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Can the Intel Core Ultra 200H (Arc 140T) (32 GB) run Z-Image Turbo?

87 ptsExcellent (S) · 87 of 100 points: Model quality 37.0/45, Memory fit 25.0/25, Speed 10.3/15, Memory use 15.0/15

Yes, it runs well

Runs well. At FP8 it needs about 12.6 GB of 18.2 GB usable, with an estimated speed of 21 s.

Best precision
FP8
Memory mode
Everything on GPU
Time per image
21 s
Output
1024×1024, 8 steps

Download Z-Image Turbo

Quantized files · GGUF for ComfyUI

Smaller GGUF versions for ComfyUI (with the ComfyUI-GGUF node). No sign-in needed; the model’s license still applies.

huggingface.co/unsloth/Z-Image-Turbo-GGUF (opens in a new tab)

Original weights · Hugging Face

Full-precision files from Alibaba (Tongyi), for fine-tuning, vLLM, Transformers, Diffusers or ComfyUI.

huggingface.co/Tongyi-MAI/Z-Image-Turbo (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from Alibaba (Tongyi). The weights themselves download from Hugging Face.

github.com/Tongyi-MAI/Z-Image (opens in a new tab)

git clone https://github.com/Tongyi-MAI/Z-Image

Links checked 5 days ago against Hugging Face, Ollama and GitHub.

How the S grade is scored

Every result gets up to 100 points from four parts. The points decide the letter grade.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.37.0 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.10.3 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.15.0 / 15
Total87.4 / 10087 ptsExcellent (S) · 87 of 100 points: Model quality 37.0/45, Memory fit 25.0/25, Speed 10.3/15, Memory use 15.0/15

Grade scale: S 85+ · A 72+ · B 58+ · C 42+ · D 25+ · F under 25 points.

Every precision on the Intel Core Ultra 200H (Arc 140T) (32 GB)

Precision Memory needed Available Time per output Memory mode Fit Grade · points Download
FP16 14.7 GB 18.2 GB 25 s Text encoder offloaded Runs well 82 ptsGreat (A) · 82 of 100 points: Model quality 37.8/45, Memory fit 20.0/25, Speed 9.6/15, Memory use 15.0/15 Original weights (opens in a new tab)
FP8 12.6 GB 18.2 GB 21 s Everything on GPU Runs well 87 ptsExcellent (S) · 87 of 100 points: Model quality 37.0/45, Memory fit 25.0/25, Speed 10.3/15, Memory use 15.0/15 Original weights (opens in a new tab)
Q8 GGUF 13.0 GB 18.2 GB 27 s Everything on GPU Runs well 86 ptsExcellent (S) · 86 of 100 points: Model quality 37.4/45, Memory fit 25.0/25, Speed 9.2/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q4 GGUF 10.1 GB 18.2 GB 28 s Everything on GPU Runs well 81 ptsGreat (A) · 81 of 100 points: Model quality 35.2/45, Memory fit 25.0/25, Speed 9.0/15, Memory use 12.8/15 GGUF (opens in a new tab)

Other hardware that runs it

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.