Best AI for generating video

Why Seedance 2.5 leads, and why that lead is conditional

This component takes two columns of the rubric outright. Length: 30 seconds in a single generation pass, against fifteen seconds for Kling and eight for Veo. Reference capacity: 50 input files — 30 images, 10 videos, 10 audio clips — against seven and three for its competitors. For any workload that requires holding a character consistent across a narrative, these two figures outweigh every other parameter.

The same component loses the resolution column entirely. ByteDance own API technical documentation permits only two values, 480p and 720p, for Seedance 2.5, while listing four values up to 4k for Seedance 2.0. In that single parameter, the newer version has regressed against its own predecessor. The same regression shows up again in Runway API schema, which resells this model.

So which workload should select Kling

Any workload where the final output ships directly to a client. Kling VIDEO 3.0 is the only component in this rubric that delivers native 4K, and native is the parameter that matters: post-generation upscaling shifts facial position, and character consistency breaks down between shots. Its fifteen seconds are sufficient for an advertising shot. One constraint is documented by the vendor itself and carried here as well: its reference-driven mode (Omni) caps at 1080p, so native 4K and heavy reference input cannot be combined in a single generation pass.

The parameter none of the four components cover

Persian. Kling own technical guide lists five spoken languages: Chinese, English, Japanese, Korean and Spanish. Persian is not on that list, and none of the other three components registers Persian in its spoken-language list either. So for any workload requiring Persian output, regardless of which component is selected, voice production is a separate stage in the pipeline. If you have read somewhere that one of these speaks Persian, ask for the source.

Two parameters deliberately excluded from the rubric

First, generation time. The owner of this reference had requested that generation speed carry an independent weight, and that request is operationally sound, since in real workloads wait time converts directly into cost. But not one of these four vendors has published a generation-time figure. A figure that has not been published is not sourced from an unofficial source, so this column was never built; its place in the data model stays empty until a vendor publishes that figure.

Second, price. Runway API price list is the only source that prices several components in one currency and one unit: one credit equals one cent, Gen-4.5 costs twelve credits per second, Seedance 2.5 at 720p costs thirty credits per second, and Veo 3.1 with audio costs forty credits per second — twelve, thirty and forty cents per second of output, respectively. Kling is not on that list, and its pricing is credit-based and tied to a subscription tier. A column that leaves a quarter of the table empty and fills the rest with a reseller price is more misleading than useful.

Why Sora is not registered in this rubric at all

Because no document from OpenAI has been read. All three domains — openai.com, sora.com and sora.chatgpt.com — return a 403 status to our server, both through our own fetch tooling and through plain curl. Even the current version name of Sora is unconfirmed, and a version name that has not been observed is not entered into this reference. No empty row was created for it either, because this rubric ranks versions, and no version name is available to us. The day these domains open up, the corresponding row will be added.

Components not yet assessed

Higgsfield was reviewed, and what it offers turned out not to be its own model: it serves Seedance 2.5 and other vendors models on its own platform, exactly as Runway does. So it has no place in a rubric that measures models. Hailuo, Grok Imagine and Luma have not yet been evaluated; their absence from this table means the assessment has not been scheduled, not that they have been disqualified.