microsoft/Mage

Health v2 · maintenance only

Flags: no_releases young

Adoption not part of the score

1649 stars · 174 forks observed · 2026-09-21

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

Mage is a family of lightweight 4B-parameter multimodal models from Microsoft, including Mage-VL for image and video understanding and Mage-Flow for text-to-image generation and instruction-based editing. It is designed for research-friendly training, fine-tuning, and deployment on modest hardware.

Use cases

• run a small vision-language model for image and video understanding
• generate images from text prompts with a compact model
• edit images via natural language instructions
• fine-tune a multimodal model on a limited compute budget
• experiment with post-training of vision-language models
• build vertical-domain applications with multimodal understanding

When to choose

• you need a compact multimodal model that trains or fine-tunes on modest hardware
• you want both understanding and generation models from one consistent family
• you are doing controlled research experiments at a fixed parameter budget

When to avoid

• you need state-of-the-art quality regardless of model size
• you need a production-ready turnkey multimodal API rather than a research codebase
• you work outside Python/GPU environments

Facets

library · maturity active

machine-learning deep-learning llm-inference llm-training image-processing video-processing stable-diffusion artificial-intelligence machine-learning deep-learning computer-vision image-processing large-language-models python cross-platform multimodal vision-language-model text-to-image image-editing 4b-parameters research-models fine-tuning microsoft video natural-language-processing gpu linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="microsoft/Mage")