OpenGVLab/VisionLLM

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1153 stars · 63 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

VisionLLM is a series of open-source multimodal large language models from OpenGVLab that unify vision-centric tasks under language instructions. VisionLLM v2 is a generalist model supporting hundreds of vision-language tasks spanning visual understanding, perception, and generation.

Use cases

• run a multimodal LLM for image understanding and captioning
• perform open-ended object detection with language instructions
• generate images from a vision-language model
• research unified vision and language task frameworks
• evaluate a generalist model across hundreds of vision-language tasks
• build instruction-driven visual perception pipelines

When to choose

• you need a single generalist model covering visual understanding, perception, and generation
• you want open-ended, instruction-driven object detection or vision tasks
• you are reproducing or extending the VisionLLM NeurIPS papers

When to avoid

• you need a lightweight production vision API rather than research code
• you lack GPU resources for large multimodal models
• you need a narrowly specialized detection model with minimal overhead

Facets

library · maturity active

machine-learning deep-learning computer-vision llm-inference image-processing computer-vision large-language-models artificial-intelligence deep-learning python multimodal vision-language-model object-detection generalist-model research-code image-generation gpu linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="OpenGVLab/VisionLLM")