Vision AI Models
Explore vision AI models from every major lab and try them on your own images: object detection, OCR, classification, captioning, segmentation, and more. Every model is free to try in the Playground, many are free and open-source to deploy, and new models are added as they ship.
Explore Vision AI Models
124 models · 25 tasks · latest model added July 27, 2026
Open-Source Vision AI Models
84 models with downloadable weights you can self-host under their licenses (Modified MIT, Apache 2.0, and MIT). 34 run live in the Playground through hosted APIs, so self-hosting is optional.
Kimi K3Moonshot AI NEW | 2.8T | Modified MIT | Jul 2026 | |
Gemma 4 12BGoogle NEW | 12B | Apache 2.0 | Jun 2026 | |
Qwen3.6 27BQwen | 27B | Apache 2.0 | Apr 2026 | |
Qwen3.6 35B A3BQwen | 35B total, 3B active | Apache 2.0 | Apr 2026 | |
Gemma 4 26B A4BGoogle | 25.2B | Apache 2.0 | Apr 2026 | |
Gemma 4 31BGoogle | 31B | Apache 2.0 | Apr 2026 | |
GLM-OCRZ.ai | 0.9B | MIT | Mar 2026 | |
Qwen3.5 9bQwen | 9B | Apache 2.0 | Mar 2026 |
Vision AI Models via API
40 proprietary models where the weights aren't downloadable: access is through each provider's API and billed by them. Try all of them free in the Playground.
Qwen3.7 FlashQwen NEW | $0.030 | $0.13 | 1M | Jul 2026 | |
Claude Opus 5Anthropic NEW | $5.00 | $25.00 | 1M | Jul 2026 | |
Gemini 3.5 Flash-LiteGoogle NEW | $0.30 | $2.50 | 1.0M | Jul 2026 | |
Gemini 3.6 FlashGoogle NEW | $1.50 | $7.50 | 1M | Jul 2026 | |
GPT-5.6 LunaOpenAI NEW | $0.50 | $3.00 | 1.5M | Jul 2026 | |
GPT-5.6 SolOpenAI NEW | $5.00 | $30.00 | 1.5M | Jul 2026 | |
GPT-5.6 TerraOpenAI NEW | $1.25 | $7.50 | 1.1M | Jul 2026 | |
Muse Spark 1.1Meta NEW | $1.25 | $4.25 | 1.0M | Jul 2026 |
What Are Vision AI Models?
Vision AI models are models that understand visual input: images, video, and documents. They span two families. Vision language models (GPT, Claude, Gemini, Qwen VL) reason about images with natural language and handle open-ended tasks zero-shot. Specialized computer vision models (RF-DETR, SAM 3, CLIP, Florence-2) are built for one task and run faster, cheaper, and often more accurately on it in production.
Which family do you need?
Prototype with a VLM to validate the task, then move to a specialized or fine-tuned model when classes are fixed and volume grows. For object detection, that usually means training RF-DETR on your own data. In a Roboflow Workflow you can chain both: a detector localizes, a VLM interprets only the crops that matter.
Frequently Asked Questions About 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.
This page lists 100+ vision AI models from Google, OpenAI, Anthropic, Meta, Qwen, Mistral, and more, covering object detection, OCR, classification, captioning, and segmentation. Every model can be tested on your own image in the browser and compared head to head before you commit to one.