Can the Arc B580 12 GB run SCAIL-2 (character animation)?
Not entirely. Even Q2_K is 0.6 GB over 12 GB, so ComfyUI keeps part of it in system RAM.
Nothing fits entirely, but Q2_K (7.3 GB) overflows by only about 0.6 GB. ComfyUI keeps that part in system RAM automatically: slower than a full fit, but usable.
01With more VRAM
With 24 GB you could run SCAIL-2 at 8-bit or better (Q8_0, 18.1 GB) with no offloading: for example on the RTX 4090 24 GB, RTX 3090 24 GB, RX 7900 XTX 24 GB.
What changes from the Arc B580 12 GB to the RTX 5060 Ti 16 GB →
02Every SCAIL-2 file on 12 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit SAFETENSORS · Comfy-Org | 32.8 GB | 38.1 GB | 26.1 GB too big | the original weights | Hugging Face → |
| Q8_0 GGUF · vantagewithai | 18.1 GB | 23.4 GB | 11.4 GB too big | practically identical to the original | Hugging Face → |
| FP8 SAFETENSORS · Comfy-Org | 17.7 GB | 23.0 GB | 11.0 GB too big | practically identical to the original | Hugging Face → |
| INT8 SAFETENSORS · Comfy-Org | 16.7 GB | 22.0 GB | 10.0 GB too big | practically identical to the original | Hugging Face → |
| Q6_K GGUF · vantagewithai | 14.2 GB | 19.5 GB | 7.5 GB too big | very close to the original | Hugging Face → |
| Q5_K_M GGUF · vantagewithai | 13.0 GB | 18.3 GB | 6.3 GB too big | close; small differences in fine detail | Hugging Face → |
| Q4_K_M GGUF · vantagewithai | 11.5 GB | 16.8 GB | 4.8 GB too big | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_M GGUF · vantagewithai | 9.1 GB | 14.4 GB | 2.4 GB too big | noticeable loss of detail | Hugging Face → |
| Q2_K ← GGUF · vantagewithai | 7.3 GB | 12.6 GB | spills 0.6 GB | heavy loss; a last resort | Hugging Face → |
“Needed” adds 4.5 GB of working memory for SCAIL-2 and a 0.8 GB reserve. Sizes 2026-10-01.
03What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | wan2.1_14B_SCAIL_2-Q2_K.gguf Q2_K · vantagewithai/SCAIL-2-GGUF-ComfyUI | models/unet | 7.3 GB | Download → |
| Text encoder | umt5_xxl_fp8_e4m3fn_scaled.safetensors UMT5-XXL FP8 (scaled) · Comfy-Org/Wan_2.1_ComfyUI_repackaged | models/text_encoders | 6.7 GB | Download → |
| VAE | Wan2_1_VAE_bf16.safetensors Wan 2.1 VAE BF16 (Kijai) · Kijai/WanVideo_comfy | models/vae | 0.3 GB | Download → |
| Also needed | clip_vision_h.safetensors CLIP Vision H · Comfy-Org/Wan_2.1_ComfyUI_repackaged | models/clip_vision | 1.3 GB | Download → |
| Total download · keep about the same free on disk | 15.6 GB | |||
Alternatives: UMT5-XXL FP16 (11.4 GB). Only for some workflows: SAM 3.1 multiplex FP16 (segmentation) (1.7 GB, character-replacement workflow (masking)). Sizes from Hugging Face, 2026-10-01.
04Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run SCAIL-2 on a Arc B580 12 GB, send your time per image and peak VRAM and it will appear here, credited.
05About 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 →
06Questions
How much VRAM does SCAIL-2 need?
Around 12.6 GB with the smallest file (Q2_K) and 23.0 GB with an 8-bit file (FP8). The full 16-bit file needs about 38.1 GB.
Which SCAIL-2 file should I download for the Arc B580 12 GB?
Q2_K (7.3 GB) from vantagewithai/SCAIL-2-GGUF-ComfyUI. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.
FP8 or Q8_0 for SCAIL-2 on the Arc B580 12 GB?
Q8_0 (18.1 GB). The Arc B580 12 GB has no FP8 maths, so FP8 (17.7 GB) only saves memory and is a step further from the original.
How much do I need to download for SCAIL-2 on the Arc B580 12 GB?
15.6 GB: wan2.1_14B_SCAIL_2-Q2_K.gguf, umt5_xxl_fp8_e4m3fn_scaled.safetensors, Wan2_1_VAE_bf16.safetensors, clip_vision_h.safetensors.