Z-Image [fp8]

fp8 quantized Z-Image for ComfyUI using its quantization feature "TensorCoreFP8Layout".

• Scaled fp8 weights. higher precision than pure fp8.

• Also with "mixed precision". Important layers remain in bf16.

There is no "official" fp8 version for z-image from ComfyUI, so I made my own.

All credit belongs to the original model author. License is the same as the original model.

Base

Quantized Z-Image. Aka. the "base" version of z-image.

https://huggingface.co/Tongyi-MAI/Z-Image

Note: No hardware fp8, all calculations are still using bf16. This is intentional.

Rev 1.1: An updated version with better "mixed precision". More bf16 layers, so the file is bigger. Previous version will be deleted.

Turbo

Quantized Z-Image-Turbo

https://huggingface.co/Tongyi-MAI/Z-Image-Turbo

Rev1.1: An updated version with better "mixed precision". More bf16 layers, so the file is bigger. No hardware fp8. Previous version will be deleted.

v1: It contains calibrated metadata for hardware fp8 linear. If you GPU supports it, ComfyUI will use hardware fp8 automatically, which should be a little bit faster. More about hardware fp8 and hardware requirement, see ComfyUI TensorCoreFP8Layout.

Qwen3 4b

Quantized Qwen3 4b. Scaled fp8 + mixed precision. Early (embed_tokens, layers.[0-1]) and final (layers.[34-35]) layers are still in BF16.

https://huggingface.co/Qwen/Qwen3-4B