| Benchmark | Claude Sonnet 4.6 | Gemini 2.5 Pro |
|---|---|---|
| AA Agentic Index | 61.6 | 7.2 |
| AA Intelligence | 48.4 | 27 |
| AA-LCR | 74 | 66 |
| AA-Omniscience | 12.2 | -14.3 |
| arc_agi_1 | 86.5 | 41 |
| ARC-AGI-2 | 60.4 | 4.9 |
| arena_elo | 1472 | 1446 |
| arena_text_factuality | 1460 | 1462 |
| arena_vision | 1278 | 1246 |
| Artificial Analysis Coding Index | 63 | 46.7 |
| browsecomp | 76.2 | 9.9 |
| coding_arena_elo | 1523 | 1224 |
| critpt | 3.1 | 2.6 |
| frontiermath_tier_4 | 8.3 | 4.2 |
| gdpval | 54.8 | 8.5 |
| GPQA Diamond | 89.9 | 84.4 |
| harmbench | 24.2 | 65.4 |
| HLE | 49 | 22.5 |
| HLE (with tools) | 46.8 | 28.4 |
| IFBench | 56.6 | 49 |
| MMMU-Pro | 75.6 | 74.9 |
| OmniScience Accuracy | 40.9 | 39 |
| OmniScience Non-Hallucination | 51.6 | 12.6 |
| scicode | 47 | 43 |
| simpleqa_verified | 29 | 56 |
| SWE-bench Verified | 79.6 | 67.2 |
| TauBench V3 - Banking | 34.4 | 9.7 |
| Terminal-Bench 2.1 | 71.2 | 28.5 |
| Terminal-Bench Hard | 59.1 | 26.5 |
| vectara_answer_rate | 99.9 | 99.1 |
| vectara_avg_summary_length | 114.7 | 106.4 |
| vectara_factual_consistency | 89.4 | 93 |
| vectara_hallucination_rate ↓ | 10.6 | 7 |
| τ²-Bench Telecom (AA run) | 97.9 | 54.1 |
| τ³-Bench | 30.5 | 9.3 |
Best tracked score per model per benchmark (default configuration; source-attributed). ↓ marks lower-is-better metrics. Open either model for its full surface, provenance and pricing.