- Humanity's Last Exam (no tools), Thinking (06-17) 6.9
- GPQA diamond, Thinking 66.7
- AIME 2025, Thinking 63.1
- LiveCodeBench v5 (UI: 1/1/2025-5/1/2025), Thinking 34.3
- Aider Polyglot (whole), Thinking 27.1
- SWE-Bench Verified, multiple attempts (single attempt 27.6), Thinking 44.9
- SimpleQA, Thinking 13
- FACTS Grounding, Thinking 86.8
- MMMU single attempt, Thinking 72.9
- Vibe-Eval (Reka), Thinking 57.5
- MRCR v2 (8-needle) 128k (average), Thinking (1M pointwise 5.40) 30.6
- Global MMLU (Lite), Thinking 84.5
Gemini 2.5 Flash-Lite Jun 2025
Gemini 2.5 Flash-Lite.
Gemini 2.5 Flash-Lite
Jun 2025 snapshot Closed weights
- LiveCodeBench v5 34.3% #41 /47
- ProfBench 44.3% #49 /72
- StructEval 72% #18 /28
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 | |
|---|---|---|---|---|
| Vectara Hallucination Leaderboard (HHEM) | 2.90% | #43 of 148 | Official leaderboard | |
| FACTS Grounding | 86.8% | #5 of 15 | Lab model card | |
| LMArena (Elo) | 1,375 | #157 of 335 | Official leaderboard | |
| Global MMLU Lite | 84.5% | #8 of 16 | Lab model card | |
| Wer wird Millionär? LLM Benchmark | 700.0 | #50 of 77 | Official leaderboard | |
| SimpleQA | 13% | #45 of 60 | Lab model card | |
| Fiction.LiveBench | 47.2% | #44 of 57 | Fiction.live leaderboard, via Epoch AI | |
| MRCR v2 | 30.6% | #27 of 30 | Lab model card | |
| Humanity's Last Exam | 6.90% | #149 of 154 | Lab model card |
Math and science
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| GPQA Diamond | 66.7% | #196 of 302 | Lab model card | |
| DTBench | 62.8% | #131 of 180 | Official leaderboard | |
| AIME 2025 | 63.1% | #123 of 143 | Lab model card |
Coding
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| StructEval | 72% | #18 of 28 | Official leaderboard | |
| WeirdML | 35.2% | #93 of 112 | Official leaderboard | |
| LiveCodeBench v5 | 34.3% | #41 of 47 | Lab model card | |
| SWE-bench Verified | 44.9% | #138 of 155 | Lab model card | |
| Aider Polyglot | 27.1% | #28 of 30 | Lab model card |
Agents and tools
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| Galileo Agent Leaderboard v2 | 47% | #8 of 21 | Official leaderboard | |
| LisanBench | 122.3 | #111 of 133 | Official leaderboard |
Professional work
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| ProfBench | 44.3% | #49 of 72 | Official leaderboard |
Vision, audio and robotics
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| MMMU | 72.9% | #52 of 103 | Lab model card | |
| Vision Arena | 1,189 | #85 of 136 | Official leaderboard | |
| Vibe-Eval | 57.5% | #8 of 9 | Lab model card |
Safety and security
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| Lakera B3 (Backbone Breaker Benchmark) | 49.9% | #26 of 35 | Official leaderboard |
Other
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| Conceptual Reasoning Index | 25.1 | #127 of 151 | Official leaderboard | |
| CAIS Vision Capabilities Index | 38.1 | #46 of 53 | Official leaderboard | |
| ACCoRD | 33.4 | #140 of 152 | Official leaderboard | |
| CAIS Text Capabilities Index | 9.20 | #64 of 68 | Official leaderboard | |
| CAIS Risk Index | 77.1 | #67 of 67 | Official leaderboard |
Its lab's numbers put it at 127.6, 5.4 points below its ECI
The Self-Reported Index fits one score to the 12 capability results Google DeepMind reported for this model, on the scale of the Epoch Capabilities Index. Labs choose which benchmarks to show and how to run them, so read it as the lab's claim, not an independent measurement. The 90% interval runs from 125.2 to 130.0. How we compute it.
- FACTS Grounding 86.8
- Global MMLU Lite 84.5
- MMMU 72.9
- GPQA Diamond 66.7
- AIME 2025 63.1
- Vibe-Eval 57.5
- SWE-bench Verified 44.9
- LiveCodeBench v5 34.3
- MRCR v2 30.6
- Aider Polyglot 27.1
- SimpleQA 13
- Humanity's Last Exam 6.9
Google DeepMind's models over time
Google DeepMind's models in color, against every other model on the Epoch Capabilities Index, by release date.
Source: Epoch Capabilities Index, Epoch AI (CC BY 4.0)
Its launch post
The benchmarks the lab chose to headline, with the scores it gave.