Anthropic · model
Claude Opus 4.6 (Adaptive) benchmark scores
As of 2026-10-07, Claude Opus 4.6 (Adaptive) (Anthropic) has measured scores on 13 benchmarks and estimated scores on 58 more.
| Benchmark | Score | Source |
|---|---|---|
| AA-GPQA Diamond | 89.6% | measured |
| AA-HLE | 39.9% | measured |
| AA-SciCode | 53.5% | estimated ± 3.8 pp, high confidence |
| Artificial Analysis Intelligence Index | 32.0% | measured |
| CritPt | 12.6% | measured |
| GDPval-AA | 38.7% | estimated ± 11.2 pp, low confidence |
| GPQA Diamond | 92.6% | estimated ± 1.4 pp, high confidence |
| HLE | 48.5% | estimated ± 6.3 pp, medium confidence |
| IFBench | 58.3% | estimated ± 6.9 pp, medium confidence |
| AA-LCR | 78.0% | measured |
| AA-Omniscience Accuracy | 47.0% | measured |
| BrowseComp | 85.7% | estimated ± 3.4 pp, high confidence |
| IFEval | 91.9% | estimated ± 1.3 pp, high confidence |
| LongBench v2 | 61.5% | estimated ± 5.9 pp, medium confidence |
| τ²-bench results | 92.1% | measured |
| AA Coding Index | 67.8% | estimated ± 6.8 pp, medium confidence |
| AA-MMMU-Pro | 75.4% | measured |
| APEX-Agents-AA | 33.0% | measured |
| BioMysteryBench (human-difficult) | 44.3% | estimated ± 5.9 pp, low confidence |
| SWE-bench Verified | 81.7% | estimated ± 4.4 pp, high confidence |
| BFCL v4 | 67.5% | estimated ± 9.8 pp, low confidence |
| JobBench | 41.4% | estimated ± 8.2 pp, low confidence |
| AA Agentic Index | 32.9% | estimated ± 11.8 pp, low confidence |
| MMLU-Pro | 85.7% | estimated ± 3.5 pp, high confidence |
| GPQA | 92.4% | estimated ± 1.6 pp, high confidence |
| AA-IFBench | 53.1% | measured |
| Gert Labs | 59.5% | estimated ± 11.3 pp, low confidence |
| AA EnterpriseOps-Gym | 41.5% | estimated ± 3.6 pp, medium confidence |
| ApprenticeBench | 9.2% | estimated ± 5.0 pp, low confidence |
| ARC-AGI-1 | 93.0% | measured |
| ARC-AGI-2 | 68.8% | measured |
| FrontierCode 1.1 Main | 27.0% | estimated ± 4.3 pp, medium confidence |
| OfficeQA Pro | 50.3% | estimated ± 7.2 pp, low confidence |
| Vals GPQA Diamond | 92.1% | estimated ± 2.2 pp, high confidence |
| Vals MMLU-Pro | 89.0% | estimated ± 1.8 pp, high confidence |
| Vals SWE-bench | 80.2% | estimated ± 6.3 pp, medium confidence |
| AA ITBench | 47.4% | estimated ± 3.6 pp, medium confidence |
| HLE w/o tools | 38.3% | estimated ± 5.7 pp, medium confidence |
| PostTrainBench v1.1 | 21.1% | estimated ± 10.5 pp, low confidence |
| Vibe Code Bench | 53.5% | measured |
| CharXiv | 82.3% | estimated ± 7.5 pp, low confidence |
| CharXiv w/o tools | 79.8% | estimated ± 2.4 pp, high confidence |
| C-Eval | 94.5% | estimated ± 1.0 pp, low confidence |
| MathVision | 87.5% | estimated ± 4.9 pp, high confidence |
| MCP Atlas | 72.3% | estimated ± 9.4 pp, medium confidence |
| MCP-Tasks | 68.2% | estimated ± 8.2 pp, low confidence |
| MMLU-Redux | 97.2% | estimated ± 1.1 pp, low confidence |
| MMMU-Pro | 77.1% | estimated ± 4.4 pp, medium confidence |
| ScreenSpot Pro | 74.1% | estimated ± 10.7 pp, low confidence |
| SuperGPQA | 84.5% | estimated ± 7.5 pp, low confidence |
| Toolathlon | 50.3% | estimated ± 7.0 pp, low confidence |
| ERQA | 64.0% | estimated ± 3.9 pp, high confidence |
| HealthBench Hard | 28.9% | estimated ± 7.7 pp, low confidence |
| MedXpertQA (MM) | 72.8% | estimated ± 6.5 pp, low confidence |
| MMLU-Pro (Arcee) | 100.0% | estimated ± 4.0 pp, low confidence |
| React Native Evals | 82.2% | estimated ± 3.0 pp, medium confidence |
| ResearchClawBench | 16.5% | estimated ± 2.6 pp, medium confidence |
| SWE-Rebench | 62.1% | estimated ± 6.5 pp, low confidence |
| ARC-AGI-3 | 1.7% | estimated ± 3.4 pp, high confidence |
| BioMysteryBench (human-solvable) | 85.7% | estimated ± 0.6 pp, low confidence |
| HealthBench (raw) | 49.0% | estimated ± 6.4 pp, low confidence |
| HealthBench (length-adjusted) | 56.3% | estimated ± 2.5 pp, low confidence |
| HealthBench Professional | 55.1% | estimated ± 4.6 pp, high confidence |
| HealthBench Professional (raw) | 59.3% | estimated ± 5.0 pp, medium confidence |
| HLE-Verified | 35.3% | estimated ± 0.7 pp, low confidence |
| LABBench2 | 76.8% | estimated ± 1.3 pp, low confidence |
| MMMU | 83.3% | estimated ± 0.9 pp, high confidence |
| MMLU | 94.5% | estimated ± 1.1 pp, low confidence |
| MMMU-Pro w/ Python | 78.9% | estimated ± 1.6 pp, high confidence |
| RealWorldQA | 85.2% | estimated ± 1.2 pp, medium confidence |
| OmniDocBench 1.5 | 90.0% | estimated ± 6.4 pp, low confidence |