Model reference · open weights

stable-video-diffusion-img2vid-xt-1-1

Video weights Image→video 1 build Its own licence terms 801 dl/mo

stable-video-diffusion-img2vid-xt-1-1 is an open-weight video model from weights. stable-video-diffusion-img2vid-xt-1-1 (FP32) weighs 4.5 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.

  • Stable Video Diffusion 1.1 Image-to-Video is a 1.5B parameter latent diffusion model developed by Stability AI that generates short video clips from a single still image.
  • It produces 25 frames at a resolution of 1024x576, which corresponds to clips of approximately four seconds or less.
  • The model is not controllable via text prompts and has limitations regarding photorealism, motion consistency, and the rendering of legible text or faces.

Summary of the weights/stable-video-diffusion-img2vid-xt-1-1 model card, 2026-10-01

What it is

Released byweights
Released2024-06-25
Parameters1.5B
VRAM4.5 GB for the weights

What it runs on

Memory and cards for stable-video-diffusion-img2vid-xt-1-1 (FP32)

4.5 GBweights, file size
3.0 GBbiggest part
537 MBruntime overhead
CardWeightsMemory
RTX 3060 12 GBfits11.6 GB
RTX 4060 Ti 16 GBfits15.4 GB
RTX 3090 24 GBfits23.4 GB
RTX 4090 24 GBfits23.4 GB
RTX 5090 32 GBfits31.0 GB
L40S 48 GBfits44.0 GB
A100 80 GBfits78.2 GB
H100 80 GBfits78.1 GB
RTX PRO 6000 Blackwell 96 GBfits93.8 GB
DGX Spark (GB10) 128 GB unifiedfits107 GB
H200 141 GBfits138 GB
B200 180 GBfits176 GB

Running it yourself

Run it on a rented GPU

Rent a machine by the hour. ComfyUI is installed on it. Open ComfyUI through the tunnel and load the workflow from the model's card on Hugging Face; choose this model's file in its loader.

# on your rented machine: pip install diffusers transformers accelerate ftfy
import torch
from diffusers import DiffusionPipeline
from diffusers.utils import export_to_video

pipe = DiffusionPipeline.from_pretrained("weights/stable-video-diffusion-img2vid-xt-1-1", torch_dtype=torch.bfloat16).to("cuda")
frames = pipe(prompt="a drone shot over a forest at sunrise").frames[0]
export_to_video(frames, "/workspace/out.mp4", fps=16)
Renting a GPU: connect, tunnels, Python
# 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 (4.5 GB)
get weights/stable-video-diffusion-img2vid-xt-1-1 svd_xt_1_1.safetensors checkpoints

start-comfyui
Renting a GPU: connect, tunnels, 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
© 2026 AxForge · EU-hosted AI infrastructure Pricing Docs Trust Privacy Terms