Claude Sonnet 5.5 vs Gemini 3.1 Pro
Claude Sonnet 5.5 
Gemini 3.1 Pro Verdict
- Claude Sonnet 5.5 (max) leads on quality: 67.6 vs 62.1.
- Claude Sonnet 5.5 (max) is stronger in agents & tools, coding, composite, knowledge, long context, maths, reasoning.
- Gemini 3.1 Pro is stronger in human preference, instruction following, multimodal.
- They cost about the same ($4.00 per 1M blended).
| Metric | Claude Sonnet 5.5 (max) | Gemini 3.1 Pro |
|---|---|---|
| BenchLeader Index | 67.6 | 62.1 |
| Agents & tools score | 69.5 | 56.7 |
| Coding score | 69.8 | 57.3 |
| Composite score | 72.6 | 63.2 |
| Knowledge score | 65.4 | 64.5 |
| Long context score | 66.6 | 66.3 |
| Maths score | 72.9 | 61.0 |
| Reasoning score | 81.1 | 68.6 |
| Human preference score | – | 59.5 |
| Instruction following score | – | 68.4 |
| Multimodal score | – | 64.9 |
| Blended price $/M | $4.00 | $4.50 |
| Output speed | 141 tok/s | 114 tok/s |
| Time to first answer | 487.1 s | 24.8 s |
| Context window | 1M | 1.0M |
| GPQA Diamond | 95.6% | 94.1% |
| FrontierMath Tiers 1–3 | 88.8% | 59.6% |
| FrontierMath Tier 4 | 80.5% | 26.8% |
| OTIS Mock AIME | 100.0% | 95.6% |
| SimpleQA Verified | 46.5% | – |
| Humanity's Last Exam | – | 46.4% |
| Terminal-Bench | 61.8% | 80.2% |
| SimpleBench | – | 79.6% |
| SciCode | 61.0% | 58.9% |
| WeirdML | – | 72.1% |
| APEX-Agents | 75.5% | 35.3% |
| ProofBench | 100.0% | 26.0% |
| GSO-Bench | – | 22.6% |
| Epoch Capabilities Index | – | 154.8 |
| LMArena Text | – | 1487 |
| LMArena Hard Prompts | – | 1508 |
| LMArena Coding | – | 1522 |
| LMArena WebDev | – | 1447 |
| LMArena Vision | – | 1296 |
| LMArena Agent | 12 | -7.8 |
| LiveBench | 75.7% | – |
| LiveBench Reasoning | 91.6% | – |
| LiveBench Coding | 91.4% | – |
| LiveBench Agentic Coding | 56.3% | – |
| LiveBench Mathematics | 96.1% | – |
| LiveBench Data Analysis | 59.5% | – |
| LiveBench Language | 78.0% | – |
| LiveBench Instruction Following | 56.8% | – |
| AA Intelligence Index v4.3.2 | 56 | 29.7 |
| IFBench | – | 77.1% |
| AA-LCR | 82.7% | 82.0% |
| MMMU-Pro | – | 82.4% |
| AA-Omniscience | 32.3 | 31.9 |
| Terminal-Bench Hard | – | 53.8% |
| GPQA Diamond (AA) | – | 94.1% |
| Humanity's Last Exam (AA) | 55.0% | 47.0% |
| SciCode (AA) | 61.0% | 58.7% |
| τ²-Bench Telecom (AA) | – | 95.6% |
| AIME 2026 | – | 98.3% |
| HMMT February 2026 | – | 94.7% |
| MathArena Apex | – | 60.9% |
| MultiChallenge | – | 71.4% |
| PRBench Finance | – | 41.9% |
| PRBench Legal | – | 44.0% |
| MultiNRC | – | 64.7% |
| HiL-Bench | – | 35.3% |
| TutorBench | – | 53.0% |
| EQ-Bench 4 | – | 1142 |
| ARC-AGI-1 | – | 98.0% |
| ARC-AGI-2 | – | 77.1% |
| ARC-AGI-3 | – | 0.4% |
| CritPt | 31.4% | 17.7% |
| GDPval-AA v2.1 | 67.0% | 14.7% |
| τ³-Banking (AA) | – | 21.4% |
| ITBench SRE (AA) | – | 30.3% |
| Analyst Agent (AA) | 57.5% | 41.3% |
| APEX-Agents (AA) | – | 32.0% |
| FORTRESS | – | 29.8% |
| MASK | – | 42.4% |
| SWE Atlas: Codebase QnA | – | 13.5% |
| SWE Atlas: Refactoring | – | 33.8% |
| SWE Atlas: Test Writing | – | 29.8% |
| LMArena Maths | – | 1488 |
| LMArena Creative Writing | – | 1481 |
| LMArena Instruction Following | – | 1480 |
| LMArena Multi-turn | – | 1497 |
| LMArena Longer Queries | – | 1500 |
| LMArena Document | – | 1459 |
| Chess Puzzles | – | 55.0% |
| EBR-bench | – | 14.3% |
| Mystery Game Puzzles | 65.0% | – |
| BALROG | – | 57.0% |
| PostTrainBench | – | 22.0% |
| ExploitBench | – | 26.1% |
| CL-bench | – | 20.8% |
| CL-bench Life | – | 16.9% |
| METR Time Horizons | – | 77.0% |
| DeepSWE v1.1 | – | 11.7% |
| ForecastBench | – | 59.0% |
| CursorBench | 55.5% | – |
| GBAEval | – | 0.8% |
| ALE-Bench | – | 1160.6 |
| AlgoTune | – | 2.0 |
| Vending-Bench 2 | – | 911.2 |
| Blueprint-Bench 2 | – | 26.5% |
| GDP.pdf | – | 17.0% |
| FrontierSWE | 61.9% | – |
| Terminal-Bench 4.0 (AA) | 63.6% | 4.0% |
| Terminal-Bench 2.1 (AA) | – | 73.8% |
| AutomationBench | 71.8% | 35.4% |
| GDP.pdf | 25.8% | 17.8% |
| MLCR | 75.0% | 15.6% |
| Harvey LAB | 2.8% | 0.0% |
| EnterpriseOps-Gym | – | 42.2% |
| AA-Omniscience: accuracy | 54.0% | 54.9% |
| AA-Omniscience: non-hallucination | 53.0% | 49.1% |
| AA-Briefcase v1.1 | 1823 | 456 |
| BrowseComp | – | 31.2% |
| DeepSearchQA | – | 60.2% |
| FACTS Search | – | 83.7% |
Data as of 2026-10-11. Best configuration of each model; every score links to its source on the model pages.
Claude Sonnet 5.5 vs Gemini 3.1 Pro: questions
- Is Claude Sonnet 5.5 better than Gemini 3.1 Pro?
- Claude Sonnet 5.5 (max) leads on quality: 67.6 vs 62.1. The BenchLeader Index combines every independent quality benchmark; Claude Sonnet 5.5 (max) is ahead overall as of 2026-10-11, but check the category scores for your use.
- Is Claude Sonnet 5.5 better than Gemini 3.1 Pro for coding?
- Claude Sonnet 5.5 scores higher in coding (70 vs 57 on the category index, where 50 is average).
- Is Claude Sonnet 5.5 better than Gemini 3.1 Pro for agentic tasks?
- Claude Sonnet 5.5 scores higher in agentic tasks (70 vs 57 on the category index, where 50 is average).
- Which is cheaper, Claude Sonnet 5.5 or Gemini 3.1 Pro?
- Claude Sonnet 5.5 is cheaper: $4.00 against $4.50 per million tokens, blended at three input tokens per output token.
- Which is faster, Claude Sonnet 5.5 or Gemini 3.1 Pro?
- Claude Sonnet 5.5 streams faster: 141 against 114 output tokens per second.
- Which has the larger context window?
- Gemini 3.1 Pro accepts more context: 1.0M against 1M tokens.