Agate
huggingface.co- Category
- AI Tools
- Rank
- No. 2803Tools index
- Pricing
- Open Source
- Type
- TOOL
- Date
About
Agate is a 260-million-parameter text-to-image model trained from scratch by LogoLabs in about 145 GPU-hours, splitting generation between a small transformer "thinker" that plans a coarse 16x16 region layout and a convolutional U-Net "renderer" that paints the image from that plan. It scores 0.550 on the GenEval benchmark, matching SDXL and beating SD 1.5, SD 2.1, and PixArt-alpha despite being much smaller, and generates an image in under two seconds on a consumer GPU or directly in the browser via WebGPU.
Why it made the leaderboard
A from-scratch 260M-parameter text-to-image model trained in under 13 hours that matches SDXL's GenEval score, showing a small, cheaply-trained model can reach competitive quality for narrow use cases like icon and logo generation.
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