Vidu vs Kling: Two Different Strengths

Vidu and Kling are frequently compared as if they were the same kind of tool. They are not. Vidu, from Shengshu Technology, is built around reference conditioning and facial performance — keeping one character or product stable across a sequence. Kling, from Kuaishou, is built around motion and physical plausibility, and in 2026 it is the model that renders natively at 4K rather than upscaling to it.

OpenFilmo runs the Vidu models, so this page is not going to argue that you should never open Kling. It is an attempt to say plainly which job each one is better at, because choosing wrongly wastes far more credits than choosing slowly.

What each model is actually better at

Four differences worth deciding on.

How to route a project between them

Decide by shot, not by project.

1. Tag each shot by what it depends on

   If the shot lives or dies on a face or a product staying recognisable, it is a consistency shot. If it lives on believable motion, it is a motion shot.

2. Generate the consistency shots first

   Character shots are the ones that force reshoots when they fail, so settle them before spending on the rest.

3. Keep references identical across the sequence

   The same reference set for every shot is what makes the continuity real. Re-cutting references between shots reintroduces the drift you were avoiding.

4. Assemble, then upscale once

   Do resolution work on the final cut rather than per clip, so you are not paying to enlarge takes you will discard.

Where the split lands in practice

Typical shot types and the model that suits each.

Why the honest answer is not a winner

Comparison pages that claim total victory are the ones nobody believes.

The leaderboard position of either model tells you very little about your project. Blind-vote rankings are measured on random prompts, and your work is not random — it is a specific subject, a specific look and a specific set of constraints. The only useful test is your own footage.

What can be said plainly is that Kling is stronger on physical motion and on native 4K, and that Vidu is stronger on keeping a subject consistent and on facial performance. Those are different claims, and a project usually needs both rather than one.

That is the practical argument for a single workspace holding several models: the routing decision becomes a per-shot choice instead of a subscription commitment, and you are not forced to accept a weakness in one area to get a strength in another.

Credits and plans

Generation is metered in credits, shared across every tool.

A five-second video costs 5 credits and one image costs 2. The Free plan gives you 30 credits every month with no credit card, no watermark and commercial use included. Paid plans start at $9 for 400 credits and add faster generation, parallel tasks and higher export resolution.

Related guides

Longer reads on the same workflow, from the OpenFilmo blog.

Related workflows

Closely related tools and guides on the same problem.

Frequently asked questions