- MMLU-Pro 83.5
- MMMU 77.7
- GPQA 77.3
- MMStar 74.9
- MathVista 81.5
- AIME2025 86
- MathVision 62.5
- IFEval 86.7
- SFE 44.3
- Physics 44
- SmolInstruct 51
- ChemBench 83.4
- MatBench 75
- MicroVQA 63.9
- ProteinLMBench 63.1
- MSEarthMCQ 65.7
- XLRS-Bench 55
Intern-S1
Intern-S1 places in the top three on CompassArena Multimodal.
Intern-S1
Open weights Flagship
- HiPhO 52.2% #21 /36
- Scientists' First Exam (SFE) 44.3% #5 /5
- SGI-Bench 28.1% #13 /15
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
Math and science
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| GPQA Diamond | 77.3% | #134 of 302 | Lab model card | |
| AIME 2025 | 86% | #70 of 143 | Lab model card | |
| Matbench | 75.0 | #1 of 2 | Lab model card | |
| HiPhO | 52.2% | #21 of 36 | Official leaderboard | |
| SGI-Bench | 28.1% | #13 of 15 | Official leaderboard | |
| ChemBench | 83.4% | #1 of 1 | Lab model card | |
| PHYSICS | 44% | #1 of 1 | Lab model card |
Vision, audio and robotics
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| MMMU | 77.7% | #15 of 136 | Official leaderboard | |
| CompassArena Multimodal | 1,155 | #2 of 8 | Official leaderboard | |
| XLRS-Bench | 55% | #1 of 4 | Lab model card | |
| MathVista | 81.5% | #27 of 70 | Lab model card | |
| MSEarth | 65.7% | #1 of 2 | Lab model card | |
| MMStar | 74.9% | #21 of 36 | Lab model card | |
| MicroVQA | 63.9% | #2 of 3 | Lab model card | |
| MATH-Vision (MathVision) | 62.5% | #38 of 51 | Lab model card | |
| Scientists' First Exam (SFE) | 44.3% | #5 of 5 | Lab model card |
Safety and security
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| LiveSecBench | 31.5 | #25 of 34 | Official leaderboard | |
| SMolInstruct | 51% | #2 of 2 | Lab model card | |
| ProteinLMBench | 63.1% | #1 of 1 | Lab model card |
Its lab's numbers put it at 137.8, number 196 of 404
The Self-Reported Index fits one score to the 8 capability results Shanghai AI Lab 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 135.1 to 140.5. How we compute it.
- IFEval 86.7
- AIME 2025 86
- MMLU-Pro 83.5
- MathVista 81.5
- MMMU 77.7
- GPQA Diamond 77.3
- MMStar 74.9
- MATH-Vision (MathVision) 62.5
Its lab's numbers next to 2 leaderboards
Where the benchmark's own leaderboard, or Epoch AI's run, also has this model. Gaps mostly come from different harnesses, effort levels and task subsets. Every pair.
Its launch post
The benchmarks the lab chose to headline, with the scores it gave.
Its system card
Every result in the longer documents the lab published with it.
Capabilities
- MMLU-Pro 83.5
- GPQA Diamond 77.3
- AIME 2025 86
- IFEval 86.7
- MathVista 81.5
- MMMU 77.7
- MATH-Vision (MathVision) 62.5
- MMStar 74.9
- SMolInstruct 51
- ChemBench 83.4
- Matbench 75
- ProteinLMBench 63.1
- Scientists' First Exam (SFE) 44.3
- PHYSICS 44
- MicroVQA 63.9
- MSEarth 65.7
- XLRS-Bench 55