Best AI video model for UGC-style ads: a model or an avatar?

For a UGC-style ad where a person speaks to camera, use an Avatar video when you control the script word for word, and a video model with native audio when you want a scene, not a presenter. Avatar jobs run from a ready avatar and a script of about 4 to 60 seconds. Video models generate the person, the scene and the sound together from a prompt, in clips of up to 10 to 30 seconds depending on the row. Neither route is the "best" one in general; they solve different briefs.

What does each route accept?

The Avatar route is documented as POST /v1/avatar-1.0/talking-video, with a top-level avatar_handle and one of script or video_inputs. Sume accepts scripts and plans whose estimated duration is 4 to 60 seconds inclusive; longer ones must be split into several jobs. Optional product and scene inputs are a product_image and a scene (a prompt or a photo).

Which video model for spoken lines?

Kling's own guide for VIDEO 3.0 lists native audio with Chinese, English, Japanese, Korean and Spanish, regional accents, and scenes with three or more characters speaking. On Sume the kling-3 row is 1080p only, 4-15 s, in 16:9, 9:16 or 1:1, with first and end frame but no reference images. Gemini Omni Flash 1.1 always produces synced audio and is the default behind sume/auto; wan-3.0 and seedance-2.5 also list audio. The Sume docs make no promise about speech quality per language, so run a short test on your own line before buying a batch.

How should I decide?

Ask three questions. Do you need the exact words, with no drift? Use the avatar. Do you need the person in a specific place with product handling? Use a model row and a first frame. Do you need more than 15 seconds? Avatar goes to 60 s; wan-3.0 and seedance-2.5 go to 30 s. For a 30-second spoken ad, one job on either of those two is simpler than stitching, but check the result for consistent faces across the whole clip.