Check my GPU →

Can the Arc B580 12 GB run Ideogram 4?

Not entirely. Even Q4_1 is 2.7 GB over 12 GB, so ComfyUI keeps part of it in system RAM.

Image model · 9.3B12 GB GDDR6 · 192-bit · 456 GB/s · BattlemageData 2026-10-01
Offload
Not entirely in VRAM, but it can still run.

The smallest sensible file, Q4_1 (6.2 GB (×2, both loaded)), needs about 14.7 GB - 2.7 GB more than Arc B580 12 GB has. ComfyUI can still run it by streaming part of the model from system RAM. How much slower that is depends on your ComfyUI version, the file format and the PCIe link - see the note below.

Best fileQ4_1
File size6.2 GB ×2
VRAM needed~14.7 GB
System RAM32 GB+
Memory map · Arc B580 12 GB14.7 GB needed · 2.7 GB over 12 GB
07 GB15 GB
Weights Q4_1 ×2 · 12.4 GBWorking memory · 1.5 GBReserve · 0.8 GBSpills to system RAM · 2.7 GB

01With more VRAM

With 24 GB you could run Ideogram 4 at 8-bit or better (Q8_0, 10.1 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 Ideogram 4 file on 12 GB

FileSizeNeededOn this cardQualityDownload
Q8_0
GGUF · molbal
10.1 GB ×222.6 GB10.6 GB too bigpractically identical to the originalHugging Face →
FP8
SAFETENSORS · Comfy-Org
9.3 GB ×220.9 GB8.9 GB too bigpractically identical to the originalHugging Face →
INT8
SAFETENSORS · Comfy-Org
9.6 GB ×221.5 GB9.5 GB too bigpractically identical to the originalHugging Face →
Q5_1
GGUF · molbal
7.3 GB ×217.0 GB5.0 GB too bigclose; small differences in fine detailHugging Face →
Q4_1 ←
GGUF · molbal
6.2 GB ×214.7 GB2.7 GB too biggood; some loss in fine detail and textHugging Face →

“Needed” adds 1.5 GB of working memory for Ideogram 4 and a 0.8 GB reserve. Sizes 2026-10-01. Needs two transformer files loaded together (main + unconditional). GGUF files need the molbal fork of ComfyUI-GGUF. No 16-bit weights were released.

03What to download

PartFileFolderSize
Modelideogram4-transformer-q4_1.gguf
main model
Q4_1 · molbal/ideogram-4-gguf
models/unet6.2 GBDownload →
Modelideogram4-unconditional_transformer-q4_1.gguf
unconditional model, loaded together with the main one
Q4_1 · molbal/ideogram-4-gguf
models/unet6.2 GBDownload →
Text encoderqwen3vl_8b_fp8_scaled.safetensors
Qwen3-VL 8B FP8 · Comfy-Org/Ideogram-4
models/text_encoders10.6 GBDownload →
VAEflux2-vae.safetensors
FLUX.2 VAE · Comfy-Org/Ideogram-4
models/vae0.3 GBDownload →
Total download · keep about the same free on disk23.3 GB

Alternatives: Qwen3-VL 8B NVFP4 (6.3 GB). FP4 files are listed only as alternatives unless the GPU is an RTX 50 (Blackwell). Sizes from Hugging Face, 2026-10-01.

04Measured and reported results

Nobody has sent measured numbers for this pair yet. If you run Ideogram 4 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 Ideogram 4 need?

Around 14.7 GB with the smallest file (Q4_1) and 20.9 GB with an 8-bit file (FP8).

Which Ideogram 4 file should I download for the Arc B580 12 GB?

Q4_1 (6.2 GB) from molbal/ideogram-4-gguf. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.

FP8 or Q8_0 for Ideogram 4 on the Arc B580 12 GB?

Q8_0 (10.1 GB). The Arc B580 12 GB has no FP8 maths, so FP8 (9.3 GB) only saves memory and is a step further from the original.

How much do I need to download for Ideogram 4 on the Arc B580 12 GB?

23.3 GB: ideogram4-transformer-q4_1.gguf, ideogram4-unconditional_transformer-q4_1.gguf, qwen3vl_8b_fp8_scaled.safetensors, flux2-vae.safetensors.