88Z AI, 19 August — Microsoft has released the open-source multimodal model family Mage, covering core capabilities in visual understanding and image generation. Mage-VL significantly reduces visual tokens via Codec-Native encoding, boosting video inference speed and enabling real-time streaming processing. Mage-Flow focuses on high-resolution image generation and editing, achieving rapid output on a single A100 GPU through efficient sampling in its Turbo version, while supporting diverse resolution requirements.
At a glance
- Mage-VL uses Codec-Native encoding to cut visual tokens by 75% and boost video inference speed by 3.5x
- Mage-Flow Turbo requires only 4 sampling steps, generating images in 0.6 seconds on a single A100 GPU
The update
Microsoft has officially open-sourced Mage, a multimodal model family with 4 billion parameters. The series primarily includes Mage-VL for streaming video and image understanding, and Mage-Flow for image generation and editing. Mage-VL introduces Codec-Native encoding technology, reducing visual tokens by 75 percent, increasing video inference speed by 3.5 times, and enabling real-time streaming understanding. Mage-Flow supports text-to-image generation and instruction editing at any native resolution between 512 and 2048. Its Turbo version requires only four sampling steps and can generate an image in 0.6 seconds on a single A100 GPU, demonstrating efficient generation performance.
Sources & editorial note
This article is an AI-assisted synthesis by 88Z AI based on the public sources below. Product claims and availability are attributed to their publishers. It does not represent independent testing or first-hand reporting.
- MageSource published
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