Wan 2.2 Vace Outpainting is a video-to-video outpainting model designed for extending video frames beyond their original borders, effectively generating additional scene content that blends seamlessly with the input video. It excels in providing creative video outpainting capabilities with flexible control over content style, motion continuity, and resolution quality. This model is part of the Wan VACE series known for versatility in video synthesis and editing tasks.
vs Qwen Video: Wan 2.2 focuses on photorealistic video outpainting with detailed multi-condition controls such as pose, depth, and trajectory, enabling precise scene expansion. In contrast, Qwen video models lean towards artistic and stylized generation, often excelling in anime or creative styles but with less emphasis on photorealism and temporal smoothness. Wan 2.2 thus provides more consistent realism and fluidity in extended video sequences.
vs KLING 2.0: While KLING 2.0 offers competitive video generation quality with open-source availability, Wan 2.2 surpasses it by integrating MoE architecture that reduces compute by about 50% while enhancing video detail and motion coherence. Wan 2.2 also provides more versatile control parameters for nuanced scene and motion manipulation, making it preferable for professional and commercial video synthesis tasks.
vs Haiulo 02: Haiulo 02 is known for smooth basic video synthesis but lacks advanced conditioning controls and high-resolution outpainting capabilities that Wan 2.2 robustly supports. Wan 2.2's ability to manage complex group movements and detailed CGI effects offers an edge for movie-quality video extension use cases over Haiulo 02’s simpler workflow.
vs Veo 3: Veo 3 focuses on rapid video generation with less emphasis on outpainting quality and fine control, geared more towards fast content creation. Wan 2.2, on the other hand, balances speed with fidelity, providing high-resolution, temporally consistent outpainting with flexible control inputs that Veo3 currently lacks.
Accessible via AI/ML API. Documentation: available here.
import requests, time headers = {"Authorization": "Bearer " + AIMLAPI_KEY} job = requests.post( "https://api.aimlapi.com/v2/video/generations", headers=headers, json={ "model": "wan-22-vace-fun-a14b/outpainting", "prompt": "A serene timelapse of clouds over a mountain range" }, ).json() gid = job["id"] while True: res = requests.get(f"https://api.aimlapi.com/v2/video/generations?generation_id={gid}", headers=headers).json() if res.get("status") in ("completed", "error"): break time.sleep(5) print(res["video"]["url"])
const headers = { Authorization: `Bearer ${process.env.AIMLAPI_KEY}`, "Content-Type": "application/json", }; const job = await (await fetch("https://api.aimlapi.com/v2/video/generations", { method: "POST", headers, body: JSON.stringify({ "model": "wan-22-vace-fun-a14b/outpainting", "prompt": "A serene timelapse of clouds over a mountain range" }), })).json(); let res; do { await new Promise((r) => setTimeout(r, 5000)); res = await (await fetch(`https://api.aimlapi.com/v2/video/generations?generation_id=${job.id}`, { headers })).json(); } while (!["completed", "error"].includes(res.status)); console.log(res.video.url);
# submit the generation — the response contains the job "id" curl -X POST https://api.aimlapi.com/v2/video/generations \ -H "Authorization: Bearer $AIMLAPI_KEY" \ -H "Content-Type: application/json" \ -d '{"model":"wan-22-vace-fun-a14b/outpainting","prompt":"A serene timelapse of clouds over a mountain range"}' # then poll until status is "completed" — video.url holds the result curl "https://api.aimlapi.com/v2/video/generations?generation_id={id}" -H "Authorization: Bearer $AIMLAPI_KEY"
OpenAI-compatible — swap the base URL and it works with your existing SDK.
| Type | Price |
|---|---|
| Output | |
| Model | Input | Output | Context | Best for |
|---|---|---|---|---|
Wan 2.2 Vace Outpainting This page | Video generation |
Wan 2.2 Vace Outpainting takes text, video as input and returns video.
Wan 2.2 Vace Outpainting is priced at $0.065 / gen.
Wan 2.2 Vace Outpainting is billed per generation — a fixed charge per output rather than by prompt length.
Wan 2.2 Vace Outpainting was built by Alibaba Cloud.
Send a request to v2/video/generations with wan-22-vace-fun-a14b/outpainting as the model id.
Yes. Wan 2.2 Vace Outpainting is served through AI/ML API, so the same key and endpoint format used for other models applies.
It offers video editing through outpainting, extending existing video content.
-min.webp){kind=small}
