README.md

metadata

title: Viggle Turbo for Qwen-Image-2.1
emoji: ⚡
colorFrom: indigo
colorTo: purple
sdk: gradio
sdk_version: 5.50.0
python_version: 3.12.12
app_file: app.py
pinned: false
license: other
license_name: qwen-research
license_link: ./LICENSE
short_description: 6-step Qwen-Image-2.1, T2I + editing, vs-base comparison
models:
  - Viggle/Qwen-Image-2.1-viggle-turbo
  - Qwen/Qwen-Image-2.1
tags:
  - text-to-image
  - image-editing
  - distillation

Viggle Turbo v0.3 — 6-step Qwen-Image-2.1

A distilled Qwen-Image-2.1 that generates and edits images in 6 steps with no classifier-free guidance, about 5× faster than the 40-step base model. On most prompts it is hard to tell apart from the base model; small, dense text and complicated edits (multi-reference composition, face swaps, identity-preserving edits) can still fall short of it.

v0.3 (2026-09-29): at 6 steps, less grain than v0.2.1 and a little softer on fine texture. We think 6 steps is close to its capacity: every further gain we found cost something elsewhere. The new 9-step setting runs 7 turbo steps and lets the base model finish the last two: finer detail and small text right more often, at about 1.4–1.5× the time of 6 steps. Weights, numbers and ComfyUI workflows are on the model card.

Generate: leave References empty for text-to-image, or add one to six images for editing, composition or style transfer; the prompt refers to them as image 1, image 2, … in the order they were added. Steps runs from 3 to 9, 6 is the default. The Examples rows are pre-rendered by this exact app; clicking one loads its prompt, references, settings and seed. The reference photos woman1/cat_window/bird.webp and the three-reference prompt come from the black-forest-labs/flux-klein-9b-kv Space; the qwen_* rows come from the Qwen/Qwen-Image-2.1 Space.

Comparison (no GPU needed): 32 of the 37 examples of the Qwen/Qwen-Image-2.1 Space, pre-rendered with this model and with the base model in 40 steps (same prompt, inputs and seed 42, prompt enhancement off, one sample each), in an image slider, plus Qwen's own API output where their Space ships one.

Prompt enhancement

Enhance prompt: Auto (default) rewrites prompts shorter than 30 tokens, On always rewrites, Off never does. The rewrite is done by DeepSeek V4.1 Flash through OpenRouter, prompted with shortened versions of the system prompts published with Qwen/Qwen-Image-2.1-PE-T2I / -PE-I2I. The rewritten prompt is shown under Prompt sent to the model; if the call fails, the original prompt is used. The rewrite can add things the request did not ask for, on-image text included, so switch it Off when the wording matters.

Privacy. When enhancement runs, the prompt and the reference images (downscaled to at most 0.5 MP) are sent to OpenRouter and the provider it routes the request to; the request only allows providers that neither train on nor retain the data. With Off, nothing leaves the Space.

Running it

Environment: LORA_FILE (default the v0.3 r256 adapter; the v0.2.1 and v0.2 adapters in the model repo also work), STUDENT_REPO, BASE_MODEL_ID, HF_TOKEN (read scope, needed only while the model repo is private), OPENROUTER_API_KEY (prompt enhancement; without it every prompt is sent as written). The app needs ZeroGPU xlarge (96 GB): the largest calls do not fit on the 48 GB card untiled, and tiling the VAE breaks edits.

License

The base model is released under the Qwen RESEARCH LICENSE AGREEMENT — non-commercial: research or evaluation purposes only. This distilled derivative and this demo inherit that restriction. Commercial use requires a separate license from Alibaba (model-business@notice.qwencloud.com). See NOTICE for the required attribution.

Qwen is licensed under the Qwen RESEARCH LICENSE AGREEMENT, Copyright (c) 2026 Hangzhou Tongyi Laboratory Technology Co., Ltd. All Rights Reserved.