- MMLU-Pro 79.1
- LiveCodeBench (v5) (UI 10/01/2024-02/01/2025) 36
- Bird-SQL (Dev) 59.3
- GPQA (diamond) 64.7
- SimpleQA 44.3
- FACTS Grounding 82.8
- Global MMLU (Lite) 86.5
- MATH 91.8
- HiddenMath 65.2
- MRCR (1M) 74.7
- MMMU 72.7
- CoVoST2 (21 lang), BLEU 40.6
- EgoSchema (test) 71.9
Gemini 2.0 Pro
Gemini 2.0 Pro ranks first on Creation-MMBench.
Google DeepMind Released 5 Feb 2025 45
Benchmarks with a score
1
Ranked first, out of five or more models
4
In the top three
Google DeepMind Feb 2025 Gemini 2.0 Pro
Closed weights
135.0
#146 of 271
Epoch Capabilities Index
- GPQA Diamond 65.7% #118 /219
- LiveCodeBench v5 36% #36 /44
- Bird-SQL 59.3% #4 /13
Where it ranks
Its best score on each benchmark, and where that ranks among every model with a score there. We rank each model once, at its best setting.
Knowledge and language
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| Creation-MMBench | 4.48 | #1 of 19 | Official leaderboard | |
| MMBench-CN v1.1 | 83.5% | #23 of 178 | Official leaderboard | |
| SimpleQA | 44.3% | #17 of 59 | Model card | |
| MRCR (Michelangelo, original) | 74.7% | #3 of 9 | Model card | |
| Global MMLU Lite | 86.5% | #6 of 16 | Model card | |
| MMLU-Pro | 79.1% | #80 of 151 | Model card | |
| LLM Confabulation Leaderboard | 18.4% | #34 of 58 | Official leaderboard | |
| FACTS Grounding | 82.8% | #10 of 15 | Model card | |
| Fiction.LiveBench | 41.7% | #50 of 57 | Epoch AI | |
| Vectara Hallucination Leaderboard (HHEM) | 0.80% | #147 of 148 | Official leaderboard |
Math and science
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| MATH | 91.8% | #6 of 93 | Model card | |
| HiddenMath | 65.2% | #2 of 11 | Model card | |
| MATH Level 5 | 83.5% | #24 of 94 | Epoch AI | |
| GPQA Diamond | 65.7% | #118 of 219 | Epoch AI | |
| Misguided Attention | 34.6% | #31 of 45 | Official leaderboard | |
| AIME 2025 | 27.5% | #50 of 53 | Official leaderboard | |
| HMMT 2025 | 7.50% | #51 of 53 | Official leaderboard |
Coding
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| BigCodeBench-Hard | 31.8% | #12 of 96 | Official leaderboard | |
| Bird-SQL | 59.3% | #4 of 13 | Model card | |
| Aider Polyglot | 35.6% | #35 of 54 | Epoch AI | |
| LiveCodeBench v5 | 36% | #36 of 44 | Model card | |
| BIRD-CRITIC | 21% | #8 of 9 | Official leaderboard |
Agents and tools
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| ToolComp | 61.5% | #13 of 32 | Official leaderboard | |
| Step Race | 1 | #39 of 59 | Official leaderboard | |
| Elimination Game | 3 | #47 of 56 | Official leaderboard |
Professional work
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| TaxEval v2 | 68.2% | #92 of 129 | Official leaderboard | |
| CorpFin v2 | 43.4% | #108 of 119 | Official leaderboard |
Vision, audio and robotics
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| MMStar | 68.5% | #21 of 173 | Official leaderboard | |
| MMBench | 84.3% | #20 of 155 | Official leaderboard | |
| VHELM | 72.4 | #6 of 41 | Official leaderboard | |
| CoVoST2 | 40.6 | #2 of 11 | Model card | |
| MMBench-EN v1.1 | 82.4% | #35 of 178 | Official leaderboard | |
| MMMU | 72.7% | #27 of 136 | Official leaderboard | |
| GeoBench | 77.5% | #16 of 48 | Official leaderboard | |
| VisuLogic | 28% | #6 of 17 | Official leaderboard | |
| MATH-Vision (MathVision) | 48.1% | #54 of 105 | Official leaderboard | |
| VISTA | 43.3% | #29 of 54 | Official leaderboard | |
| EgoSchema | 71.9% | #7 of 12 | Model card | |
| EnigmaEval | 0.69% | #38 of 41 | Epoch AI |
Safety and security
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| AIR-Bench 2024 | 68.4% | #37 of 82 | Official leaderboard | |
| Anthropic Red Team | 98.7% | #44 of 75 | Official leaderboard | |
| HELM Safety | 90.5 | #44 of 75 | Official leaderboard | |
| SimpleSafetyTests | 97.5% | #53 of 75 | Official leaderboard |
Other
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| OpenVLM Leaderboard | 73.3 | #19 of 173 | Official leaderboard | |
| LiveBench | 65.1% | #11 of 48 | Epoch AI |
Google DeepMind's models over time
Google DeepMind's models in color, against every other model on the Epoch Capabilities Index, by release date.
Its launch post
The benchmarks the lab chose to headline, with the scores it gave.