Check my GPU →

HiDream-O1-Image on 6 GB of VRAM

Not entirely. Even FP8 is 4.9 GB over 6 GB, so ComfyUI keeps part of it in system RAM. A 2026 all-in-one 8.8B model built on Qwen3-VL: no separate text encoder and no VAE. It generates, edits and personalises up to 2048×2048.

Image model · 8.8BAny 6 GB GPUData 2026-10-01
Offload
Not entirely in VRAM, but it can still run.

The smallest sensible file, FP8 (8.1 GB), needs about 10.9 GB - 4.9 GB more than 6 GB GPU 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 fileFP8
File size8.1 GB
VRAM needed~10.9 GB
System RAM16 GB+
Memory map · 6 GB GPU10.9 GB needed · 4.9 GB over 6 GB
05 GB11 GB
Weights FP8 · 8.1 GBWorking memory · 2.0 GBReserve · 0.8 GBSpills to system RAM · 4.9 GB

Got an RTX 40 or 50? Swap Q8_0 for FP8 (8.1 GB): same quality class, computed natively there.

Also try the FP8 file (8.1 GB) on NVIDIA GPUs. It does not fit entirely, but a current ComfyUI streams the overflow from RAM and native 8-bit files often beat a small GGUF that does fit. Dynamic VRAM →

02Every file, on 6 GB

FileSizeNeededOn this cardQualityDownload
16-bit
SAFETENSORS · Comfy-Org
16.4 GB19.2 GB13.2 GB too bigthe original weightsHugging Face →
FP8 ←
SAFETENSORS · Comfy-Org
8.1 GB10.9 GB4.9 GB too bigpractically identical to the originalHugging Face →

“Needed” adds 2 GB of working memory for HiDream-O1 and a 0.8 GB reserve. Sizes 2026-10-01. The Comfy-Org files are complete checkpoints (loaded from the checkpoints folder); there is no separate text encoder or VAE to add. No GGUF version was found.

03What to download

PartFileFolderSize
Checkpointhidream_o1_image_fp8_scaled.safetensors
FP8 · Comfy-Org/HiDream-O1-Image
models/checkpoints8.1 GBDownload →
Total download · keep about the same free on disk8.1 GB

One file: this model has no separate text encoder or VAE. Sizes from Hugging Face, 2026-10-01.

04The text encoder

This model has no separate text encoder: reading the prompt is built into the model itself, so its memory is already in the file sizes above.