Datasheet for local AI49 models98 GPUsData read 2026-09-25
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Can the Arc B580 12 GB run Stable Diffusion 3.5 Large?

Image model · 8.1B12 GB GDDR6 · 192-bit · 456 GB/s · BattlemageData 2026-09-25
Runs well
Yes — and comfortably.

Download Q8_0 (8.8 GB). With the model's working memory it needs about 11.1 GB, leaving 0.9 GB spare on 12 GB. Quality: practically identical to the original.

Best fileQ8_0
File size8.8 GB
VRAM needed~11.1 GB
System RAM32 GB+
Memory map · Arc B580 12 GB11.1 GB / 12 GB
06 GB12 GB
Weights Q8_0 · 8.8 GBWorking memory · 1.5 GBReserve · 0.8 GBFree · 0.9 GB
calculated from real file sizes plus working memory. Real-world results people have reported are listed further down. How this works.

01What to download

PartFileFolderSize
Modelsd3.5_large-Q8_0.gguf
Q8_0 · city96/stable-diffusion-3.5-large-gguf
models/unet8.8 GBDownload →
Text encodert5xxl_fp8_e4m3fn.safetensors
T5-XXL FP8 · Comfy-Org/stable-diffusion-3.5-fp8
models/text_encoders4.9 GBDownload →
Text encoderclip_l.safetensors
CLIP-L · Comfy-Org/stable-diffusion-3.5-fp8
models/text_encoders0.2 GBDownload →
Text encoderclip_g.safetensors
CLIP-G · Comfy-Org/stable-diffusion-3.5-fp8
models/text_encoders1.4 GBDownload →
Total download · keep about the same free on disk15.3 GB

Alternatives: T5-XXL FP16 (9.8 GB). The 16-bit text encoder is a little more faithful; the smaller one is chosen here because it loads faster and needs less RAM. Sizes read from Hugging Face (2026-09-25). “Download” links start the file directly; the file name links are the same files the official ComfyUI workflows use.

System RAM: 32 GB or more. ComfyUI keeps the model file, the text encoder and the VAE in system RAM and moves them to the GPU as needed. With this set of files that is about 15.3 GB, plus roughly 6 GB for Windows, ComfyUI and a browser: 21.3 GB in total. With less RAM it still runs, but Windows starts swapping to disk and loading gets very slow. calculated

02Every SD 3.5 Large file on 12 GB

FileSizeNeededOn this cardQualityDownload
16-bit
SAFETENSORS · stabilityai
16.5 GB18.8 GB6.8 GB too bigthe original weightsHugging Face →
Q8_0 ←
GGUF · city96
8.8 GB11.1 GBfits · 0.9 GB sparepractically identical to the originalHugging Face →
Q5_1
GGUF · city96
6.3 GB8.6 GBfits · 3.4 GB spareclose; small differences in fine detailHugging Face →
Q4_1
GGUF · city96
5.3 GB7.6 GBfits · 4.4 GB sparegood; some loss in fine detail and textHugging Face →

Sizes from the Hugging Face file listing, read 2026-09-25. “Needed” = file + 1.5 GB working memory for this model + 0.8 GB kept free for the system.

03The text encoder

CLIP-L + CLIP-G + T5-XXL: 9.8 GB as 16-bit, 4.9 GB as FP8 (T5-XXL sizes shown; CLIP-L and CLIP-G add about 1.6 GB). ComfyUI encodes the prompt first and can push the encoder out of VRAM before sampling, so it does not have to fit together with the model. On 12 GB the FP8 encoder fits on its own, so prompt encoding stays fast.

04About this GPU

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.

Arc B580 12 GB: 12 GB GDDR6 · 192-bit · 456 GB/s · Battlemage. Everything that runs on the Arc B580 12 GB →

05What more VRAM would change

Nothing to gain for this model: the Arc B580 12 GB already runs a top-quality file entirely in VRAM. More memory would only help with bigger images, longer clips or several models at once.

What changes from the Arc B580 12 GB to the RTX 5060 Ti 16 GB →

06Measured and reported results

LabelSetupResultPeak VRAMDateSource
reportedfp8 · 1024x1024 · 20 steps
“SD 3.5 large fp8 (20step): GOOD (26s)”
Intel Arc B580 12GB, PyTorch 2.8 XPU in Docker (YanWenKun); single 1024x1024 image, pre-warmed inference only (model load excluded)
26 s / image—2025-08-03github.com →

Reported results are other people's numbers, copied as published, with a link. Settings, drivers and ComfyUI versions differ, so compare them with care. Send yours.

07Questions

How much VRAM does SD 3.5 Large need?

Around 7.6 GB with the smallest file (Q4_1) and 11.1 GB with an 8-bit file (Q8_0), counting working memory and a small system reserve. The full 16-bit file needs about 18.8 GB.

Which SD 3.5 Large file should I download for the Arc B580 12 GB?

Q8_0 (8.8 GB) from city96/stable-diffusion-3.5-large-gguf. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.

Is FP8 faster than GGUF on the Arc B580 12 GB?

No. This GPU has no FP8 compute, so ComfyUI converts FP8 weights back before the maths. FP8 only saves memory here; Q8_0 GGUF is the closer-to-original 8-bit pick.

How much do I need to download for SD 3.5 Large on the Arc B580 12 GB?

About 15.3 GB for the model file, text encoder and VAE listed on this page, and the same again free on disk. With a 12 GB card, 32 GB of system RAM or more is recommended.