Model reference · open weights
Wan2.2-TI2V is an open-weight video model from Wan-AI, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
Wan2.2 💜 <a href="https://wan.video"<bWan</b</a    ｜    🖥️ <a href="https://github.com/Wan-Video/Wan2.2"GitHub</a    |   🤗 <a href="https://huggingface.co/Wan-AI/"Hugging Face</a   |   🤖 <a href="https://modelscope.cn/organization/Wan-AI"ModelScope</a   |    📑 <a href="https://arxiv.org/abs/2503.20314"Technical Report</a    |    📑 <a href="https://wan.video/welcome?spm=a2tyo02.30011076.0.0.6c9ee41eCcluqg"Blog</a    |   💬 <a href="https://gw.alicdn.com/imgextra/i2/O1CN01tqjWFi1ByuyehkTSB!!6000000000015-0-tps-611-1279.jpg"WeChat Group</a   |    📖 <a href="https://discord.gg/AKNgpMK4Yj"Discord</a   Wan: Open and Advanced Large-Scale Video Generative Models <be We are excited to introduce Wan2.2, a major upgrade to our foundational video models. With Wan2.2, we have focused on incorporating the following innovations: - 👍 Effective MoE Architecture: Wan2.2 introduces a Mixture-of-Experts (MoE) architecture into video diffusion models. By separating the denoising process cross timesteps with specialized powerful expert models, this enlarges the overall model capacity while maintaining the same computational cost. - 👍 Cinematic-level Aesthetics: Wan2.2 incorporates meticulously curated aesthetic data, complete with detailed labels for lighting, composition, contrast, color tone, and more. This allows for more precise and controllable cinematic style generation, facilitating the creation of videos with customizable aesthetic preferences. - 👍 Complex Motion Generation: Compared to Wan2.1, Wan2.2 is trained on a significantly larger data, with +65.6% more images and +83.2% more videos. This expansion notably enhances the model's generalization across multiple dimensions such as motions, semantics, and aesthetics, achieving TOP performance among all open-sourced and closed-sourced models. - 👍 Efficient High-Definition Hybrid TI2V: Wan2.2 open-sources a 5B model built with our advanced Wan2.2-VAE that achieves a compression ratio of 16×16×4. This model supports both text-to-video and image-to-video generation at 720P resolution with 24fps and can also run
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | Wan-AI |
|---|---|
| Type | Video models |
| Parameters (lead) | 5.0B |
| Variants | 2 |
| Runs with | diffusers |
| Released | 2025-07-28 |
| Popularity | 194k downloads / month |
| Likes | 761 |
| Licence | Open weights |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
Using it via the API
Once AxForge deploys wan2-2-ti2v for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (wan2-2-ti2v below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/videos/generations \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"wan2-2-ti2v","prompt":"a drone shot over a forest"}'
Licence
Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗
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