AI RACE— A Corrida da IA
Modelo de IA

Wan 2.7

Alibaba

Experimente agora ↗
Lançamento04/2026

Rankings

#49
AIM 72.5Pico: #45
#30
AIM 72.1Pico: #18
#18
AIM 77.8Pico: #13
#18
AIM 77.3Pico: #7

Análise

Wan 2.7 is a solid choice for video content teams or advertising studios—well-suited if your workflow is primarily video. However, if high-quality image generation is required, specialized image models are recommended.

Pontos fortes

  • Outstanding video generation—ranked #8 on AIM, enabling high-quality video content creation from scratch
  • Strong image-to-video capabilities—ranked #13 on AIM, ideal for animation or assembling videos from still images
  • Reliable video editing performance—ranked #21 on AIM, capable of handling video editing and enhancement tasks

Pontos fracos

  • Weak text-to-image performance—ranked #55 on AIM, unsuitable for high-quality image generation
  • Narrowly specialized in video with limited cross-domain balance—unlike general-purpose models that handle both image and video generation well

Casos de uso

Creating promotional videos, teasers, and TikTok/Instagram Reels content from scripts or still imagesAssembling illustrated stills into motion graphics or presentation videos for podcasts and blogsEditing, cutting, and enhancing existing video footage (frame extraction, adding effects)

Guias e vídeos

Wan 2.7 is a next-generation video and image generation model from Alibaba (Tongyi Lab), released in April 2026. It is accessible via online platforms such as fal.ai, InVideo, and EaseMate AI, or can be run locally thanks to its open-source license (Apache 2.0). The model supports text-to-video, image-to-video, reference-to-video, natural-language video editing, native audio sync, and first/last-frame control. Best practices: enable Thinking Mode for complex prompts so the model can reason through intent first; use multi-reference (up to 5 images) to maintain character consistency; and leverage first-frame control to directly guide the opening scene.

Análises