Model card
Intern-S1-Pro.
Shanghai AI LabLarge language model1 current SOTA
Added from Papers with Code MMLU-Pro refresh on 2026-05-19.
§ 02 · Benchmarks
Every benchmark Intern-S1-Pro has a recorded score for.
| # | Benchmark | Area · Task | Metric | Value | Rank | Date | Source |
|---|---|---|---|---|---|---|---|
| 01 | OCRBench v2 | Computer Vision · General OCR Capabilities | chinese-score | 60.6% | #1 | — | source ↗ |
| 02 | OCRBench v2 | Computer Vision · General OCR Capabilities | english-score | 60.1% | #2 | — | source ↗ |
| 03 | Tau2-Bench | Agentic AI · Tool Use | accuracy | 80.9% | #5 | — | source ↗ |
| 04 | AIME 2025 | Reasoning · Mathematical Reasoning | accuracy | 93.1% | #6 | — | source ↗ |
| 05 | MMLU-Pro | Reasoning · Commonsense Reasoning | accuracy | 86.6% | #9 | 2026-03-26 | source ↗ |
| 06 | MMLU-Pro | Reasoning · Commonsense Reasoning | accuracy | 86.6% | #9 | — | source ↗ |
| 07 | LiveCodeBench | Computer Code · Code Generation | pass-1 | 74.3% | #12 | — | source ↗ |
| 08 | MMMU-Pro | Multimodal · Visual Question Answering | accuracy | 72.8% | #17 | — | source ↗ |
Rank column shows this model’s position vs all other models scored on the same benchmark + metric (competitors after the slash). #1 in red means current SOTA. Sorted by rank, then newest result.
§ 03 · Strengths by area
Where Intern-S1-Pro actually performs.
§ 04 · Papers
1 paper with results for Intern-S1-Pro.
- 2026-03-26· 7 results
Intern-S1-Pro: Scientific Multimodal Foundation Model at Trillion Scale
§ 05 · Related models
Other Shanghai AI Lab models scored on Codesota.
§ 06 · Sources & freshness
Where these numbers come from.
pwc-dump
7
results
paperswithcode
1
result
0 of 8 rows marked verified.