Coding
LiveCodeBench leaderboard
As of 2026-10-07, the highest measured score on LiveCodeBench is 91.6% by Qwen3.7 Max. 140 more models have estimated scores, calibrated from the benchmarks they were measured on.
Measured scores: benchlm.ai.
| # | Model | Score | Source |
|---|---|---|---|
| 1 | Apodex 1.1 | 100.0% | estimated ± 8.9 pp, low confidence |
| 2 | Apodex 1.1 Mini | 100.0% | estimated ± 8.9 pp, low confidence |
| 3 | Claude Fable 5 | 100.0% | estimated ± 8.9 pp, low confidence |
| 4 | Claude Fable 5.1 | 100.0% | estimated ± 8.9 pp, low confidence |
| 5 | Claude Opus 4.7 (Adaptive) | 100.0% | estimated ± 8.9 pp, low confidence |
| 6 | Claude Opus 4.8 | 100.0% | estimated ± 8.9 pp, low confidence |
| 7 | Claude Opus 5 | 100.0% | estimated ± 8.9 pp, low confidence |
| 8 | Claude Sonnet 5 | 100.0% | estimated ± 8.9 pp, low confidence |
| 9 | DeepSeek V4 Flash 0731 | 100.0% | estimated ± 8.9 pp, low confidence |
| 10 | DeepSeek V4 Pro 0813 | 100.0% | estimated ± 8.9 pp, low confidence |
| 11 | Gemini 3.1 Pro | 100.0% | estimated ± 8.9 pp, low confidence |
| 12 | Gemini 3.5 Flash | 100.0% | estimated ± 8.9 pp, low confidence |
| 13 | Gemini 3.6 Flash | 100.0% | estimated ± 8.9 pp, low confidence |
| 14 | Gemini 3.7 Flash | 100.0% | estimated ± 8.9 pp, low confidence |
| 15 | Gemini 3.8 Flash | 100.0% | estimated ± 8.9 pp, low confidence |
| 16 | GLM-5.1 | 100.0% | estimated ± 8.9 pp, low confidence |
| 17 | GLM-5.2 | 100.0% | estimated ± 8.9 pp, low confidence |
| 18 | GLM-5.3 | 100.0% | estimated ± 8.9 pp, low confidence |
| 19 | GPT-5.4 | 100.0% | estimated ± 8.9 pp, low confidence |
| 20 | GPT-5.4 mini | 100.0% | estimated ± 8.9 pp, low confidence |
| 21 | GPT-5.4 nano | 100.0% | estimated ± 8.9 pp, low confidence |
| 22 | GPT-5.5 | 100.0% | estimated ± 8.9 pp, low confidence |
| 23 | GPT-5.6 Luna | 100.0% | estimated ± 8.9 pp, low confidence |
| 24 | GPT-5.6 Sol | 100.0% | estimated ± 8.9 pp, low confidence |
| 25 | GPT-5.6 Terra | 100.0% | estimated ± 8.9 pp, low confidence |
| 26 | GPT-6 Astra | 100.0% | estimated ± 8.9 pp, low confidence |
| 27 | Grok 4.5 | 100.0% | estimated ± 8.9 pp, low confidence |
| 28 | Grok 4.6 | 100.0% | estimated ± 8.9 pp, low confidence |
| 29 | Hy3 | 100.0% | estimated ± 8.9 pp, low confidence |
| 30 | Hy3 Preview | 100.0% | estimated ± 8.9 pp, low confidence |
| 31 | Inkling | 100.0% | estimated ± 8.9 pp, low confidence |
| 32 | Inkling-Small | 100.0% | estimated ± 8.9 pp, low confidence |
| 33 | Kimi K2.6 | 100.0% | estimated ± 8.9 pp, low confidence |
| 34 | Kimi K2.7 Code | 100.0% | estimated ± 8.9 pp, low confidence |
| 35 | Kimi K3 | 100.0% | estimated ± 8.9 pp, low confidence |
| 36 | Ling 3.0 Flash | 100.0% | estimated ± 8.9 pp, low confidence |
| 37 | Ling 3.0 Flash FP8 | 100.0% | estimated ± 8.9 pp, low confidence |
| 38 | MiMo-V2.5-Pro | 100.0% | estimated ± 8.9 pp, low confidence |
| 39 | MiniMax M2.7 | 100.0% | estimated ± 8.9 pp, low confidence |
| 40 | MiniMax M3 | 100.0% | estimated ± 8.9 pp, low confidence |
| 41 | Muse Spark | 100.0% | estimated ± 8.9 pp, low confidence |
| 42 | Muse Spark 1.1 | 100.0% | estimated ± 8.9 pp, low confidence |
| 43 | Muse Spark 1.2 | 100.0% | estimated ± 8.9 pp, low confidence |
| 44 | Muse Spark 1.3 | 100.0% | estimated ± 8.9 pp, low confidence |
| 45 | Quasar 438B | 100.0% | estimated ± 8.9 pp, low confidence |
| 46 | Qwen3.6 Plus | 100.0% | estimated ± 8.9 pp, low confidence |
| 47 | Qwen3.8-27B | 100.0% | estimated ± 8.9 pp, low confidence |
| 48 | Qwen3.8-Flash-Next | 100.0% | estimated ± 8.9 pp, low confidence |
| 49 | Qwen3.8 Max Preview | 100.0% | estimated ± 8.9 pp, low confidence |
| 50 | MiMo-V2-Flash | 98.4% | estimated ± 8.9 pp, low confidence |
| 51 | GPT-5.1 | 97.2% | estimated ± 8.9 pp, low confidence |
| 52 | Gemini 3.5 Flash-Lite | 97.1% | estimated ± 8.9 pp, low confidence |
| 53 | Nemotron 3 Ultra | 96.9% | estimated ± 8.9 pp, low confidence |
| 54 | Muse Glimmer 30B | 96.2% | estimated ± 8.9 pp, low confidence |
| 55 | Claude Mythos 5 | 95.3% | estimated ± 10.2 pp, low confidence |
| 56 | Ember-1 | 93.5% | estimated ± 10.2 pp, low confidence |
| 57 | Qwen3.7 Max | 91.6% | measured |
| 58 | Mistral Medium 3.5 128B | 90.8% | estimated ± 8.9 pp, low confidence |
| 59 | Kimi K2.5 | 90.5% | estimated ± 8.9 pp, low confidence |
| 60 | Kimi K2.5 (Reasoning) | 90.5% | estimated ± 8.9 pp, low confidence |
| 61 | Ornith-1.5-397B | 90.1% | estimated ± 10.2 pp, low confidence |
| 62 | Qwen3.7 Plus | 89.6% | measured |
| 63 | GPT-5.3 Codex | 89.5% | estimated ± 10.2 pp, low confidence |
| 64 | Ornith-1.0-397B | 87.9% | estimated ± 10.2 pp, low confidence |
| 65 | Solar Pro 4 | 87.8% | measured |
| 66 | Qwen3.5-122B-A10B | 87.7% | estimated ± 8.9 pp, low confidence |
| 67 | Claude Opus 4.5 | 87.0% | estimated ± 10.2 pp, low confidence |
| 68 | Beam | 87.0% | estimated ± 10.2 pp, low confidence |
| 69 | Claude Opus 4.6 | 87.0% | estimated ± 10.2 pp, low confidence |
| 70 | GPT-5.2 | 86.5% | estimated ± 10.2 pp, low confidence |
| 71 | Claude Sonnet 4.6 | 86.2% | estimated ± 10.2 pp, low confidence |
| 72 | Ornith-1.5-35B-A3B | 85.9% | estimated ± 10.2 pp, low confidence |
| 73 | BTL-4 | 85.5% | estimated ± 10.2 pp, low confidence |
| 74 | dots3-note Preview | 85.5% | estimated ± 10.2 pp, low confidence |
| 75 | MiMo-V2-Pro | 85.2% | estimated ± 10.2 pp, low confidence |
| 76 | GLM-5 | 85.1% | estimated ± 10.2 pp, low confidence |
| 77 | GLM-4.7 | 84.9% | measured |
| 78 | Claude Sonnet 4.5 | 84.7% | estimated ± 10.2 pp, low confidence |
| 79 | Grok 4.20 | 84.4% | estimated ± 10.2 pp, low confidence |
| 80 | Qwen3.5 397B | 84.1% | estimated ± 10.2 pp, low confidence |
| 81 | Qwen3.6-27B | 83.9% | measured |
| 82 | Ornith-1.0-35B | 83.7% | estimated ± 10.2 pp, low confidence |
| 83 | MiMo-V2-Omni | 83.2% | estimated ± 10.2 pp, low confidence |
| 84 | Laguna M.1 | 83.1% | estimated ± 10.2 pp, low confidence |
| 85 | Claude 4.1 Opus | 83.0% | estimated ± 10.2 pp, low confidence |
| 86 | MAI-Thinking-1 | 82.4% | estimated ± 10.2 pp, low confidence |
| 87 | Claude Haiku 4.5 | 82.2% | estimated ± 10.2 pp, low confidence |
| 88 | Gemma 4 31B | 82.1% | estimated ± 8.9 pp, low confidence |
| 89 | Claude 4 Sonnet | 81.8% | estimated ± 10.2 pp, low confidence |
| 90 | MAI-Code-1.1-Flash | 81.8% | estimated ± 10.2 pp, low confidence |
| 91 | Qwen3.5-27B | 81.6% | estimated ± 10.2 pp, low confidence |
| 92 | Laguna XS 2.1 | 80.6% | estimated ± 10.2 pp, low confidence |
| 93 | Grok Code Fast 1 | 80.5% | estimated ± 10.2 pp, low confidence |
| 94 | Ornith-1.5-9B | 80.4% | estimated ± 10.2 pp, low confidence |
| 95 | Qwen3.6-35B-A3B | 80.4% | measured |
| 96 | Solar Open 2 | 80.3% | estimated ± 10.2 pp, low confidence |
| 97 | Laguna XS.2 | 79.9% | estimated ± 10.2 pp, low confidence |
| 98 | Ornith-1.0-9B | 79.6% | estimated ± 10.2 pp, low confidence |
| 99 | Qwen3.5-35B-A3B | 79.4% | estimated ± 10.2 pp, low confidence |
| 100 | Grok 4.3 | 79.2% | estimated ± 8.9 pp, low confidence |
| 101 | K-EXAONE 2.0 | 78.8% | estimated ± 10.2 pp, low confidence |
| 102 | LongCat-Flash-Lite-Sparse | 78.8% | estimated ± 10.2 pp, low confidence |
| 103 | Ternary Bonsai 2 27B | 73.3% | estimated ± 10.2 pp, low confidence |
| 104 | o1 | 73.2% | estimated ± 8.9 pp, low confidence |
| 105 | Step 3.7 Flash | 72.9% | estimated ± 8.9 pp, low confidence |
| 106 | Gemma 4 26B A4B | 72.3% | estimated ± 8.9 pp, low confidence |
| 107 | Granite 4.2 30B | 70.4% | estimated ± 10.2 pp, low confidence |
| 108 | GPT-5 (high) | 68.7% | estimated ± 8.9 pp, low confidence |
| 109 | Nemotron 3 Super 100B | 68.6% | estimated ± 8.9 pp, low confidence |
| 110 | GPT-4.1 | 68.4% | estimated ± 10.2 pp, low confidence |
| 111 | ZAYA1-74B-Preview | 67.3% | estimated ± 10.2 pp, low confidence |
| 112 | o3-mini | 63.9% | estimated ± 10.2 pp, low confidence |
| 113 | LLaDA2.2-flash | 63.9% | estimated ± 10.2 pp, low confidence |
| 114 | Claude 3.5 Sonnet | 63.6% | estimated ± 10.2 pp, low confidence |
| 115 | MiniCPM5-2B | 61.3% | estimated ± 10.2 pp, low confidence |
| 116 | o1-preview | 60.4% | estimated ± 8.9 pp, low confidence |
| 117 | Gemini 2.5 Pro | 58.7% | estimated ± 8.9 pp, low confidence |
| 118 | K-Exaone | 56.3% | estimated ± 8.9 pp, low confidence |
| 119 | Gemma 4 12B | 53.8% | estimated ± 8.9 pp, low confidence |
| 120 | GPT-OSS 120B | 52.7% | estimated ± 8.9 pp, low confidence |
| 121 | Command A+ | 47.4% | estimated ± 8.9 pp, low confidence |
| 122 | Nemotron 3.5 Lightning 30B A3B NVFP4 | 45.2% | estimated ± 8.9 pp, low confidence |
| 123 | Mistral Small 4 | 45.0% | estimated ± 8.9 pp, low confidence |
| 124 | Mistral Small 4 (Reasoning) | 45.0% | estimated ± 8.9 pp, low confidence |
| 125 | Trinity-Large-Preview | 43.3% | estimated ± 8.9 pp, low confidence |
| 126 | Trinity-Large-Thinking | 43.3% | estimated ± 8.9 pp, low confidence |
| 127 | Ling 2.6 Flash | 42.2% | estimated ± 8.9 pp, low confidence |
| 128 | Gemini 1.5 Pro | 39.1% | estimated ± 8.9 pp, low confidence |
| 129 | DeepSeek V3 | 37.6% | measured |
| 130 | Granite 4.2 8B | 36.7% | estimated ± 8.9 pp, low confidence |
| 131 | GPT-4 Turbo | 35.0% | estimated ± 8.9 pp, low confidence |
| 132 | GPT-OSS 20B | 33.5% | estimated ± 8.9 pp, low confidence |
| 133 | GPT-4.1 mini | 32.6% | estimated ± 8.9 pp, low confidence |
| 134 | Mistral Large 3 | 32.3% | estimated ± 8.9 pp, low confidence |
| 135 | Claude 3 Opus | 31.3% | estimated ± 8.9 pp, low confidence |
| 136 | Llama 4 Maverick | 25.5% | estimated ± 8.9 pp, low confidence |
| 137 | Celeris-1 | 22.1% | estimated ± 8.9 pp, low confidence |
| 138 | Nemotron 3 Nano 30B | 22.1% | estimated ± 8.9 pp, low confidence |
| 139 | Nemotron 3 Nano Omni 30B A3B | 21.0% | estimated ± 8.9 pp, low confidence |
| 140 | Ultravox v0.6 Llama 3.3 70B | 17.9% | estimated ± 8.9 pp, low confidence |
| 141 | GPT-4o mini | 17.0% | estimated ± 8.9 pp, low confidence |
| 142 | GPT-4.1 nano | 16.6% | estimated ± 8.9 pp, low confidence |
| 143 | Gemma 3 27B | 14.7% | estimated ± 8.9 pp, low confidence |
| 144 | Gemma 4 E4B | 13.6% | estimated ± 8.9 pp, low confidence |
| 145 | Llama 4 Scout | 11.6% | estimated ± 8.9 pp, low confidence |
| 146 | LFM2.5-2.6B | 10.9% | estimated ± 8.9 pp, low confidence |
| 147 | Gemma 4 E2B | 10.1% | estimated ± 8.9 pp, low confidence |
All leaderboards
Agentic · terminal
- AA Terminal-Bench 2.1
- AA Terminal-Bench 4.0
- Terminal-Bench 2.0
- Terminal-Bench 3.0
- Terminal-Bench 4.0
- Terminal-Bench-Science 0.1
- Terminal-Bench 2.1
- Terminal-Bench 2.1 (Vals AI)
Agentic · tools
- AA Agentic Index
- AA-AnalystAgent
- AA AutomationBench
- AA EnterpriseOps-Gym
- GDP.pdf
- AA Harvey LAB
- AA ITBench
- AA Tau3 Banking
- Agents' Last Exam
- APEX-Agents
- APEX-Agents-AA
- ApprenticeBench
- AutomationBench
- BFCL v4
- BrowseComp
- Claw-Eval
- CWE-bench v1
- CyberGym
- DeepPlanning
- DeepSearchQA
- DRACO
- ExploitGym
- GDPval-AA
- Gert Labs
- HLE w/ tools
- JobBench
- MCP Atlas
- MCP-Tasks
- OSWorld-Verified
- OSWorld 2.0
- QwenClawBench
- ResearchClawBench
- SkillsBench
- τ²-bench results
- τ³-bench results
- Toolathlon
- Toolathlon-Verified
- VITA-Bench
- WideResearch
Coding
- AA Coding Index
- AA-SciCode
- CursorBench 3.1
- CursorBench 3.2
- CursorBench 4.0
- DeepSWE
- FrontierCode 1.1 Main
- FrontierCode 1.1 Extended
- FrontierSWE v2
- LiveCodeBench
- LiveCodeBench Pro
- LiveCodeBench v6
- NL2Repo
- OpenHarmony Bench
- PostTrainBench v1.1
- ProgramBench
- React Native Evals
- SciCode
- SWE-bench Pro
- SWE-bench Verified
- SWE-Rebench
- Vals LiveCodeBench
- Vals SWE-bench
- Vibe Code Bench
- VulcanBench v3
Math
- AIME 2025
- AIME26
- FrontierMath (legacy)
- FrontierMath v2 (Tier 4)
- FrontierMath v2 (Tiers 1-3)
- HMMT Feb 2025
- HMMT Feb 2026
- HMMT Nov 2025
- IMOAnswerBench
- MATH-500
- MMAnswerBench
Knowledge & reasoning
- AA-GPQA Diamond
- AA-HLE
- ARC-AGI-2
- ARC-AGI-1
- ARC-AGI-3
- Artificial Analysis Intelligence Index
- BioMysteryBench (human-difficult)
- BioMysteryBench (human-solvable)
- C-Eval
- CritPt
- GPQA
- GPQA Diamond
- HealthBench (raw)
- HealthBench Hard
- HealthBench (length-adjusted)
- HealthBench Professional
- HealthBench Professional (raw)
- HLE
- HLE w/o tools
- HLE-Verified
- JevBench 1.4
- LABBench2
- MedXpertQA (Text)
- MMLU
- MMLU-Pro
- MMLU-Pro (Arcee)
- MMLU-Redux
- MMMLU
- AA-Omniscience Accuracy
- SuperGPQA
- Vals GPQA Diamond
- Vals MMLU-Pro
Instruction following
Multilingual
Vision & documents
- AA-MMMU-Pro
- BabyVision
- CharXiv
- CharXiv w/o tools
- ERQA
- MathVision
- MathVision w/ Python
- MedXpertQA (MM)
- MMMU
- MMMU-Pro
- MMMU-Pro w/ Python
- MMVU
- OfficeQA Pro
- OmniDocBench 1.5
- RealWorldQA
- RefCOCO (avg)
- ScreenSpot Pro
- SimpleVQA
- Video-MME (with subtitle)
- VideoMMMU
- V*
- ZeroBench