Datasheet for local AI49 models98 GPUsData read 2026-09-25
No adsNo tracking
Check my GPU →

HiDream-I1 (Full) on 6 GB of VRAM

Image model · 17BAny 6 GB GPUData 2026-09-25
Offload
Not entirely in VRAM, but it can still run.

The smallest sensible file, Q4_K_M (11.5 GB), needs about 14.3 GB — 8.3 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 fileQ4_K_M
File size11.5 GB
VRAM needed~14.3 GB
System RAM48 GB+
Memory map · 6 GB GPU14.3 GB needed · 8.3 GB over 6 GB
07 GB14 GB
Weights Q4_K_M · 11.5 GBWorking memory · 2.0 GBReserve · 0.8 GBSpills to system RAM · 8.3 GB
calculated from real file sizes plus working memory. Not yet measured on this setup. How this works.

Worth trying on NVIDIA GPUs: with an up-to-date ComfyUI, Dynamic VRAM (on by default for NVIDIA since March 2026) streams whatever does not fit from system RAM, and ComfyUI's own start-up message recommends native FP8/INT8 files over GGUF, saying they “will be faster even if they are larger than your memory”. So before settling for a heavily compressed GGUF, try the native FP8 file (17.1 GB). The file recommended above is the best one that fits entirely — the safe choice on older ComfyUI versions, AMD and Intel. Comfy blog: Dynamic VRAM →

01What to download

PartFileFolderSize
Modelhidream-i1-full-Q4_K_M.gguf
Q4_K_M · city96/HiDream-I1-Full-gguf
models/unet11.5 GBDownload →
Text encodert5xxl_fp8_e4m3fn_scaled.safetensors
T5-XXL FP8 scaled · Comfy-Org/HiDream-I1_ComfyUI
models/text_encoders5.2 GBDownload →
Text encoderclip_l_hidream.safetensors
CLIP-L (HiDream) · Comfy-Org/HiDream-I1_ComfyUI
models/text_encoders0.2 GBDownload →
Text encoderclip_g_hidream.safetensors
CLIP-G (HiDream) · Comfy-Org/HiDream-I1_ComfyUI
models/text_encoders1.4 GBDownload →
Text encoderllama_3.1_8b_instruct_fp8_scaled.safetensors
Llama 3.1 8B Instruct FP8 · Comfy-Org/HiDream-I1_ComfyUI
models/text_encoders9.1 GBDownload →
VAEae.safetensors
FLUX.1 VAE (ae) · Comfy-Org/HiDream-I1_ComfyUI
models/vae0.3 GBDownload →
Total download · keep about the same free on disk27.7 GB

Alternatives: T5-XXL FP16 (9.8 GB). The 16-bit text encoder is a little more faithful; the smaller one is chosen here because it loads faster and needs less RAM. Sizes read from Hugging Face (2026-09-25). “Download” links start the file directly; the file name links are the same files the official ComfyUI workflows use.

System RAM: 48 GB or more. ComfyUI keeps the model file, the text encoder and the VAE in system RAM and moves them to the GPU as needed. With this set of files that is about 27.7 GB, plus roughly 6 GB for Windows, ComfyUI and a browser: 33.7 GB in total. With less RAM it still runs, but Windows starts swapping to disk and loading gets very slow. calculated

02Every file, on 6 GB

FileSizeNeededOn this cardQualityDownload
16-bit
SAFETENSORS · Comfy-Org
34.2 GB37.0 GB31.0 GB too bigthe original weightsHugging Face →
Q8_0
GGUF · city96
18.7 GB21.5 GB15.5 GB too bigpractically identical to the originalHugging Face →
FP8
SAFETENSORS · Comfy-Org
17.1 GB19.9 GB13.9 GB too bigpractically identical to the originalHugging Face →
Q6_K
GGUF · city96
14.7 GB17.5 GB11.5 GB too bigvery close to the originalHugging Face →
Q5_K_M
GGUF · city96
13.0 GB15.8 GB9.8 GB too bigclose; small differences in fine detailHugging Face →
Q4_K_M ←
GGUF · city96
11.5 GB14.3 GB8.3 GB too biggood; some loss in fine detail and textHugging Face →
Q3_K_M
GGUF · city96
8.8 GB11.6 GB5.6 GB too bignoticeable loss of detailHugging Face →
Q2_K
GGUF · city96
6.6 GB9.4 GB3.4 GB too bigheavy loss; a last resortHugging Face →

Sizes from the Hugging Face file listing, read 2026-09-25. “Needed” = file + 2 GB working memory for this model + 0.8 GB kept free for the system.

03The text encoder

CLIP-L + CLIP-G + T5-XXL + Llama 3.1 8B: 15.9 GB as FP8 (all four together: CLIP-L 0.25 + CLIP-G 1.39 + T5-XXL FP8 5.16 + Llama 3.1 8B FP8 9.08 GB). ComfyUI encodes the prompt first and can push the encoder out of VRAM before sampling, so it does not have to fit together with the model. On 6 GB the encoder itself is too big for VRAM, so let it run from system RAM: slower prompt encoding, same images.