NVIDIA Nemotron Nano V2 VL
This work addresses vision-language tasks for applications like document and video analysis, but appears incremental as it builds on prior models and techniques.
The paper tackles the problem of real-world document understanding, long video comprehension, and reasoning by introducing Nemotron Nano V2 VL, which delivers significant improvements over the previous model across all vision and text domains.
We introduce Nemotron Nano V2 VL, the latest model of the Nemotron vision-language series designed for strong real-world document understanding, long video comprehension, and reasoning tasks. Nemotron Nano V2 VL delivers significant improvements over our previous model, Llama-3.1-Nemotron-Nano-VL-8B, across all vision and text domains through major enhancements in model architecture, datasets, and training recipes. Nemotron Nano V2 VL builds on Nemotron Nano V2, a hybrid Mamba-Transformer LLM, and innovative token reduction techniques to achieve higher inference throughput in long document and video scenarios. We are releasing model checkpoints in BF16, FP8, and FP4 formats and sharing large parts of our datasets, recipes and training code.