Google DeepMind·released 2026-02-191 source
Gemini 3.1 Pro benchmark scores: 30 benchmarks tracked. 30% of its scores are independently reproduced — the rest are self-reported or unverified.
Leads on 0 of 30 benchmarks·best result 98 on ARC-AGI (unverified)·9 of 30 independently reproduced·$2/$12 per M tokens
Consensus: LiteLLM · See every model’s pricing →
| Benchmark | Score | Evidence status | Measured |
|---|---|---|---|
| ARC-AGI | 98accuracy (%) | unverified· optimizedT1 | 2026-02-19ARC Prize Leaderboard |
| OTIS Mock AIME 2024-2025 | 95.6accuracy (%) | reproduced· optimizedT1 | 2026-02-19Epoch AI |
| DTBench | 95.12accuracy (%) | unverifiedT1 | 2026-02-19https://conceptualreasoning.ai/dtbench |
| GPQA diamond | 92.59accuracy (%) | reproduced· optimizedT1 | 2026-02-19Epoch AI |
| Terminal Bench | 80.22accuracy (%) | unverifiedT1 | 2026-02-19https://www.tbench.ai/leaderboard/terminal-bench/2.0 |
| ARC-AGI-2 | 77.1accuracy (%) | unverifiedT2 | 2026-02-19 |
| METR Time Horizons | 77.03accuracy (%) | self-reportedT1 | 2026-02-19https://metr.org/blog/2025-03-19-measuring-ai-ability-to-complete-long-tasks/ |
| SWE-Bench verified | 75.62accuracy (%) | reproduced· optimizedT1 | 2026-02-19Epoch AI |
| SimpleBench | 75.52accuracy (%) | unverifiedT1 | 2026-02-19https://lmcouncil.ai/benchmarks |
| SimpleQA Verified | 73.5accuracy (%) | unverifiedT2 | 2026-02-19 |
| WeirdML | 72.07accuracy (%) | unverifiedT1 | 2026-02-19https://htihle.github.io/weirdml.html |
| LMCA | 63.32accuracy (%) | unverifiedT1 | 2026-02-19https://conceptualreasoning.ai/lmca |
| FrontierMath-Tiers-1-3-v2-Private | 59.65accuracy (%) | reproducedT1 | 2026-02-19Epoch AI |
| Balrog | 57accuracy (%) | unverifiedT1 | 2026-02-19Balrog Leaderboard |
| Chess Puzzles | 52.65accuracy (%) | reproducedT1 | 2026-02-19Epoch AI |
| DeepResearch Bench | 47.8accuracy (%) | unverifiedT1 | 2026-02-19https://evals.futuresearch.ai/#drb |
| HLE | 43.74accuracy (%) | unverifiedT2 | 2026-02-19 |
| APEX-Agents | 35.3accuracy (%) | unverifiedT2 | 2026-02-19 |
| Mystery Game Puzzles | 27.3accuracy (%) | reproducedT1 | 2026-02-19Epoch AI |
| FrontierMath-Tier-4-v2-Private | 26.83accuracy (%) | reproducedT1 | 2026-02-19Epoch AI |
| ExploitBench | 26.1accuracy (%) | unverifiedT2 | 2026-02-19 |
| ProofBench | 26accuracy (%) | unverifiedT1 | 2026-02-19https://www.vals.ai/benchmarks/proof_bench |
| GSO-Bench | 22.55accuracy (%) | unverifiedT1 | 2026-02-19https://gso-bench.github.io/index.html |
| PostTrainBench | 21.99accuracy (%) | unverifiedT2 | 2026-02-19 |
| CL-bench | 20.8accuracy (%) | unverifiedT2 | 2026-02-19 |
| CL-bench Life | 16.9accuracy (%) | unverifiedT2 | 2026-02-19 |
| EBR-bench | 14.29accuracy (%) | reproducedT1 | 2026-02-19Epoch AI |
| DeepSWE | 11.73accuracy (%) | unverifiedT1 | 2026-02-19https://deepswe.datacurve.ai/ |
| MirrorCode | 8.89accuracy (%) | reproducedT1 | 2026-02-19Epoch AI |
| Furniture Assembly | 0accuracy (%) | unverifiedT2 | 2026-02-19 |
Claims drawn from cited facts, not live model generation.
This model was developed by Google DeepMind and released in 2026.
2 cited facts
It is scored on 30 tracked benchmarks, and it currently holds no top score among them. Its record is independently reproduced, meaning outside evaluation backs up the reported scores.
3 cited facts
Its mean gap to the best recorded score across its tracked benchmarks is 26.85 points.
1 cited fact
5 facts cross-checked across data sources: 5 single-source.
Source facts, citations, and refresh stamp for this record.
Sources: curated_capability_claims, epoch_benchmarks, litellm_prices
Gemini 3.1 Pro is an AI model developed by Google DeepMind, released 2026-02-19. Its benchmark record below tags every score as independently reproduced, self-reported, or unverified.
Gemini 3.1 Pro has recorded scores on 30 benchmarks, each shown with its evidence status.
Gemini 3.1 Pro has recorded scores on 30 benchmarks — GPQA diamond, OTIS Mock AIME 2024-2025, DTBench, WeirdML, LMCA, SimpleQA Verified, and 24 more. The full table above shows each score with its evidence status.
9 of 30 recorded scores (30%) are independently reproduced rather than self-reported by the lab.
Gemini 3.1 Pro has 30 tracked claims: 9 independently reproduced, 1 self-reported, 20 unverified.
Listed API pricing: $2 per million input tokens, $12 per million output tokens. See the pricing block for the full breakdown.