Wan is the AI video family from Alibaba’s Tongyi research group. Wan 2.2 was a 2025 release that brought open MoE architecture to the video field; Wan 2.5 is the iteration that polishes motion stability and pushes clip length. The model is positioned for developers who need permissive licensing and a fallback to open weights.
I ran Wan 2.5 through the standard three-test methodology, comparing it to Veo 4 and Kling 3 on the same prompts.
What is Wan 2.5?
Wan 2.5 is Alibaba’s text-to-video model, the latest in the Wan series. The model produces up to 8-second clips at 720p with a focus on motion stability and prompt fidelity rather than peak photorealism.
Distribution is through the Alibaba Cloud / Tongyi platforms and through Hugging Face for the weights. Apache-style licensing makes it a real option for commercial fine-tuning, similar to Hunyuan Video.
How I got access
Through an Alibaba Cloud Tongyi account for the hosted version, plus a Hugging Face inference endpoint for the open weights. Both worked; the cloud version is faster for iteration.
The test results
Test 1. Photorealistic outdoor scene
Prompt: “A small fishing boat rocking on calm sea at golden hour, slow camera dolly forward. 8 seconds, 720p.”
Wan 2.5 produced a steady, coherent shot with correct lighting and natural wave motion. The boat identity held. For 720p brand b-roll, the result is fully postable.
Test 2. Motion-heavy action
Prompt: “Two dancers in a studio executing synchronized turns under stage lighting. 6 seconds.”
Synchronization across two characters is genuinely hard. Wan 2.5 held it in three of five takes; the other two had a beat-off-sync moment. For dance and choreography content, the model is competitive.
Test 3. Prompt adherence test
Prompt: “A barista in a green apron pouring oat milk into an espresso, slow pour, latte art forming. Wide overhead shot.”
Prompt fidelity is where Wan 2.5 closed the gap. Apron color, pour direction, and latte art formation were correct on four of five takes. Veo 4 produces a smoother result; Wan 2.5 is the open alternative with comparable prompt following.
The annoying parts
Documentation gap. English documentation is improving but still inconsistent. Most developers need to cross-reference with Chinese-language sources.
No native audio. Wan 2.5 is visual-only. Audio still requires a separate pipeline.
720p ceiling. Production-quality output tops at 720p. For 4K work, Kling 3 is the better choice.
Is it worth the price?
For developers wanting permissive licensing and an open-weights option, Wan 2.5 is the clear pick over closed-source competitors. The cloud version sits at the developer-friendly end of the per-second pricing band.
For consumer creators, the lack of a polished app pushes most users to managed platforms or aggregators.
How Vuela.ai fits into a Wan workflow
Wan 2.5 is the open-leaning alternative when you need permissive licensing or a fallback to self-host. Vuela.ai exposes Wan-class generation in the catalogue alongside Veo, Kling, Sora, and the rest, so you can pick the right model without managing infrastructure.
For audio, cloning, and translation, Vuela.ai layers them on top.
Wan-class video plus the rest of the pipeline
Vuela.ai gives you Wan-class output plus cloner, translator, audio, and 70+ tools on one flat plan.
The verdict
Wan 2.5 is the open-leaning fallback for teams that need permissive licensing. Quality is competitive on prompt fidelity and motion, slightly behind Veo 4 and Kling 3 on premium output.
Use Wan when licensing matters; use the closed models when peak quality matters. Vuela.ai gives you both.