Model reference · open weights
dreamlike-diffusion-1.0 is an open-weight image model from dreamlike-art. dreamlike-diffusion-1.0 (FP16) weighs 2.1 GB; the smallest configuration that runs it is RTX 3060 12 GB.
For self-hosting, compare this build's requirements below with the GPU you plan to rent.
Summary of the dreamlike-art/dreamlike-diffusion-1.0 model card, 2026-10-01
What it is
| Released by | dreamlike-art |
|---|---|
| Released | 2022-12-11 |
| Parameters | 860M |
| VRAM | 2.1 GB for the weights |
What it runs on
| Card | One image | Memory |
|---|---|---|
| RTX 3060 12 GB | fits | 11.6 GB |
| RTX 4060 Ti 16 GB | fits | 15.4 GB |
| RTX 3090 24 GB | fits | 23.4 GB |
| RTX 4090 24 GB | fits | 23.4 GB |
| RTX 5090 32 GB | fits | 31.0 GB |
| L40S 48 GB | fits | 44.0 GB |
| A100 80 GB | fits | 78.2 GB |
| H100 80 GB | fits | 78.1 GB |
| RTX PRO 6000 Blackwell 96 GB | fits | 93.8 GB |
| DGX Spark (GB10) 128 GB unified | fits | 107 GB |
| H200 141 GB | fits | 138 GB |
| B200 180 GB | fits | 176 GB |
From the model card
Use the same prompts as you would for SD 1.5. Add dreamlikeart if the artstyle is too weak. Non-square aspect ratios work better for some prompts. If you want a portrait photo, try using a 2:3 or a 9:16 aspect ratio. If you want a landscape photo, try using a 3:2 or a 16:9 aspect ratio. Use slightly higher resolution for better results: 640x640px, 512x768px, 768x512px, etc.
https://huggingface.co/dreamlike-art/dreamlike-photoreal-2.0
You can use this model for free on dreamlike.art!
We support a Gradio Web UI to run dreamlike-diffusion-1.0:
Download dreamlike-diffusion-1.0.ckpt (2.13GB)
This model can be used just like any other Stable Diffusion model. For more information, please have a look at the Stable Diffusion Pipeline.
from diffusers import StableDiffusionPipeline
import torch
model_id = "dreamlike-art/dreamlike-diffusion-1.0"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda")
prompt = "dreamlikeart, a grungy woman with rainbow hair, travelling between dimensions, dynamic pose, happy, soft eyes and narrow chin, extreme bokeh, dainty figure, long hair straight down, torn kawaii shirt and baggy jeans, In style of by Jordan Grimmer and greg rutkowski, crisp lines and color, complex background, particles, lines, wind, concept art, sharp focus, vivid colors"
image = pipe(prompt).images[0]
image.save("./result.jpg")
This model is licesed under a modified CreativeML OpenRAIL-M license.
Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.
Running it yourself
Rent a machine by the hour. ComfyUI is installed on it. Open ComfyUI through the tunnel: its default workflow loads a checkpoint. Choose this model's file in Load Checkpoint, with the settings its model card gives.
# on your rented machine: pip install diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
pipe = DiffusionPipeline.from_pretrained("dreamlike-art/dreamlike-diffusion-1.0", torch_dtype=torch.bfloat16).to("cuda")
image = pipe(prompt="a red bicycle on a cobbled street").images[0]
image.save("/workspace/out.png")# on your rented machine (the ssh line is on its page in the console)
# get REPO FILE FOLDER: one file into /workspace/models/FOLDER, where ComfyUI loads it from
get() { hf download "$1" "$2" --local-dir /workspace/hf-files && mkdir -p "/workspace/models/$3" && mv "/workspace/hf-files/$2" "/workspace/models/$3/$4"; }
# the model (2.0 GB)
get dreamlike-art/dreamlike-diffusion-1.0 dreamlike-diffusion-1.0.safetensors checkpoints
start-comfyui# on your computer, in a second terminal: ComfyUI in your browser at http://localhost:8188
# HOST, PORT and BOOKING are your machine's, from its page in the console
ssh -o HostKeyAlias=axforge-BOOKING -o StrictHostKeyChecking=accept-new -L 8188:localhost:8188 dev@HOST -p PORT