Vision AI Models

Vision AI models are models that interpret visual data such as images, video, and documents. They include vision language models that answer questions about images in natural language, and specialized computer vision models for tasks like object detection, OCR, classification, and segmentation.

All major frontier models accept images: GPT-5.6, Claude Opus 4.7, and Gemini 3.1 Pro, plus open-weight options like Qwen3 VL, Gemma 4, and Pixtral. This page lists 100+ vision-capable models you can test on your own image right now.

Yes. Many models on this page are free and open-source, including CLIP and Florence-2 (MIT), RF-DETR and Qwen3 VL (Apache 2.0). They run with no API costs when self-hosted via Roboflow Inference. Every model here is also free to try in the Playground.

Computer vision models are the specialized family within vision AI: models built and trained for a specific visual task. Vision AI also includes multimodal language models that handle visual tasks through prompting. If you want to train a model on your own data, see the Roboflow model library; this page is for trying hosted models.