- MMMU Val with chatGPT as a judge 48.2
- AI2D 85
- ChartQA 86.3
- InfoVQA Val 77.4
- OCRBench 839 (out of 1000) 83.9
- OCRBenchV2 English 60.1 / Chinese 37.9 60.1
- DocVQA val 91.2
- VideoMME* (1 tile per image) 54.7
Llama-3.1-Nemotron-Nano-VL-8B-V1
Llama-3.1-Nemotron-Nano-VL-8B-V1.
8
Benchmarks with a score
0
Ranked first, out of five or more models
0
In the top three
NVIDIA Jun 2025 Llama-3.1-Nemotron-Nano-VL-8B-V1
Open weights Small
No Epoch Capabilities Index score yet
- OCRBench v2 56.4% #13 /65
- Video-MME 54.7% #41 /42
- AI2D 85% #33 /44
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.
Vision, audio and robotics
| Benchmark | Score | Rank | Source | |
|---|---|---|---|---|
| OCRBench v2 | 56.4% | #13 of 65 | Official leaderboard | |
| ChartQA | 86.3% | #19 of 37 | Model card | |
| InfographicVQA | 77.4% | #14 of 22 | Model card | |
| DocVQA | 91.2% | #24 of 33 | Model card | |
| AI2D | 85% | #33 of 44 | Model card | |
| OCRBench | 83.9% | #25 of 28 | Model card | |
| MMMU | 48.2% | #93 of 97 | Model card | |
| Video-MME | 54.7% | #41 of 42 | Model card |
Its launch post
The benchmarks the lab chose to headline, with the scores it gave.