AI BriefingQwen-Image-2.1-Uncensored-GGUF: Run Qwen-Image 2.1 Locally with 4.6GB VRAM
abenzerps/Qwen-Image-2.1-Uncensored-GGUF
About the project
This build quantizes the original weights of Qwen-Image 2.1 into GGUF format to enable local execution. Safety filters and content censorship have been removed, allowing the generation of adult or sensitive images without refusal based on the prompt.
It operates via the ComfyUI-GGUF node. The Q4_K_M quantized file, at approximately 4.6GB, offers the most balanced performance. Applying a configuration that offloads the text encoder to system RAM can save 9–17GB of GPU VRAM.
The Q8_0 version currently encounters tensor shape mismatch errors, so using Q4_K_M, Q5_K_M, or Q6_K is recommended. Text encoder and VAE files are also included, allowing immediate integration into workflows without separate downloads.
abenzerps/Qwen-Image-2.1-Uncensored-GGUF
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