DeepSeek VL2
Vision-language model for OCR, documents, charts, and visual Q&A.
- Dynamic slicing for high-resolution images.
- Strong OCR and document understanding performance.
- Vision-language reasoning with efficient inference.
DeepSeek VL2 is a vision-language model built for OCR, document analysis, and high-resolution visual reasoning. It combines a strong vision encoder with a language backbone and uses dynamic tiling to preserve fine-grained details in large images.
Architecture notes describe a visual encoder + adapter pipeline feeding into a MoE language decoder, plus multi-head latent attention to reduce KV cache growth on long sequences. Reported variants emphasize a large total parameter count with a much smaller active set, helping keep inference efficient.
VL2 shines on screenshots, charts, and complex documents where text and layout matter. It is a strong companion to V3.1 for end-to-end doc pipelines and to Janus-Pro-7B for generation-heavy multimodal flows.
- High-resolution OCR and document parsing.
- Dynamic tiling for detailed visuals.
- MoE efficiency with smaller active params.
- Chart and screenshot reasoning.
- Production document-processing pipelines.