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LatestThesysdev1
ThesysdevText / LLM

OUI-1: A Gemma-based diffusion model for generative UI

Thesys releases an experimental diffusion language model aimed at turning prompts into user interfaces, built atop Google's Gemma.

Sep 7, 2026
UpdateGemma
OUI-1

A new model called OUI-1 has appeared on Hugging Face, positioned as a diffusion language model for generative user-interface tasks. Published by the thesysdev account and built on Google's Gemma foundation, it is released under the Gemma license as an initial, minor release (model card).

The premise is what makes it notable. Most text models generate tokens left to right; a diffusion approach instead refines an entire output in parallel across denoising steps. Pairing that technique with a UI-generation goal suggests an interest in producing structured layouts and code where the whole design is considered at once rather than assembled sequentially.

What we know

  • Base: Gemma, Google's open model family
  • Type: diffusion language model, text and code
  • Purpose: generative UI tasks
  • License: Gemma

Several key details are not yet published, including parameter count, context length, and benchmark results. Without those figures it is hard to judge how OUI-1 compares to conventional code and UI generators, and buyers should treat it as an early experiment rather than a finished tool.

Why it matters: generative UI is a fast-growing niche, and applying diffusion to it is an unusual bet. If the approach holds up, parallel generation could offer a different speed-and-coherence tradeoff for building interfaces from natural language. For now, OUI-1 is worth watching as a signal of where open, Gemma-derived tooling is heading.

Sources

  • thesysdev/OUI-1

    Hugging Face

    Visit
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Get the model

Hugging Face

Specs

Context window262K tokens
Size51.6 GB
PrecisionBF16
ArchitectureDiffusionGemmaForBlockDiffusion
LicenseGEMMA
Downloads922
Likes150

Can you run it?

Runs on a 24 GB GPU at 4-bit.

  • BF16 (as published)

    80 GB GPU (A100 / H100) · 128 GB Mac Studio

    54.6 GB
  • 8-bit

    32 GB GPU (RTX 5090) · 48 GB Mac

    30.4 GB
  • 4-bit

    24 GB GPU (RTX 3090 / 4090) · 32 GB Mac

    18.5 GB
Your machine
GGUF builds
  • KV cache sized for 8,192 tokens of context; longer prompts need proportionally more.

Based on Hugging Face weights metadata. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

CodeText / LLM

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