Gemma-4-31B-Glamour

Creative model

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Hourly Usage

Performance Metrics

Median Total Time

69.44s

Median TTFT

15.45s

Median Prefill TPS

1413.84

Median Gen TPS

9.33

Model Information

Context Size

262144

Quantization

r64

Engine

vllm

Creation Method

LoRA Finetune

Model Type

Gemma31B

Chat Template

Gemma4

Reasoning

Yes

Vision

Yes

Parameters

31B

Added At

7/19/2026


license: apache-2.0 base_model: google/gemma-4-31B-it tags:

  • web-design
  • code-generation
  • html
  • css
  • gemma-4
  • glamour pipeline_tag: text-generation datasets:
  • schneewolflabs/glamour-opus

Gemma4-Glamour-31B

A web-design generator fine-tuned from google/gemma-4-31B-it. Give it a natural-language brief; it returns a self-contained front-end as three fenced blocks — html, css, js.

Part of the Glamour project (Schneewolf Labs): an arena + synthetic-data pipeline for web-design generation and critique.

Training

  • Method: QLoRA SFT (r=64, α=32), merged to full weights.
  • Data: ~445 brief→implementation pairs. Trained on the Opus-authored subset only and evaluated on the held-out non-Opus subset (gemini, gpt, grok, glm, kimi, deepseek, haiku) — eval loss fell 0.67→0.42 across the run, improving even on designs authored by other models.
  • Checkpoint: this is the phase-1 generator, taken at an early-stop checkpoint (~step 56/84) on the eval plateau. Format adherence is still developing; treat as a v1.

Usage

from openai import OpenAI            # or any chat client
c = OpenAI(base_url="http://localhost:8000/v1", api_key="x")
c.chat.completions.create(
    model="glamour-31b",
    messages=[{"role": "user", "content": "Design a neobrutalist pricing page."}],
)

Output is html / css / js fenced blocks. A Q4_K_M GGUF runs in llama.cpp at ~10 tok/s on a single GB10.

License

Apache-2.0 (inherited from Gemma 4).