Best Visual Question Answering Models

Visual question answering (VQA) is the task of answering a free-form question about an image, which forces a model to combine perception with language understanding and reasoning. A single question may require recognizing objects, reading text inside the image, counting, comparing positions, or chaining several of those steps, and the output is text rather than a fixed label or box. Modern vision language models handle VQA zero-shot: the image and question go in together and the model generates the answer. Benchmarks score exact-match or judged answer quality across question types. VQA drives document and screenshot understanding, assistive technology for low-vision users, and ad hoc extraction like "what is the total on this receipt?". This page lists 69 visual question answering models, including 30 open-weight options you can self-host; 62 of them run live in the Playground so you can test them on your own images.

On our visual reasoning benchmark (23 models tested, updated Jul 28, 2026), Gemini 3.5 Flash by Google currently scores highest at 84.1%. The full ranking is on our evals page. For fixed categories in production, a model fine-tuned on your own data still often wins.

Yes. 30 of the 69 visual question answering models here are open-weight (for example Kimi K3, Gemma 4 12B, and Qwen3.6 27B), free to self-host under their licenses (Modified MIT, Apache 2.0, and MIT).

Yes. You can run 62 of them in the Roboflow Playground for free. Upload an image and compare the models' output side by side, no setup required.