qingy2024 / uigen-t3-preview-32b-GGUF

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Model's Last Updated: June 09 2025

Introduction of uigen-t3-preview-32b-GGUF

Model Details of uigen-t3-preview-32b-GGUF

UIGEN-T3 — Advanced UI Generation with Hybrid Reasoning

Tesslate’s next-gen UI model, built for thoughtful design.


UIGEN-T3 UI Screenshot 1 UIGEN-T3 UI Screenshot 2 UIGEN-T3 UI Screenshot 2 UIGEN-T3 UI Screenshot 3 UIGEN-T3 UI Screenshot 4 UIGEN-T3 UI Screenshot 5 UIGEN-T3 UI Screenshot 6
Demos

Explore New UI generations: 📂 https://uigenoutput.tesslate.com


Join our Discord: https://discord.gg/GNbWAeJ4 Our Website: https://tesslate.com

Quick Information
  • UI generation model built on Qwen3 architecture
  • Supports both components and full web pages
  • Hybrid reasoning system : Use /think or /no_think modes
  • Powered by UIGenEval , a first-of-its-kind benchmark for UI generation
  • Released for research, non-commercial use. If you want to use it commercially, please contact us for a pilot program.

Model Details
  • Base Model : Qwen/Qwen3-32B
  • Reasoning Style : Hybrid ( /think and /no_think )
  • Tokenizer : Qwen default, with design token headers
  • Output : Components + Full pages (with <html> , <head> )
  • Images : User-supplied or placehold.co – no images in the dataset due to licensing concerns.
  • License : Research only (non-commercial). Contact us for enterprise use cases.

Reasoning System

UIGEN-T3 was trained using a pre/post reasoning model architecture .

You can explicitly control the reasoning mode:

  • /think → Enables guided reasoning with layout analysis and heuristics.
  • /no_think → Faster, raw code generation.

Outputs also include design tokens at the top of each generation for easier site-wide customization.


Inference Parameters

Please use 20k context length to get the best results if using reasoning.

Parameter Value
Temperature 0.6
Top P 0.95
Top K 20
Max Tokens 40k+

Evaluation: UIGenEval Framework

UIGenEval is our internal evaluation suite, designed to bridge the gap between creative output and quality assurance. (Learn more in our upcoming paper: "UIGenEval: Bridging the Evaluation Gap in AI-Driven UI Generation" - August, 2025)

UIGenEval evaluates models across four pillars:

  1. Technical Quality — Clean HTML, CSS structure, semantic accuracy.
  2. Prompt Adherence — Feature completeness and fidelity to instructions.
  3. Interaction Behavior — Dynamic logic hooks and functional interactivity.
  4. Responsive Design — Multi-viewport performance via Lighthouse, Axe-core, and custom scripts.

This comprehensive framework directly informs our GRPO reward functions for the next release.


Example Prompts to Try
  • make a google drive clone
  • build a figma-style canvas with toolbar
  • create a modern pricing page with three plans
  • generate a mobile-first recipe sharing app layout

Use Cases
Use Case Description
Startup MVPs Quickly scaffold UIs from scratch with clean code.
Design-to-Code Transfer Figma (coming soon) → Code generation.
Component Libraries Build buttons, cards, navbars, and export at scale.
Internal Tool Builders Create admin panels, dashboards, and layout templates.
Rapid Client Prototypes Save time on mockups with production-ready HTML+Tailwind outputs.

Limitations
  • No Bootstrap support (planned).
  • Not suited for production use — research-only license .
  • Responsive tuning varies across output complexity.

Roadmap
Milestone Status
Launch Tesslate Designer 2 days
Figma convert
Bootstrap & JS logic
GRPO fine-tuning
4B draft model release Now

Technical Requirements
  • GPU : ≥24GB VRAM for 32B inference on GGUF.
  • Libraries : transformers , torch , peft .
  • Compatible with Hugging Face inference APIs and local generation pipelines.

Community & Contribution

Citation
@misc{tesslate_UIGEN-T3,
  title={UIGEN-T3: Hybrid Reasoning for Robust UI Generation on Qwen3},
  author={Tesslate Team},
  year={2025},
  publisher={Tesslate},
  note={Non-commercial Research License},
  url={https://huggingface.co/tesslate/UIGEN-T3}
}

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