Arc B580 12 GB for local AI
Which image and video models run on the Arc B580 12 GB, which file to download for each, and how much VRAM they need.
VRAM12 GB
MemoryGDDR6
Bus192-bit
Bandwidth456 GB/s
ArchitectureBattlemage
Launched2024-12
Launch price$249
Runs well17 of 49
Specs: www.intel.com · launch: www.intel.com
01What runs on it
| Model | Verdict | Best file | Size | Needed |
|---|---|---|---|---|
| image models | ||||
| FLUX.1 [dev] | Runs | Q5_K_S | 8.3 GB | 10.6 GB |
| FLUX.1 [schnell] | Runs | Q5_K_S | 8.3 GB | 10.6 GB |
| FLUX.1 Kontext [dev] | Runs | Q5_K_M | 8.4 GB | 11.0 GB |
| FLUX.1 Krea [dev] | Runs | Q5_K_M | 8.4 GB | 10.7 GB |
| FLUX.1 Fill [dev] | Runs | Q5_K_S | 8.3 GB | 10.9 GB |
| FLUX.2 [dev] | Offload only | Q4_K_M | 20.1 GB | 23.4 GB |
| FLUX.2 [klein] 9B | Runs well | FP8 | 9.4 GB | 11.7 GB |
| FLUX.2 [klein] 4B | Runs well | 16-bit | 7.8 GB | 9.6 GB |
| Krea 2 (Turbo) | Runs | Q5_K_M | 8.9 GB | 11.5 GB |
| Qwen-Image | Tight | Q2_K | 7.1 GB | 9.9 GB |
| Qwen-Image-Edit (2511) | Tight | Q2_K | 7.5 GB | 10.5 GB |
| Qwen-Image 2.1 | Runs well | Q8_0 | 7.6 GB | 9.9 GB |
| Z-Image Turbo | Runs well | Q8_0 | 7.2 GB | 9.2 GB |
| Z-Image (base) | Runs well | Q8_0 | 7.2 GB | 9.2 GB |
| Ideogram 4 | Offload only | Q4_1 | 6.2 GB | 14.7 GB |
| Boogu-Image (Turbo) | Runs | Q5_1 | 8.6 GB | 11.2 GB |
| ERNIE-Image (Turbo) | Runs well | Q8_0 | 8.7 GB | 11.0 GB |
| HiDream-O1-Image | Runs well | FP8 | 8.1 GB | 10.9 GB |
| Mage-Flow (Microsoft) | Runs well | 16-bit | 8.2 GB | 10.0 GB |
| Lumina Image 2.0 | Runs well | 16-bit | 5.2 GB | 7.0 GB |
| HiDream-I1 (Full) | Tight | Q3_K_M | 8.8 GB | 11.6 GB |
| HiDream-I1 (Dev) | Tight | Q3_K_M | 8.8 GB | 11.6 GB |
| Stable Diffusion 3.5 Large | Runs well | Q8_0 | 8.8 GB | 11.1 GB |
| Stable Diffusion 3.5 Medium | Runs well | 16-bit | 5.1 GB | 6.9 GB |
| Chroma1-HD | Runs well | FP8 | 9.2 GB | 11.5 GB |
| SDXL 1.0 | Runs well | 16-bit | 6.9 GB | 7.1 GB |
| Illustrious XL / Pony (SDXL anime) | Runs well | 16-bit | 6.9 GB | 7.1 GB |
| Stable Diffusion 1.5 | Runs well | 16-bit | 2.1 GB | 3.3 GB |
| HunyuanImage 2.1 | Tight | Q2_K | 7.3 GB | 10.6 GB |
| video models | ||||
| Wan 2.1 T2V 14B | Tight | Q3_K_M | 7.6 GB | 11.9 GB |
| Wan 2.1 T2V 1.3B | Runs well | 16-bit | 2.8 GB | 5.6 GB |
| Wan 2.1 I2V 14B 480P | Offload only | Q3_K_M | 8.6 GB | 12.9 GB |
| Wan 2.1 I2V 14B 720P | Offload only | Q4_K_M | 11.3 GB | 18.1 GB |
| Wan 2.1 VACE 14B | Offload only | Q3_K_S | 7.8 GB | 12.6 GB |
| Wan 2.2 T2V A14B | Tight | Q3_K_M | 7.2 GB | 11.5 GB |
| Wan 2.2 I2V A14B | Tight | Q3_K_M | 7.2 GB | 11.5 GB |
| Wan 2.2 TI2V 5B | Runs well | Q8_0 | 5.4 GB | 9.2 GB |
| Wan 2.2 Animate 14B | Tight | Q2_K | 6.5 GB | 11.8 GB |
| Wan Animate 2 (14B) | Tight | Q2_K | 6.5 GB | 11.8 GB |
| Wan 2.2 S2V 14B | Offload only | Q4_K_M | 13.9 GB | 18.7 GB |
| SCAIL-2 (character animation) | Offload only | Q2_K | 7.3 GB | 12.6 GB |
| HunyuanVideo (13B, original) | Tight | Q3_K_M | 6.2 GB | 10.5 GB |
| LTX-Video 13B (0.9.8) | Tight | Q3_K_M | 6.5 GB | 10.8 GB |
| HunyuanVideo 1.5 | Runs | Q6_K | 7.0 GB | 11.3 GB |
| LTX-2 (19B) | Offload only | Q2_K | 8.1 GB | 12.9 GB |
| LTX-2.3 (22B) | Offload only | Q2_K | 8.3 GB | 13.1 GB |
| LTX-2.5 (22B) | Offload only | Q2_K | 8.8 GB | 13.6 GB |
| MiniMax H3 (33B) | Offload only | Q4_K_M | 19.9 GB | 25.7 GB |
| MiniMax H3 Pruned | Offload only | Q4_K_M | 11.6 GB | 17.4 GB |
Calculated from real file sizes plus working memory. How the numbers work.
02Good to know
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.
03Measured and reported results
| Label | Model | Setup | Result | Peak VRAM | Date | Source |
|---|---|---|---|---|---|---|
| reported | FLUX.1 dev | fp8 · 1024x1024 · 20 steps “Flux1 dev fp8 (20step): GOOD (35s)” Intel Arc B580 12GB, PyTorch 2.8 XPU in Docker (YanWenKun); single 1024x1024 image, pre-warmed inference only (model load excluded) | 35 s / image | — | 2025-08-03 | github.com → |
| reported | FLUX.1 Krea | Flux1 Krea dev (precision not stated) · 1024x1024 · 20 steps “Flux1 Krea dev (20step): OK (46s)” Intel Arc B580 12GB, PyTorch 2.8 XPU in Docker (YanWenKun); single 1024x1024 image, pre-warmed inference only (model load excluded) | 46 s / image | — | 2025-08-03 | github.com → |
| reported | FLUX.1 schnell | Flux1 schnell (template) · 1024x1024 · 4 steps “Flux1 schnell (4step): GOOD (8s)” Intel Arc B580 12GB, PyTorch 2.8 XPU in Docker (YanWenKun); single 1024x1024 image, pre-warmed inference only (model load excluded) | 8 s / image | — | 2025-08-03 | github.com → |
| reported | SD 3.5 Large | 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 → |
| reported | SDXL | sd_xl_base_1.0 · 1024x1024 · 20 steps “100%|██| 20/20 [00:05<00:00, 3.96it/s]” ComfyUI 'GPU Benchmark' thread: default workflow, SDXL 1.0 base, 1024x1024, seed 1, second run; Intel B580 Steel Legend OC 12 GB | 3.96 it/s | — | 2025-05-12 | github.com → |
| reported | Wan 2.2 5B | Wan 2.2 5B T2V (template) · 640x352 “Wan 2.2 5B Text to Video (640x352, 121 frames): FAST (60s, very poor quality)” Arc B580 12GB, PyTorch 2.8 XPU; same post: 960x544/121f = 181s, 1280x704 OOM; steps not stated | 60 s / clip (121 frames) | — | 2025-08-03 | github.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.