Daniel Han
@danielhanchen
Building @UnslothAI • Making open-source LLMs faster, better & more accessible • YC S24 • ex-NVIDIA ML
Joined April 2016
2K Following 36.3K Followers
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!
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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:
Guide:
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