Wan 2.2 — implementation by Spacelike AI

MoE video diffusion · 27 B total / 14 B active · Alibaba Tongyi Lab

Wan 2.2 final-sample output generated by Spacelike AI.

Wan 2.2, released July 28, 2025, is the first open-source video diffusion model with a Mixture-of-Experts backbone. The T2V-A14B variant routes between a high-noise expert (early denoising / layout) and a low-noise expert (late denoising / detail) based on signal-to-noise ratio, giving it 27 B total parameters while using only 14 B per step.

A companion 5 B dense model (TI2V-5B) pairs a 4×16×16 high-compression 3D VAE with a unified text- and image-to-video head, generating 720p 24 fps clips on a single consumer GPU. Shown here is a single-frame sample from an A14B text-to-video trace.

Specification

Architecture
MoE flow-matching DiT · 2 experts · 3D VAE
Parameters
27 B total / 14 B active per step (T2V-A14B)
Training objective
Flow matching · SNR-routed expert gating
Native resolution
1280 × 720 · 24 fps · up to 5 s
Text encoder
UMT5
Sampler shown
Flow-match Euler · 50 steps · cfg 5.0
License
Apache 2.0
Release
July 28, 2025
Checkpoint
Wan2.2-T2V-A14B

Client: Tenstorrent Inc. — performance optimization.

implementation · Hugging Face · Vendor announcement

Live sample on the Spacelike AI home page.

Sample images on this page are licensed under CC BY 4.0 — reuse with attribution to Spacelike AI and a link back to spacelike.ai.

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sigma 14.6 · latent noise
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