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Can the Arc B580 12 GB run Z-Image Turbo?

Yes, but only just: Q8_0 leaves 2.8 GB free on the Arc B580 12 GB.

Image model · 6B12 GB GDDR6 · 192-bit · 456 GB/s · BattlemageData 2026-10-01
Runs well
Yes.

Take Q8_0 (7.2 GB). In use it comes to about 9.2 GB, with 2.8 GB left over on 12 GB.

Best fileQ8_0
File size7.2 GB
VRAM needed~9.2 GB
System RAM32 GB+
Memory map · Arc B580 12 GB9.2 GB / 12 GB
06 GB12 GB
Weights Q8_0 · 7.2 GBWorking memory · 1.2 GBReserve · 0.8 GBFree · 2.8 GB

01What to download

PartFileFolderSize
Modelz-image-turbo-Q8_0.gguf
Q8_0 · unsloth/Z-Image-Turbo-GGUF
models/unet7.2 GBDownload →
Text encoderqwen_3_4b_fp8_mixed.safetensors
Qwen3 4B FP8 · Comfy-Org/z_image_turbo
models/text_encoders5.6 GBDownload →
VAEae.safetensors
FLUX.1 VAE (ae) · Comfy-Org/z_image_turbo
models/vae0.3 GBDownload →
Total download · keep about the same free on disk13.2 GB

Alternatives: Qwen3 4B BF16 (8.0 GB). Sizes from Hugging Face, 2026-10-01.

Free ComfyUI workflow, tested on my RTX 5060 Ti: 16-bit workflow (.json). Drag the file into ComfyUI. All workflows →

02Every Z-Image Turbo file on 12 GB

FileSizeNeededOn this cardQualityDownload
16-bit
SAFETENSORS · Comfy-Org
12.3 GB14.3 GB2.3 GB too bigthe original weightsHugging Face →
Q8_0 ←
GGUF · unsloth
7.2 GB9.2 GBfits · 2.8 GB sparepractically identical to the originalHugging Face →
INT8
SAFETENSORS · Comfy-Org
6.2 GB8.2 GBfits · 3.8 GB sparepractically identical to the originalHugging Face →
Q6_K
GGUF · unsloth
5.9 GB7.9 GBfits · 4.1 GB sparevery close to the originalHugging Face →
Q5_K_M
GGUF · unsloth
5.6 GB7.6 GBfits · 4.4 GB spareclose; small differences in fine detailHugging Face →
Q4_K_M
GGUF · unsloth
5.0 GB7.0 GBfits · 5.0 GB sparegood; some loss in fine detail and textHugging Face →
Q3_K_M
GGUF · unsloth
4.2 GB6.2 GBfits · 5.8 GB sparenoticeable loss of detailHugging Face →
Q2_K
GGUF · unsloth
3.6 GB5.6 GBfits · 6.4 GB spareheavy loss; a last resortHugging Face →

“Needed” adds 1.2 GB of working memory for Z-Image Turbo and a 0.8 GB reserve. Sizes 2026-10-01.

03Measured and reported results

Nobody has sent measured numbers for this pair yet. If you run Z-Image Turbo on a Arc B580 12 GB, send your time per image and peak VRAM and it will appear here, credited.

04About the Arc B580 12 GB

Intel Arc GPUs run ComfyUI through PyTorch's native XPU support on Windows 11 and Linux. Memory works the same as on NVIDIA, so the fit verdicts apply. FP8 files save memory but give no speed-up, and some custom nodes are NVIDIA-only.

12 GB GDDR6 · 192-bit · 456 GB/s · Battlemage. Everything that runs on it →

05Questions

How much VRAM does Z-Image Turbo need?

Around 5.6 GB with the smallest file (Q2_K) and 8.2 GB with an 8-bit file (INT8). The full 16-bit file needs about 14.3 GB.

Which Z-Image Turbo file should I download for the Arc B580 12 GB?

Q8_0 (7.2 GB) from unsloth/Z-Image-Turbo-GGUF. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.

How much do I need to download for Z-Image Turbo on the Arc B580 12 GB?

13.2 GB: z-image-turbo-Q8_0.gguf, qwen_3_4b_fp8_mixed.safetensors, ae.safetensors.