| Benchmark | Gemini 2.5 Pro | Qwen3.5 27B |
|---|---|---|
| AA Agentic Index | 7.2 | 54.6 |
| AA Intelligence | 27 | 34.6 |
| AA-LCR | 66 | 72.3 |
| AA-Omniscience | -14.3 | -44 |
| arena_vision | 1246 | 1221 |
| Artificial Analysis Coding Index | 46.7 | 34.9 |
| browsecomp | 9.9 | 61 |
| browsecomp_zh | 32.2 | 62.1 |
| coding_arena_elo | 1224 | 1357 |
| critpt | 2.6 | 0.9 |
| gdpval | 8.5 | 33 |
| GPQA Diamond | 84.4 | 85.8 |
| HLE | 22.5 | 48.5 |
| HMMT 2025 | 65.7 | 89.8 |
| hmmt_feb_2025 | 82.5 | 92 |
| hmmt_nov_2025 | 80 | 89.8 |
| IFBench | 49 | 76.5 |
| mathvision | 73.3 | 86 |
| MathVista | 83.9 | 87.8 |
| MMLU-Pro | 86 | 86.1 |
| MMMU | 83.9 | 82.3 |
| MMMU-Pro | 74.9 | 75 |
| MMStar | 79.2 | 81 |
| multichallenge | 53.6 | 60.8 |
| OCRBench | 85.9 | 89.4 |
| OmniScience Accuracy | 39 | 20.7 |
| OmniScience Non-Hallucination | 12.6 | 24.9 |
| scicode | 43 | 39.5 |
| SWE-bench Verified | 67.2 | 75 |
| Terminal-Bench Hard | 26.5 | 32.6 |
| vectara_answer_rate | 99.1 | 99.8 |
| vectara_avg_summary_length | 106.4 | 94.4 |
| vectara_factual_consistency | 93 | 87.9 |
| vectara_hallucination_rate ↓ | 7 | 12.1 |
| τ²-Bench Telecom (AA run) | 54.1 | 93.9 |
| τ³-Bench | 9.3 | 68.4 |
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.