Z-Image-Turbo W4A8

W4A8 (4-bit weight, 8-bit activation) quantized weights for Z-Image-Turbo, made for ComfyUI using ComfyUI's native asym_w4a8_int8 quantized-diffusion format (Comfy Kitchen).

Both the diffusion model and the Qwen3-4B text encoder are quantized, so the whole pipeline fits in low VRAM.

Files

File Size Notes
z_image_turbo_w4a8.safetensors 3.5 GB Diffusion model, asym_w4a8_int8, group_size 16 + ConvRot
qwen_3_4b_w4a8.safetensors 2.8 GB Qwen3-4B text encoder, asym_w4a8_int8, group_size 16 + ConvRot

Original BF16 sizes: diffusion 12.3 GB, text encoder 8.0 GB.

Usage (ComfyUI)

Place the files in your ComfyUI models directory:

ComfyUI/
β”œβ”€β”€ models/
β”‚   β”œβ”€β”€ diffusion_models/
β”‚   β”‚   └── z_image_turbo_w4a8.safetensors
β”‚   β”œβ”€β”€ text_encoders/
β”‚   β”‚   └── qwen_3_4b_w4a8.safetensors
β”‚   └── vae/
β”‚       └── flux1-vae.safetensors

Then use the standard Z-Image-Turbo text-to-image workflow with a Load Diffusion Model node pointed at z_image_turbo_w4a8.safetensors and a Load CLIP node pointed at qwen_3_4b_w4a8.safetensors.

Both files are detected automatically by ComfyUI (.comfy_quant metadata keys); no custom nodes are required. The text encoder must be loaded through the Qwen3-4B / Z-Image CLIP path (it does not need the pooled output).

Quality & Speed

Verified on an 8 GB VRAM GPU (RTX 4060 Laptop) at 1024x1024, 8 sampling steps:

Model Steps Sample time
BF16 8 ~14 s
W4A8 (this repo) 8 ~7 s
int8_convrot (official) 8 ~6 s

Image quality is visually identical between BF16, W4A8 and the official int8_convrot checkpoint.

Quantization format

Per quantized Linear layer the file stores:

  • <key>.weight β€” int8, ConvRot-rotated packed int4 [N, K/2]
  • <key>.weight_s_rel β€” fp8 e4m3fn group scale [N, K/group_size]
  • <key>.weight_s_channel β€” fp32 channel scale [N]
  • <key>.weight_codebook β€” fp32 Lloyd-Max codebook [16]
  • <key>.comfy_quant β€” uint8 JSON {"format": "asym_w4a8_int8", "group_size": 16, "convrot_groupsize": ...}

1D norms, biases, the embedding table and cap_embedder.1 are kept in BF16.

Downloads last month
17
Inference Providers NEW
This model isn't deployed by any Inference Provider. πŸ™‹ Ask for provider support

Model tree for CuTIsolation/Z-Image-Turbo-W4A8

Finetuned
(143)
this model