What Wan 2.2 image-to-video does
Wan 2.2, released in July 2025 under the Apache 2.0 licence, is the successor to Wan 2.1 in Alibaba's line of open video models. The image-to-video variant, Wan2.2-I2V-A14B, uses a mixture-of-experts diffusion transformer: one expert handles the early, noisy steps that set the overall layout, another handles the late steps that refine detail. About 14 billion parameters are active per step out of 27 billion in total. A smaller hybrid model, Wan2.2-TI2V-5B, accepts both text and an image and runs on a single consumer card.
You give the model a picture, which becomes the first frame of the clip, and a prompt that says what should move. It generates 81 frames at 16 frames per second, about five seconds, and builds the clip on that picture: faces, clothes and lighting stay close to the source while the camera or the subject moves.
How to write the motion prompt
The image already carries the subject, the style and the composition, so the prompt only needs to describe the change. Write one or two short sentences: who or what moves, how, and what the camera does. "The woman turns her head to the right and smiles, soft wind in her hair, slow push-in" works; a list of style tags does not. Mention the camera explicitly when it matters: "static camera", "slow pan to the left", "the drone rises".
Keep the motion plausible for a five-second clip. One action per prompt is the safe choice. Verbs such as walks, waves, blinks, flows, drifts, rotates give predictable motion. Avoid asking for things that are not in the picture: the model can move a car, but it has to invent the road behind, which is less dependable than what the picture already shows. A negative prompt has an effect only when the guidance is above 1; the 4-step Lightning LoRA workflows run at 1 and ignore it. Otherwise the usual list works: blurry, distorted hands, extra limbs, flickering, watermark, text.
Settings that matter
- Resolution: 480p is about three times faster than 720p and often enough for social media; use 720p for a final clip.
- Frames: 81 frames at 16 fps is the standard five-second clip. Longer sequences drift; better to generate two clips and cut.
- Steps: 40 sampling steps in the official script, 20 in the basic ComfyUI workflow. With the 4-step Lightning LoRA, 4 to 8 are enough.
- Guidance (CFG): 3.5 by default for the 14B I2V model, and 1 with the 4-step LoRA. Higher values follow the prompt more literally but add flicker.
- Seed: as in Stable Diffusion, the same image, prompt, settings and seed reproduce the same clip; change only the seed to get another motion for the same picture.
Test the prompt at 480p before spending time on 720p. The seed does not carry over: at 720p the noise has another shape, so the motion changes.
Which images animate best
Wan 2.2 works from any photo or AI-generated image, but some pictures are much easier. A clear main subject on a simple background gives clean motion; crowded scenes make the model choose what to move. The clip takes the aspect ratio of the picture, so portrait and landscape both work. In ComfyUI, set a width and height with the same ratio, or the image is cropped. Sharp, well-lit pictures hold detail through the clip if they are at least as large as the output (832 pixels on the long side at 480p, 1280 at 720p); a blurry or heavily compressed source produces a blurry video.
Images generated with Stable Diffusion, SDXL or Flux animate very well, which makes image-to-video the easiest way to get a short video with a precise look: generate the exact frame you want first, then animate it.
Running Wan 2.2 I2V at home
The weights are on Hugging Face and run in ComfyUI, in Diffusers and in the official Wan repository. With the official script, which Alibaba says needs an 80 GB card, the 14B I2V model peaks at about 41 GB of VRAM at 480p and 60 GB at 720p. In ComfyUI it runs on a 24 GB card with the fp8 quantised checkpoints and offloading, at the cost of several minutes per clip. The 5B TI2V model generates a 720p, five-second clip on an RTX 4090 in under ten minutes and needs about 24 GB of VRAM with the official script; in ComfyUI it fits on an 8 GB card. Below that, use a cloud GPU or the free demo on this site.