Coding
FrontierCode 1.1 Extended leaderboard
As of 2026-10-07, the highest measured score on FrontierCode 1.1 Extended is 64.5% by GPT-6 Astra. 139 more models have estimated scores, calibrated from the benchmarks they were measured on.
Measured scores: benchlm.ai.
| # | Model | Score | Source |
|---|---|---|---|
| 1 | GPT-6 Astra | 64.5% | measured |
| 2 | Claude Opus 5 | 63.6% | measured |
| 3 | Claude Opus 5.5 | 63.6% | measured |
| 4 | Claude Fable 5.1 | 62.5% | estimated ± 1.6 pp, low confidence |
| 5 | Claude Fable 5 | 62.4% | estimated ± 1.6 pp, medium confidence |
| 6 | Gemini 3.8 Flash | 62.3% | estimated ± 1.6 pp, medium confidence |
| 7 | Claude Mythos 5 | 61.5% | estimated ± 3.0 pp, medium confidence |
| 8 | Grok 4.6 | 61.3% | measured |
| 9 | DeepSeek V4 Pro 0813 | 61.1% | estimated ± 2.4 pp, medium confidence |
| 10 | Grok 4.7 | 61.0% | estimated ± 3.0 pp, medium confidence |
| 11 | GPT-5.6 Sol | 60.6% | measured |
| 12 | Sakana Fugu-Ultra | 59.9% | estimated ± 3.0 pp, medium confidence |
| 13 | Muse Spark 1.3 | 59.5% | estimated ± 3.0 pp, medium confidence |
| 14 | Grok 4.5 | 59.4% | estimated ± 1.6 pp, medium confidence |
| 15 | GLM-5.3 | 59.2% | estimated ± 2.4 pp, medium confidence |
| 16 | Claude Sonnet 5.5 | 59.1% | measured |
| 17 | Hy4 preview | 57.8% | estimated ± 3.0 pp, medium confidence |
| 18 | Beam | 57.7% | estimated ± 3.0 pp, medium confidence |
| 19 | Qwen3.8 Max Preview | 57.7% | estimated ± 3.4 pp, low confidence |
| 20 | Ornith-1.5-397B | 57.6% | estimated ± 3.0 pp, medium confidence |
| 21 | Claude Opus 4.7 (Adaptive) | 57.4% | estimated ± 3.0 pp, medium confidence |
| 22 | Qwen3.8-Omni-Flash | 57.1% | estimated ± 3.0 pp, medium confidence |
| 23 | Qwen3.8-Flash-Next | 56.8% | estimated ± 3.0 pp, low confidence |
| 24 | Ornith-1.0-397B | 56.7% | estimated ± 3.0 pp, low confidence |
| 25 | dots3-note Preview | 56.3% | estimated ± 3.0 pp, low confidence |
| 26 | Atria Dawn Preview | 55.9% | estimated ± 3.0 pp, low confidence |
| 27 | Ornith-1.5-35B-A3B | 55.9% | estimated ± 3.0 pp, low confidence |
| 28 | Laguna S 2.1 | 55.8% | estimated ± 3.0 pp, low confidence |
| 29 | GPT-5.6 Terra | 55.8% | measured |
| 30 | Sakana Fugu | 55.7% | estimated ± 3.0 pp, low confidence |
| 31 | GPT-5.4 | 55.2% | estimated ± 3.0 pp, low confidence |
| 32 | Qwen3.7 Plus | 55.2% | estimated ± 3.0 pp, low confidence |
| 33 | Claude Opus 4.8 | 55.2% | estimated ± 1.6 pp, medium confidence |
| 34 | Claude Sonnet 5 | 55.1% | estimated ± 1.6 pp, medium confidence |
| 35 | Kimi K3 | 55.1% | estimated ± 1.6 pp, low confidence |
| 36 | GPT-5.5 | 55.1% | estimated ± 1.6 pp, low confidence |
| 37 | Composer 2.5 | 55.1% | estimated ± 1.6 pp, low confidence |
| 38 | Gemini 3.5 Flash | 55.1% | estimated ± 1.6 pp, low confidence |
| 39 | Gemini 3.6 Flash | 55.1% | estimated ± 1.6 pp, low confidence |
| 40 | GLM-5.2 | 55.1% | estimated ± 1.6 pp, low confidence |
| 41 | Kimi K2.7 Code | 55.1% | estimated ± 1.6 pp, low confidence |
| 42 | GPT-5.6 Luna | 55.1% | measured |
| 43 | Claude Opus 4.5 | 55.0% | estimated ± 3.0 pp, low confidence |
| 44 | Step 3.7 Flash | 54.7% | estimated ± 3.0 pp, low confidence |
| 45 | GPT-5.2 | 54.5% | estimated ± 3.0 pp, low confidence |
| 46 | GLM-5 | 54.3% | estimated ± 3.0 pp, low confidence |
| 47 | Claude Opus 4.6 | 53.7% | estimated ± 3.0 pp, low confidence |
| 48 | MAI-Thinking-1 | 53.4% | estimated ± 3.0 pp, low confidence |
| 49 | Muse Glimmer 30B | 52.8% | estimated ± 3.0 pp, low confidence |
| 50 | GLM-5.3-Flash | 52.7% | estimated ± 2.4 pp, low confidence |
| 51 | Qwen3.5 397B | 52.7% | estimated ± 3.0 pp, low confidence |
| 52 | Kimi K2.5 | 52.6% | estimated ± 3.0 pp, low confidence |
| 53 | Ornith-1.0-35B | 52.5% | estimated ± 3.0 pp, low confidence |
| 54 | Qwen3.6-35B-A3B | 52.1% | estimated ± 3.0 pp, low confidence |
| 55 | Quasar 438B | 51.4% | estimated ± 3.4 pp, low confidence |
| 56 | Laguna XS 2.1 | 51.3% | estimated ± 3.0 pp, low confidence |
| 57 | Ornith-1.5-9B | 51.2% | estimated ± 3.0 pp, low confidence |
| 58 | Apodex 1.1 | 51.1% | estimated ± 3.4 pp, low confidence |
| 59 | Apodex 1.1 Mini | 51.1% | estimated ± 3.4 pp, low confidence |
| 60 | Hy3 | 49.9% | estimated ± 3.4 pp, low confidence |
| 61 | Hy3 Preview | 49.9% | estimated ± 3.4 pp, low confidence |
| 62 | Ornith-1.0-9B | 49.1% | estimated ± 3.0 pp, low confidence |
| 63 | LongCat-Flash-Lite-Sparse | 47.9% | estimated ± 3.0 pp, low confidence |
| 64 | DeepSeek V4 Flash 0731 | 46.5% | estimated ± 2.4 pp, low confidence |
| 65 | Ling 3.0 Flash FP8 | 44.5% | estimated ± 3.4 pp, low confidence |
| 66 | MiMo-V2-Flash | 43.9% | estimated ± 3.4 pp, low confidence |
| 67 | Granite 4.2 30B | 43.6% | estimated ± 3.0 pp, low confidence |
| 68 | GPT-5.1 | 43.6% | estimated ± 3.4 pp, low confidence |
| 69 | Muse Spark 1.2 | 42.3% | estimated ± 2.4 pp, low confidence |
| 70 | Kimi K2.5 (Reasoning) | 41.8% | estimated ± 3.4 pp, low confidence |
| 71 | LLaDA2.2-flash | 41.5% | estimated ± 3.0 pp, low confidence |
| 72 | Qwen3.8-27B | 41.2% | estimated ± 2.4 pp, low confidence |
| 73 | Qwen3.5-122B-A10B | 41.0% | estimated ± 3.4 pp, low confidence |
| 74 | Qwen3.8 Max | 40.4% | estimated ± 2.4 pp, low confidence |
| 75 | Gemma 4 31B | 39.4% | estimated ± 3.4 pp, low confidence |
| 76 | o1 | 36.6% | estimated ± 3.4 pp, low confidence |
| 77 | Gemma 4 26B A4B | 36.3% | estimated ± 3.4 pp, low confidence |
| 78 | GPT-5 (high) | 35.2% | estimated ± 3.4 pp, low confidence |
| 79 | Nemotron 3 Super 100B | 35.1% | estimated ± 3.4 pp, low confidence |
| 80 | Inkling-Small | 34.2% | estimated ± 2.4 pp, low confidence |
| 81 | Claude Opus 4.7 | 33.8% | estimated ± 2.4 pp, low confidence |
| 82 | Muse Spark 1.1 | 33.8% | estimated ± 2.4 pp, low confidence |
| 83 | o1-preview | 32.3% | estimated ± 3.4 pp, low confidence |
| 84 | Granite 4.2 8B | 31.9% | estimated ± 3.0 pp, low confidence |
| 85 | Gemini 3.7 Flash | 31.7% | estimated ± 2.4 pp, low confidence |
| 86 | K-Exaone | 30.7% | estimated ± 3.4 pp, low confidence |
| 87 | Gemma 4 12B | 29.8% | estimated ± 3.4 pp, low confidence |
| 88 | GPT-OSS 120B | 29.3% | estimated ± 3.4 pp, low confidence |
| 89 | Gemini 3.1 Pro | 28.4% | estimated ± 2.4 pp, low confidence |
| 90 | Command A+ | 27.2% | estimated ± 3.4 pp, low confidence |
| 91 | GPT-5.3 Codex | 27.1% | estimated ± 2.4 pp, low confidence |
| 92 | MiniCPM5-2B | 26.4% | estimated ± 3.0 pp, low confidence |
| 93 | Inkling | 26.4% | estimated ± 2.4 pp, low confidence |
| 94 | Nemotron 3.5 Lightning 30B A3B NVFP4 | 26.3% | estimated ± 3.4 pp, low confidence |
| 95 | Mistral Small 4 | 26.2% | estimated ± 3.4 pp, low confidence |
| 96 | Mistral Small 4 (Reasoning) | 26.2% | estimated ± 3.4 pp, low confidence |
| 97 | Claude Sonnet 4.6 | 26.1% | estimated ± 2.4 pp, low confidence |
| 98 | Trinity-Large-Preview | 25.4% | estimated ± 3.4 pp, low confidence |
| 99 | Trinity-Large-Thinking | 25.4% | estimated ± 3.4 pp, low confidence |
| 100 | Ling 2.6 Flash | 25.0% | estimated ± 3.4 pp, low confidence |
| 101 | GLM-5.1 | 24.5% | estimated ± 2.4 pp, low confidence |
| 102 | Kimi K2.6 | 24.2% | estimated ± 2.4 pp, low confidence |
| 103 | Gemini 1.5 Pro | 23.5% | estimated ± 3.4 pp, low confidence |
| 104 | DeepSeek V3 | 23.0% | estimated ± 3.4 pp, low confidence |
| 105 | Gemini 3.5 Flash-Lite | 22.4% | estimated ± 2.4 pp, low confidence |
| 106 | Gemini 3 Flash | 22.4% | estimated ± 2.4 pp, low confidence |
| 107 | MiniMax M3 | 22.4% | estimated ± 2.4 pp, low confidence |
| 108 | GPT-4 Turbo | 21.6% | estimated ± 3.4 pp, low confidence |
| 109 | Muse Spark | 21.6% | estimated ± 2.4 pp, low confidence |
| 110 | MiMo-V2.5-Pro | 21.0% | estimated ± 2.4 pp, low confidence |
| 111 | GPT-OSS 20B | 20.9% | estimated ± 3.4 pp, low confidence |
| 112 | MiniMax M2.7 | 20.7% | estimated ± 2.4 pp, low confidence |
| 113 | GPT-4.1 mini | 20.5% | estimated ± 3.4 pp, low confidence |
| 114 | Mistral Large 3 | 20.4% | estimated ± 3.4 pp, low confidence |
| 115 | Qwen3.6 Plus | 20.2% | estimated ± 2.4 pp, low confidence |
| 116 | Claude 3 Opus | 19.9% | estimated ± 3.4 pp, low confidence |
| 117 | GPT-5.4 mini | 19.6% | estimated ± 2.4 pp, low confidence |
| 118 | Qwen 3.6 Max (preview) | 19.4% | estimated ± 2.4 pp, low confidence |
| 119 | GPT-5.2-Codex | 18.8% | estimated ± 2.4 pp, low confidence |
| 120 | Grok 4.20 | 18.6% | estimated ± 2.4 pp, low confidence |
| 121 | Grok 4.3 | 17.5% | estimated ± 2.4 pp, low confidence |
| 122 | MiMo-V2.5 | 17.0% | estimated ± 2.4 pp, low confidence |
| 123 | Llama 4 Maverick | 16.8% | estimated ± 3.4 pp, low confidence |
| 124 | Qwen3.6-27B | 15.8% | estimated ± 2.4 pp, low confidence |
| 125 | GPT-5.4 nano | 15.6% | estimated ± 2.4 pp, low confidence |
| 126 | GLM-4.7 | 15.1% | estimated ± 2.4 pp, low confidence |
| 127 | Celeris-1 | 15.0% | estimated ± 3.4 pp, low confidence |
| 128 | Nemotron 3 Nano 30B | 15.0% | estimated ± 3.4 pp, low confidence |
| 129 | Nemotron 3 Ultra | 14.7% | estimated ± 2.4 pp, low confidence |
| 130 | Qwen3.7 Max | 14.5% | estimated ± 2.4 pp, low confidence |
| 131 | Nemotron 3 Nano Omni 30B A3B | 14.4% | estimated ± 3.4 pp, low confidence |
| 132 | Ultravox v0.6 Llama 3.3 70B | 12.6% | estimated ± 3.4 pp, low confidence |
| 133 | Claude Haiku 4.5 | 12.2% | estimated ± 2.4 pp, low confidence |
| 134 | GPT-4o mini | 12.1% | estimated ± 3.4 pp, low confidence |
| 135 | Mistral Medium 3.5 128B | 12.0% | estimated ± 2.4 pp, low confidence |
| 136 | GPT-4.1 nano | 11.8% | estimated ± 3.4 pp, low confidence |
| 137 | Ling 3.0 Flash | 10.8% | estimated ± 2.4 pp, low confidence |
| 138 | Gemma 3 27B | 10.8% | estimated ± 3.4 pp, low confidence |
| 139 | Qwen3.5 Flash | 10.1% | estimated ± 2.4 pp, low confidence |
| 140 | Gemma 4 E4B | 10.1% | estimated ± 3.4 pp, low confidence |
| 141 | Llama 4 Scout | 8.8% | estimated ± 3.4 pp, low confidence |
| 142 | Gemini 3.1 Flash-Lite | 8.8% | estimated ± 2.4 pp, low confidence |
| 143 | LFM2.5-2.6B | 8.4% | estimated ± 3.4 pp, low confidence |
| 144 | Gemma 4 E2B | 7.8% | estimated ± 3.4 pp, low confidence |
| 145 | Laguna M.1 | 5.4% | estimated ± 2.4 pp, low confidence |
| 146 | Laguna XS.2 | 4.2% | estimated ± 2.4 pp, low confidence |
| 147 | Gemini 2.5 Pro | 3.9% | estimated ± 2.4 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