We present LLaVA-OneVision, a family of open large multimodal models (LMMs) developed by consolidating our insights into data, models, and visual representations in the LLaVA-NeXT blog series. Our experimental results demonstrate show that LLaVA-OneVision is the first single model that can simultaneously push the performance boundaries of open LMMs in three important computer vision scenarios: single-image, multi-image and video scenarios. Importantly, the design of LLaVA-OneVision allow strong transfer learning across different modalities/scenarios, yielding new emerging capabilities. In particular, strong video understanding and cross-scenario capabilities are demosntrated through task transfer from images to videos.

We open-source the LLaVA-OneVision to facilitate future development of LMM in the community.

• Training Code: Cook a SOTA model with our released training code

• 🤗 Checkpoints: Access pre-trained model checkpoints (0.5B, 7B, 72B)

• 🤗 LLaVA-OneVision Data: Explore training datasets for Single-Image and OneVision stages

• 🎨 Live Demo: Try it out yourself!