Datasheet for local AI49 models98 GPUsData read 2026-09-25
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Arc A770 16 GB for local AI

Which image and video models run on the Arc A770 16 GB, which file to download for each, and how much VRAM they need.

Intel16 GB GDDR6 · 256-bit · 560 GB/s · AlchemistData 2026-09-25
VRAM16 GB
MemoryGDDR6
Bus256-bit
Bandwidth560 GB/s
ArchitectureAlchemist
Launched2022-10
Launch price$349
Runs well25 of 49

Specs: www.intel.com · launch: game.intel.com

01What runs on it

ModelVerdictBest fileSizeNeeded
image models
FLUX.1 [dev]Runs wellQ8_012.7 GB15.0 GB
FLUX.1 [schnell]Runs wellQ8_012.7 GB15.0 GB
FLUX.1 Kontext [dev]Runs wellQ8_012.7 GB15.3 GB
FLUX.1 Krea [dev]Runs wellQ8_012.7 GB15.0 GB
FLUX.1 Fill [dev]Runs wellQ8_012.7 GB15.3 GB
FLUX.2 [dev]Offload onlyQ2_K12.9 GB16.2 GB
FLUX.2 [klein] 9BRuns wellQ8_010.0 GB12.3 GB
FLUX.2 [klein] 4BRuns well16-bit7.8 GB9.6 GB
Krea 2 (Turbo)Runs wellFP813.1 GB15.7 GB
Qwen-ImageRunsQ4_K_M13.1 GB15.9 GB
Qwen-Image-Edit (2511)TightQ3_K_M9.9 GB12.9 GB
Qwen-Image 2.1Runs wellQ8_07.6 GB9.9 GB
Z-Image TurboRuns well16-bit12.3 GB14.3 GB
Z-Image (base)Runs well16-bit12.3 GB14.3 GB
Ideogram 4RunsQ4_16.2 GB14.7 GB
Boogu-Image (Turbo)Runs wellQ8_011.6 GB14.2 GB
ERNIE-Image (Turbo)Runs wellQ8_08.7 GB11.0 GB
HiDream-O1-ImageRuns wellFP88.1 GB10.9 GB
Mage-Flow (Microsoft)Runs well16-bit8.2 GB10.0 GB
Lumina Image 2.0Runs well16-bit5.2 GB7.0 GB
HiDream-I1 (Full)RunsQ5_K_M13.0 GB15.8 GB
HiDream-I1 (Dev)RunsQ5_K_M13.0 GB15.8 GB
Stable Diffusion 3.5 LargeRuns wellQ8_08.8 GB11.1 GB
Stable Diffusion 3.5 MediumRuns well16-bit5.1 GB6.9 GB
Chroma1-HDRuns wellQ8_09.7 GB12.0 GB
SDXL 1.0Runs well16-bit6.9 GB7.1 GB
Illustrious XL / Pony (SDXL anime)Runs well16-bit6.9 GB7.1 GB
Stable Diffusion 1.5Runs well16-bit2.1 GB3.3 GB
HunyuanImage 2.1RunsQ4_K_M11.3 GB14.6 GB
video models
Wan 2.1 T2V 14BRunsQ5_K_M11.3 GB15.6 GB
Wan 2.1 T2V 1.3BRuns well16-bit2.8 GB5.6 GB
Wan 2.1 I2V 14B 480PRunsQ4_K_M11.3 GB15.6 GB
Wan 2.1 I2V 14B 720PTightQ3_K_M8.6 GB15.4 GB
Wan 2.1 VACE 14BTightQ3_K_S7.8 GB12.6 GB
Wan 2.2 T2V A14BRunsQ5_K_M10.8 GB15.1 GB
Wan 2.2 I2V A14BRunsQ5_K_M10.8 GB15.1 GB
Wan 2.2 TI2V 5BRuns well16-bit10.0 GB13.8 GB
Wan 2.2 Animate 14BTightQ3_K_M8.6 GB13.9 GB
Wan Animate 2 (14B)TightQ3_K_M8.6 GB13.9 GB
Wan 2.2 S2V 14BTightQ2_K9.5 GB14.3 GB
SCAIL-2 (character animation)TightQ3_K_M9.1 GB14.4 GB
HunyuanVideo (13B, original)RunsQ6_K11.0 GB15.3 GB
LTX-Video 13B (0.9.8)RunsQ6_K10.9 GB15.2 GB
HunyuanVideo 1.5Runs wellQ8_09.0 GB13.3 GB
LTX-2 (19B)TightQ3_K_M10.1 GB14.9 GB
LTX-2.3 (22B)TightQ3_K_M10.8 GB15.6 GB
LTX-2.5 (22B)TightQ2_K8.8 GB13.6 GB
MiniMax H3 (33B)Offload onlyQ4_K_M19.9 GB25.7 GB
MiniMax H3 PrunedTightQ3_K_M8.9 GB14.7 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

LabelModelSetupResultPeak VRAMDateSource
reportedFLUX.1 devfp8 (ComfyUI template) · 20 steps
“20/20 [00:46<00:00, 2.33s/it] Prompt executed in 47.13 seconds”
'GPU Benchmark Flux DEV fp8' thread; Intel A770 on Fedora Linux, PyTorch 2.3.110+xpu (53.26 s with PyTorch nightly); resolution not stated
47.13 s / image · 2.33 s/it—2025-07-24github.com →
reportedSDXLSDXL 1.0 base · 1024x1024 · 20 steps
“20/20 [00:14<00:00, 1.36it/s] ... Prompt executed in 23.44 seconds”
ACER A770 16GB; thread benchmark = SDXL 1024x1024 20 steps seed 1; later runs 1.53 it/s / 14.28 s
23.44 s / image · 1.36 it/s—2025-07-10github.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.