Can the RTX 4070 Laptop 8 GB run HiDream-I1 (Dev)?
Not entirely. Even Q2_K is 1.4 GB over 8 GB, so ComfyUI keeps part of it in system RAM.
Nothing fits entirely, but Q2_K (6.6 GB) overflows by only about 1.4 GB. ComfyUI keeps that part in system RAM automatically: slower than a full fit, but usable.
Also try the FP8 file (17.1 GB) on this GPU. 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 →
01With more VRAM
With 20 GB you could run HiDream-I1 at 8-bit or better (FP8, 17.1 GB) with no offloading.
What changes from the RTX 4070 Laptop 8 GB to the RTX 3090 24 GB →
02Every HiDream-I1 file on 8 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit SAFETENSORS · Comfy-Org | 34.2 GB | 37.0 GB | 29.0 GB too big | the original weights | Hugging Face → |
| FP8 SAFETENSORS · Comfy-Org | 17.1 GB | 19.9 GB | 11.9 GB too big | practically identical to the original | Hugging Face → |
| Q8_0 GGUF · city96 | 18.7 GB | 21.5 GB | 13.5 GB too big | practically identical to the original | Hugging Face → |
| Q6_K GGUF · city96 | 14.7 GB | 17.5 GB | 9.5 GB too big | very close to the original | Hugging Face → |
| Q5_K_M GGUF · city96 | 13.0 GB | 15.8 GB | 7.8 GB too big | close; small differences in fine detail | Hugging Face → |
| Q4_K_M GGUF · city96 | 11.5 GB | 14.3 GB | 6.3 GB too big | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_M GGUF · city96 | 8.8 GB | 11.6 GB | 3.6 GB too big | noticeable loss of detail | Hugging Face → |
| Q2_K ← GGUF · city96 | 6.6 GB | 9.4 GB | spills 1.4 GB | heavy loss; a last resort | Hugging Face → |
“Needed” adds 2 GB of working memory for HiDream-I1 and a 0.8 GB reserve. Sizes 2026-10-01.
03What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | hidream-i1-dev-Q2_K.gguf Q2_K · city96/HiDream-I1-Dev-gguf | models/unet | 6.6 GB | Download → |
| Text encoder | t5xxl_fp8_e4m3fn_scaled.safetensors T5-XXL FP8 scaled · Comfy-Org/HiDream-I1_ComfyUI | models/text_encoders | 5.2 GB | Download → |
| Text encoder | clip_l_hidream.safetensors CLIP-L (HiDream) · Comfy-Org/HiDream-I1_ComfyUI | models/text_encoders | 0.2 GB | Download → |
| Text encoder | clip_g_hidream.safetensors CLIP-G (HiDream) · Comfy-Org/HiDream-I1_ComfyUI | models/text_encoders | 1.4 GB | Download → |
| Text encoder | llama_3.1_8b_instruct_fp8_scaled.safetensors Llama 3.1 8B Instruct FP8 · Comfy-Org/HiDream-I1_ComfyUI | models/text_encoders | 9.1 GB | Download → |
| VAE | ae.safetensors FLUX.1 VAE (ae) · Comfy-Org/HiDream-I1_ComfyUI | models/vae | 0.3 GB | Download → |
| Total download · keep about the same free on disk | 22.8 GB | |||
Alternatives: T5-XXL FP16 (9.8 GB). Sizes from Hugging Face, 2026-10-01.
04The text encoder
At 15.9 GB even the smallest CLIP-L + CLIP-G + T5-XXL + Llama 3.1 8B file is too big for 8 GB, so it runs from system RAM. That slows down reading the prompt, not the picture. Sizes: FP8 15.9 GB (all four together: CLIP-L 0.25 + CLIP-G 1.39 + T5-XXL FP8 5.16 + Llama 3.1 8B FP8 9.08 GB). Why the encoder does not count against VRAM →
05Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run HiDream-I1 on a RTX 4070 Laptop 8 GB, send your time per image and peak VRAM and it will appear here, credited.
06About the RTX 4070 Laptop 8 GB
The RTX 4070 Laptop 8 GB is an Ada Lovelace GPU with hardware FP8, so ComfyUI can compute Comfy-Org's FP8 files natively: small and fast. (Plain FP8 files use FP8 maths with the --fast fp8_matrix_mult option.) As a laptop GPU it runs at a lower power limit than desktop cards (35–115 W depending on the laptop). The memory verdicts are the same; speed depends heavily on how much power the laptop maker allows.
8 GB GDDR6 · 128-bit · Ada Lovelace · 35–115 W. Everything that runs on it →
07Questions
How much VRAM does HiDream-I1 need?
Around 9.4 GB with the smallest file (Q2_K) and 19.9 GB with an 8-bit file (FP8). The full 16-bit file needs about 37.0 GB.
Which HiDream-I1 file should I download for the RTX 4070 Laptop 8 GB?
Q2_K (6.6 GB) from city96/HiDream-I1-Dev-gguf. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.
FP8 or Q8_0 for HiDream-I1 on the RTX 4070 Laptop 8 GB?
FP8 (17.1 GB): the RTX 4070 Laptop 8 GB computes it natively, while Q8_0 (18.7 GB) is unpacked on the fly.
How much do I need to download for HiDream-I1 on the RTX 4070 Laptop 8 GB?
22.8 GB: hidream-i1-dev-Q2_K.gguf, t5xxl_fp8_e4m3fn_scaled.safetensors, clip_l_hidream.safetensors, clip_g_hidream.safetensors, llama_3.1_8b_instruct_fp8_scaled.safetensors, ae.safetensors.