Qwen-Image-2.1 works great in Unsloth Desktop via INT8 / FP8 and GGUFs! Pinned offloading to RAM also allows INT8 / FP8 to fit in under 6-8GB of VRAM, and is still relatively fast!
We also made some dynamic GGUFs for it as well!
Qwen-Image-2.1 runs locally in Unsloth Desktop via INT8, FP8, GGUF
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Daniel Han says Qwen-Image-2.1 works in Unsloth Desktop through INT8, FP8, and GGUF builds, with Unsloth also releasing dynamic GGUFs for it. Pinned RAM offloading lets INT8 and FP8 fit under 6–8GB of VRAM while remaining relatively fast. The linked Unsloth post says the 7B model runs on 12GB VRAM and performs on par with Nano Banana 2.0.
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@danielhanchen
Qwen-Image-2.1 can now run locally on 12GB VRAM with Unsloth GGUFs! 🖼️ The 7B model performs on par with Nano Banana 2.0. For higher quality, you can also run Dynamic FP8 on just 6GB of VRAM via offloading. GGUF: https://huggingface.co/unsloth/Qwen-Image-2.1-GGUF Guide: https://unsloth.ai/docs/models/qwen-image-2.1
Source: Daniel Han · x.comPublished · added here