ModelTC/LightX2V-Qwen-Image-Lightning
Distilled Qwen-Image model versions that achieve 4-step inference for text rendering image generation.
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This repository releases distilled versions of the Qwen-Image text-rendering image generation model. The distilled models achieve significantly faster inference by reducing sampling steps to 4 while preserving the original model’s capability for complex text rendering. Releases include fp32, bf16, and fp8 precision variants, along with LoRA adapters that can be combined with base models for deployment.
Frequently asked
- What is ModelTC/LightX2V-Qwen-Image-Lightning?
- Distilled Qwen-Image model versions that achieve 4-step inference for text rendering image generation.
- Is LightX2V-Qwen-Image-Lightning open source?
- Yes — ModelTC/LightX2V-Qwen-Image-Lightning is open source, released under the Apache-2.0 license.
- What language is LightX2V-Qwen-Image-Lightning written in?
- ModelTC/LightX2V-Qwen-Image-Lightning is primarily written in Python.
- How popular is LightX2V-Qwen-Image-Lightning?
- ModelTC/LightX2V-Qwen-Image-Lightning has 1.3k stars on GitHub.
- Where can I find LightX2V-Qwen-Image-Lightning?
- ModelTC/LightX2V-Qwen-Image-Lightning is on GitHub at https://github.com/ModelTC/LightX2V-Qwen-Image-Lightning.