Can the RTX 5070 Laptop 8 GB run HiDream-I1 (Full)?
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.
Worth trying on this GPU: 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
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | hidream-i1-full-Q2_K.gguf Q2_K · city96/HiDream-I1-Full-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). 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: 32 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 22.8 GB, plus roughly 6 GB for Windows, ComfyUI and a browser: 28.8 GB in total. With less RAM it still runs, but Windows starts swapping to disk and loading gets very slow. calculated
02Every HiDream-I1 Full 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 → |
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 8 GB the encoder itself is too big for VRAM, so let it run from system RAM: slower prompt encoding, same images.
04About this GPU
The RTX 5070 Laptop 8 GB is a Blackwell GPU with FP8 and FP4 hardware: ComfyUI computes Comfy-Org's FP8 files natively here, and NVFP4 files (where a model offers them) are faster still. As a laptop GPU it runs at a lower power limit than desktop cards (50–100 W depending on the laptop). The memory verdicts are the same; speed depends heavily on how much power the laptop maker allows.
RTX 5070 Laptop 8 GB: 8 GB GDDR7 · 128-bit · 384 GB/s · Blackwell · 50–100 W. Everything that runs on the RTX 5070 Laptop 8 GB →
05What more VRAM would change
With 20 GB you could run HiDream-I1 Full at 8-bit or better (FP8, 17.1 GB) with no offloading.
06Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run HiDream-I1 Full on a RTX 5070 Laptop 8 GB, send your time per image and peak VRAM and it will appear here, credited.
07Questions
How much VRAM does HiDream-I1 Full need?
Around 9.4 GB with the smallest file (Q2_K) and 19.9 GB with an 8-bit file (FP8), counting working memory and a small system reserve. The full 16-bit file needs about 37.0 GB.
Which HiDream-I1 Full file should I download for the RTX 5070 Laptop 8 GB?
Q2_K (6.6 GB) from city96/HiDream-I1-Full-gguf. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.
Is FP8 faster than GGUF on the RTX 5070 Laptop 8 GB?
It can be. This GPU has FP8 hardware, and ComfyUI computes FP8 natively for files made for it (Comfy-Org's fp8_scaled files), or for any FP8 file with the --fast fp8_matrix_mult option. GGUF files are unpacked on the fly, which costs some speed.
How much do I need to download for HiDream-I1 Full on the RTX 5070 Laptop 8 GB?
About 22.8 GB for the model file, text encoder and VAE listed on this page, and the same again free on disk. With a 8 GB card, 32 GB of system RAM or more is recommended.