |
| May 8, 2025 | 84.8 | HumanEval | |
| May 7, 2025 | 92.1 | HumanEval 0-shot | |
| Apr 16, 2025 | Granite 3.3 8B Instruct | 89.7 | HumanEval |
| Mar 27, 2025 | 78.7 | HumanEval | |
| Mar 17, 2025 | 88.4 | HumanEval | |
| Mar 12, 2025 | 87.8 | HumanEval 0-shot (IT); PT = 48.8 | |
| Mar 10, 2025 | Reka Flash 3 | 96.3 | HumanEval |
| Feb 27, 2025 | 91 | HumanEval | |
| Feb 26, 2025 | Granite 3.2 8B Instruct | 89.3 | HumanEval |
| Feb 26, 2025 | Mercury Coder Small | 90 | HumanEval |
| Feb 22, 2025 | Moonlight-16B-A3B | 48.1 | HumanEval |
| Jan 30, 2025 | 95.9 | HumanEval (pass@10) | |
| Jan 30, 2025 | 84.8 | humaneval_instruct_pass@1 | |
| Jan 28, 2025 | HumanEval | ||
| Jan 15, 2025 | 86.9 | HumanEval | |
| Jan 13, 2025 | 86.6 | HumanEval (Python) | |
| Jan 13, 2025 | 82.3 | HumanEval(Pass@1) | |
| Dec 26, 2024 | 65.2 | HumanEval (Pass@1) | |
| Dec 12, 2024 | 82.6 | HumanEval (simple-evals) | |
| Dec 6, 2024 | 88.4 | HumanEval, 0-shot, pass@1 | |
| Oct 22, 2024 | Claude 3.5 Sonnet (October 2024) | 93.7 | HumanEval (0-shot) |
| Sep 19, 2024 | 86.6 | Best of HumanEval / HumanEval+ | |
| Sep 5, 2024 | 89 | HumanEval python | |
| Aug 20, 2024 | 70.7 | HumanEval (0-shot) | |
| Aug 13, 2024 | Grok-2 | 88.4 | HumanEval (pass@1) |
| Jul 24, 2024 | 92 | Best of Human Eval / Human Eval Plus | |
| Jul 23, 2024 | 89 | HumanEval (0-shot) | |
| Jul 18, 2024 | GPT-4o mini | 87.2 | HumanEval |
| Jun 27, 2024 | 51.8 | HumanEval (pass@1) | |
| Jun 20, 2024 | Claude 3.5 Sonnet | 92 | HumanEval (0-shot) |
| Jun 7, 2024 | 86 | HumanEval | |
| May 14, 2024 | 84.1 | HumanEval chat preamble, 0-shot | |
| May 13, 2024 | GPT-4o | 90.2 | HumanEval (0-shot) |
| May 7, 2024 | 81.1 | HumanEval | |
| Apr 22, 2024 | 55.5 | HumanEval (0-Shot) | |
| Apr 18, 2024 | 81.7 | HumanEval (0-shot) [instruct] | |
| Apr 11, 2024 | GPT-4 Turbo | 88.2 | HumanEval% |
| Mar 28, 2024 | Grok-1.5 | 74.1 | HumanEval (0-shot, pass@1) |
| Mar 4, 2024 | Claude 3 Opus | 84.9 | HumanEval (0-shot) |
| Feb 26, 2024 | 45.1 | HumanE (pass@1) | |
| Feb 21, 2024 | 32.3 | HumanEval (pass@1) | |
| Feb 15, 2024 | 71.9 | HumanEval chat preamble, 0-shot | |
| Feb 5, 2024 | 41.5 | HumanEval | |
| Jan 16, 2024 | GLM-4 | 72 | HumanEval (0-shot) |
| Dec 12, 2023 | HumanEval (in Coding average only) | ||
| Dec 11, 2023 | 40.2 | HumanE [detailed table] | |
| Dec 6, 2023 | 74.4 | HumanEval, 0-shot (IT) | |
| Nov 29, 2023 | 73.8 | HumanEval | |
| Nov 3, 2023 | Grok-1 | 63.2 | HumanEval (0-shot) |
| Sep 27, 2023 | 30.5 | HumanEval | |
| Sep 25, 2023 | 43.9 | HumanEval (0-shot Pass@1) | |
| Jul 11, 2023 | Claude 2 | 71.2 | Codex P@1 (0-shot) |
| Mar 14, 2023 | GPT-4 | 67 | HumanEval (0-shot) |
70 system cards report it, from 19 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 15, 2026 | | 81.3 | HumanEval, sampled pass@1, n=32, EvalPlus sanitized, Table 6 | Capabilities |
| Oct 15, 2026 | | 76.9 | HumanEval, sampled pass@1, n=32, EvalPlus sanitized, Table 6 | Capabilities |
| Oct 5, 2026 | Beam 1.0 Base technical report | 87.3 | HumanEval+, 0-shot temperature 0.7, Table 23 | Capabilities |
| Sep 10, 2026 | | 79.4 | HumanEval, pass@1, 0-shot | Capabilities |
| Jul 31, 2026 | | 94.5 | HumanEval, TD, 92.7 no-think (Table 3) | Capabilities |
| Jun 4, 2026 | | 83.8 | HumanEval, sampled pass@1 n=32, EvalPlus sanitized | Capabilities |
| Dec 23, 2025 | | 78 | HumanEval, 0-shot, base model Table 2 | Capabilities |
| Sep 17, 2025 | | 73 | HumanEval (Pass@10) (Table 18) | Capabilities |
| Aug 25, 2025 | | 98.2 | HumanEval, OpenCompass (Table 14) | Capabilities |
| Aug 4, 2025 | | 82.8 | Human Eval (Figure 1) | Capabilities |
| Jul 30, 2025 | | 87.2 | HumanEval pass@1 (Table 24) | Capabilities |
| Jun 17, 2025 | Mercury Coder Small technical report | 90 | HumanEval, pass@1, marked as reported by Artificial Analysis (Table 1) | Capabilities |
| Jun 4, 2025 | | 84.8 | HumanEval (HE), EvalPlus (Table 7) | Capabilities |
| Apr 1, 2025 | | 85.4 | HumanEval Python pass@1 (Table 26) | Capabilities |
| Mar 26, 2025 | | 78.7 | HumanEval (Table 1) | Capabilities |
| Mar 25, 2025 | | 71.3 | HumanEval, IT, 0-shot pass@1 (Table 18) | Capabilities |
| Mar 25, 2025 | | 87.8 | HumanEval, IT, 0-shot pass@1 (Table 18) | Capabilities |
| Mar 25, 2025 | | 41.5 | HumanEval, IT, 0-shot pass@1 (Table 18) | Capabilities |
| Mar 25, 2025 | | 85.4 | HumanEval, IT, 0-shot pass@1 (Table 18) | Capabilities |
| Mar 3, 2025 | | 74.4 | HumanEval (0-Shot) (Tables 7 and 8) | Capabilities |
| Feb 19, 2025 | | 87.8 | HumanEval (Table 4) | Capabilities |
| Jan 26, 2025 | | 88.4 | HumanEval (Table 6) | Capabilities |
| Jan 14, 2025 | | 86.9 | HumanEval (Table 8) | Capabilities |
| Dec 19, 2024 | | 84.8 | HumanEval, Qwen2.5-7B-Instruct (Table 8) | Capabilities |
| Dec 19, 2024 | | 86.6 | HumanEval, Qwen2.5-72B-Instruct (Table 6) | Capabilities |
| Dec 19, 2024 | | 88.4 | HumanEval, Qwen2.5-32B-Instruct (Table 7) | Capabilities |
| Dec 19, 2024 | | 83.5 | HumanEval, Qwen2.5-14B-Instruct (Table 7) | Capabilities |
| Dec 19, 2024 | | 86.6 | HumanEval, Qwen2.5-Turbo (Table 7) | Capabilities |
| Dec 12, 2024 | | 82.6 | HumanEval, simple-evals (Table 1) | Capabilities |
| Dec 6, 2024 | | 88.4 | HumanEval, 0-shot, pass@1 (Instruction tuned models table) | Capabilities |
| Nov 23, 2024 | | 72.6 | HumanEval (0-shot), post-trained (Table 2) | Capabilities |
| Nov 23, 2024 | | 80.5 | HumanEval (0-shot), post-trained (Table 2) | Capabilities |
| Nov 23, 2024 | | 89 | HumanEval (0-shot), post-trained (Table 2) | Capabilities |
| Nov 22, 2024 | | 95.9 | HumanEval (pass@10), RLVR (Table 4) | Capabilities |
| Oct 22, 2024 | Claude 3.5 Sonnet (October 2024) model card | 93.7 | HumanEval, 0-shot (Table 7) | Capabilities |
| Oct 22, 2024 | Claude 3.5 Haiku model card | 88.1 | HumanEval, 0-shot (Table 8) | Capabilities |
| Aug 30, 2024 | | 61 | HumanEval (0-Shot) (Section 3 table) | Capabilities |
| Aug 30, 2024 | | 58.5 | HumanEval (0-Shot) (Section 3 table) | Capabilities |
| Aug 30, 2024 | | 62.2 | HumanEval (0-Shot) (Section 3 table) | Capabilities |
| Aug 30, 2024 | | 70.7 | HumanEval (0-shot) (Table 3) | Capabilities |
| Aug 30, 2024 | | 61.5 | HumanEval (0-shot) (Table 3) | Capabilities |
| Jul 31, 2024 | | 40.2 | HumanEval, PT, pass@1 (Table 13) | Capabilities |
| Jul 31, 2024 | | 51.8 | HumanEval, PT, pass@1 (Table 13) | Capabilities |
| Jul 23, 2024 | | 72.6 | HumanEval, 0-shot, pass@1, instruction tuned (Instruction tuned models table) | Capabilities |
| Jul 23, 2024 | | 80.5 | HumanEval, 0-shot, pass@1, instruction tuned (Instruction tuned models table) | Capabilities |
| Jul 23, 2024 | | 89 | HumanEval, 0-shot, pass@1, instruction tuned (Instruction tuned models table) | Capabilities |
| Jul 15, 2024 | | 86 | HumanEval, Qwen2-72B-Instruct (Table 6). 87.0 on the non-contaminated subset (Table 15) | Capabilities |
| Jun 20, 2024 | Claude 3.5 Sonnet model card | 92 | HumanEval, 0-shot (Table 1) | Capabilities |
| Jun 18, 2024 | GLM-4 technical report | 72 | GLM-4 (0116), HumanEval (Table 2) | Capabilities |
| Jun 18, 2024 | ChatGLM3-6B technical report | 58.5 | ChatGLM3-6B-Base, HumanEval (Table 1) | Capabilities |
| May 7, 2024 | | 81.1 | HumanEval 0-shot, DeepSeek-V2 Chat (RL) (Table 3) | Capabilities |
| Apr 18, 2024 | | 62.2 | HumanEval (0-shot), instruction tuned (Instruction tuned models table) | Capabilities |
| Apr 18, 2024 | | 81.7 | HumanEval (0-shot), instruction tuned (Instruction tuned models table) | Capabilities |
| Mar 13, 2024 | | 32.3 | HumanEval, PT, pass@1 (Table 6) | Capabilities |
| Mar 13, 2024 | | 22 | HumanEval, PT, pass@1 (Table 6) | Capabilities |
| Mar 4, 2024 | Claude 3 Sonnet model card | 73 | HumanEval, 0-shot (Table 1) | Capabilities |
| Mar 4, 2024 | Claude 3 Opus model card | 84.9 | HumanEval, 0-shot (Table 1) | Capabilities |
| Mar 4, 2024 | Claude 3 Haiku model card | 75.9 | HumanEval, 0-shot (Table 1) | Capabilities |
| Jan 8, 2024 | | 40.2 | HumanE, 0-shot (Table 2) | Capabilities |
| Jan 5, 2024 | | 73.8 | HumanEval (Python), DeepSeek 67B Chat (Table 6) | Capabilities |
| Oct 10, 2023 | | 30.5 | HumanEval, 0-shot (Table 2) | Capabilities |
| Sep 28, 2023 | | 37.2 | HumanEval 0-shot pass@1 (Table 5, Table 10) | Capabilities |
| Sep 28, 2023 | | 43.9 | HumanEval 0-shot pass@1 (Table 5, Table 10) | Capabilities |
| Sep 28, 2023 | | 14.6 | HumanEval 0-shot pass@1 (Table 5, Table 10) | Capabilities |
| Jul 19, 2023 | | 12.8 | Human-Eval pass@1, 0-shot, pretrained (Table 21). pass@100 = 45.6 | Capabilities |
| Jul 19, 2023 | | 29.9 | Human-Eval pass@1, 0-shot, pretrained (Table 21). pass@100 = 89.0 | Capabilities |
| Jul 19, 2023 | | 22.6 | Human-Eval pass@1, 0-shot, pretrained (Table 21). pass@100 = 77.2 | Capabilities |
| Jul 19, 2023 | | 18.3 | Human-Eval pass@1, 0-shot, pretrained (Table 21). pass@100 = 60.2 | Capabilities |
| Jul 11, 2023 | Claude 2 model card | 71.2 | Codex P@1 (0-shot) (4.3) | Capabilities |
| Mar 14, 2023 | GPT-4 technical report | 67 | HumanEval, 0-shot (Table 2, base model) | Capabilities |
The lab's number comes out ahead in 8 of 20 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 |
|---|---|---|---|
| | 41.5% HumanEval | 68.3% Leaderboard | −27 pts |
| | 65.2% HumanEval (Pass@1) | 91.5% Leaderboard | −26 pts |
| | 45.1% HumanE (pass@1) | 69.5% Leaderboard | −24 pts |
| GPT-4 Mar 2023 | 67% HumanEval (0-shot) | 88.4% Leaderboard | −21 pts |
| | 58.5% HumanEval (0-Shot) (Section 3 table) | 64.6% Leaderboard | −6.1 pts |
| | 40.2% HumanE [detailed table] | 45.1% Leaderboard | −4.9 pts |
| Claude 3.5 Sonnet | 92% HumanEval (0-shot) | 87.2% Leaderboard | +4.8 pts |
| | 81.7% HumanEval (0-shot) [instruct] | 77.4% Leaderboard | +4.3 pts |
| | 32.3% HumanEval (pass@1) | 35.4% Leaderboard | −3.1 pts |
| | 72.6% HumanEval, 0-shot, pass@1, instruction tuned (Instruction tuned models table) | 69.5% Leaderboard | +3.1 pts |
| | 22% HumanEval, PT, pass@1 (Table 6) | 25% Leaderboard | −3.0 pts |
| Claude 3 Sonnet | 73% HumanEval, 0-shot (Table 1) | 70.7% Leaderboard | +2.3 pts |
| Claude 3 Opus | 84.9% HumanEval (0-shot) | 82.9% Leaderboard | +2.0 pts |
| GPT-4 Turbo Apr 2024 | 88.2% HumanEval% | 90.2% Leaderboard | −2.0 pts |
| | 30.5% HumanEval | 28.7% Leaderboard | +1.8 pts |
| Claude 2 | 71.2% Codex P@1 (0-shot) | 69.5% Leaderboard | +1.7 pts |
| GPT-4o mini | 87.2% HumanEval | 88.4% Leaderboard | −1.2 pts |
| | 89% HumanEval python | 90.2% Leaderboard | −1.2 pts |
| Claude 3 Haiku | 75.9% HumanEval, 0-shot (Table 1) | 76.8% Leaderboard | −0.9 pts |
| | 62.2% HumanEval (0-shot), instruction tuned (Instruction tuned models table) | 61.6% Leaderboard | +0.6 pts |
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