UIGEN-T3-8B-Preview-GPTQ

AlphaGaO/UIGEN-T3-8B-Preview-GPTQ

UIGEN-T3-8B-Preview-GPTQ is a text generation model from AlphaGaO. Use it when you need the model to write or continue text. It is set up for transformers.

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

Downloads · 30 days

19% of all-time downloads

All-time downloads

Public

Parameters

8.2B

6.1 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors6.1 GB · 100%

Parameter types

How the weights are stored.

I326.9B · 85%

Try a prompt

Base models

Qwen/Qwen3-8B

Model card

From the Hugging Face model README

UIGEN-T3 — Advanced UI Generation with Hybrid Reasoning

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

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/Qwen3-8B
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:

Technical Quality — Clean HTML, CSS structure, semantic accuracy.
Prompt Adherence — Feature completeness and fidelity to instructions.
Interaction Behavior — Dynamic logic hooks and functional interactivity.
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: ≥16GB VRAM for 8B inference on GGUF.
Libraries: transformers, torch, peft.
Compatible with Hugging Face inference APIs and local generation pipelines.

Community & Contribution

Join our Discord: https://discord.gg/GNbWAeJ4
Chat about AI, design, or model training.
Want to contribute UIs or feedback? Let’s talk!

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}
}

Task: Text Generation
Library: transformers
Type: qwen3
Languages: en
Created: Jun 10, 2025
Updated: Jun 10, 2025