Can the Arc B580 12 GB run Stable Diffusion 3.5 Large?
Yes, but only just: Q8_0 leaves 0.9 GB free on the Arc B580 12 GB.
Q8_0 (8.8 GB) fits with only 0.9 GB to spare (about 11.1 GB of 12 GB).
01What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | sd3.5_large-Q8_0.gguf Q8_0 · city96/stable-diffusion-3.5-large-gguf | models/unet | 8.8 GB | Download → |
| Text encoder | t5xxl_fp8_e4m3fn.safetensors T5-XXL FP8 · Comfy-Org/stable-diffusion-3.5-fp8 | models/text_encoders | 4.9 GB | Download → |
| Text encoder | clip_l.safetensors CLIP-L · Comfy-Org/stable-diffusion-3.5-fp8 | models/text_encoders | 0.2 GB | Download → |
| Text encoder | clip_g.safetensors CLIP-G · Comfy-Org/stable-diffusion-3.5-fp8 | models/text_encoders | 1.4 GB | Download → |
| VAE | diffusion_pytorch_model.safetensors SD 3.5 VAE (gated repo: log in and accept the licence first) · stabilityai/stable-diffusion-3.5-large | models/vae | 0.2 GB | Download → |
| Total download · keep about the same free on disk | 15.5 GB | |||
Alternatives: T5-XXL FP16 (9.8 GB). Sizes from Hugging Face, 2026-10-01.
02Every SD 3.5 Large file on 12 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit SAFETENSORS · stabilityai | 16.5 GB | 18.8 GB | 6.8 GB too big | the original weights | Hugging Face → |
| Q8_0 ← GGUF · city96 | 8.8 GB | 11.1 GB | fits · 0.9 GB spare | practically identical to the original | Hugging Face → |
| Q5_1 GGUF · city96 | 6.3 GB | 8.6 GB | fits · 3.4 GB spare | close; small differences in fine detail | Hugging Face → |
| Q4_1 GGUF · city96 | 5.3 GB | 7.6 GB | fits · 4.4 GB spare | good; some loss in fine detail and text | Hugging Face → |
“Needed” adds 1.5 GB of working memory for SD 3.5 Large and a 0.8 GB reserve. Sizes 2026-10-01.
03Measured and reported results
| Label | Setup | Result | Peak VRAM | Date | Source |
|---|---|---|---|---|---|
| reported | fp8 · 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 | — | 2025-08-03 | github.com → |
Other people's numbers are copied as published, with a link. Send yours.
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 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). 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.
How much do I need to download for SD 3.5 Large on the Arc B580 12 GB?
15.5 GB: sd3.5_large-Q8_0.gguf, t5xxl_fp8_e4m3fn.safetensors, clip_l.safetensors, clip_g.safetensors, diffusion_pytorch_model.safetensors.