Runway vs Kling vs Veo: choosing an AI video API

When you set out to add AI video generation to a product, the first real decision isn't which prompt to write — it's how you integrate at all. There are two shapes to choose from, and they have very different consequences for your codebase. You can integrate a single-model provider, or you can integrate a unified AI video API. This post lays out the structural difference honestly, then gives you a checklist for deciding which fits your project.

The core trade-off

Integrating a single provider — Runway, Luma, Heygen, Synthesia, or any other — gives you exactly one thing: that provider's model, reached through that provider's SDK, with that provider's auth and response shape. If the model fits your need, that's a clean, direct integration.

A unified API gives you many models behind one key and one request shape. Veo, Kling, Seedance, Wan and more are all reachable through the same endpoint. The practical consequence is concrete: switching models is a one-field change. You edit the model_id in your request body and the rest of your integration stays exactly as it was — no new SDK, no second set of credentials, no re-integration. That's the structural fact. Whether it matters to you depends on whether you expect to swap models, which is the next question.

How to actually choose

Rather than ranking models, ask what your project actually needs and map each need to a model family. Reach for a given model when the job calls for it — none is strictly "better" than the others.

• Do you need one specific model, or the freedom to swap? If you already know one model is the right tool and you'll never change it, a single-model integration is enough. If you expect to compare options or move as new models ship, the one-field swap of a unified API is the point.
• Do you need audio generated in the same pass? When a clip has to come back with synchronized dialogue, ambient sound, or music baked in alongside the picture, reach for Veo — generating audio in-pass is its strength.
• Do you need multi-shot sequences? When a single prompt has to become a sequence of cuts rather than one continuous take, reach for Kling for the shot structure.
• Do you need multimodal references? When text alone can't capture the character, product, or motion, and you want to combine image, video, or audio references in one call, reach for Seedance.
• Do you need to edit existing footage? When you already have a clip and want instruction-based edits, reference-to-video, or extend operations, reach for Wan.
• One vendor relationship, or many? A single provider means one contract and one bill. A unified API means one relationship that covers many model families at once. Pick the operational shape that fits how your team buys.

Cost discipline

A unified API makes cost control a workflow rather than a guess. Iterate on a cheap Lite or Fast tier while you're still tuning the prompt — drafts don't deserve premium rates. Once the prompt is locked, switch the model_id to a premium tier for the final render. It's the same endpoint, so the swap costs you nothing in engineering time. And because the exact per-model credit cost is queryable with GET /api/ai/models before you call, the price is never a surprise. We won't quote numbers here that could go stale — query the catalog and you'll see the current cost for any model.

The request lifecycle

One reason the model swap is so cheap is that the request lifecycle is shared across every model:

• Create a job. Send POST /api/ai/jobs with a model_id and a prompt (plus any model-specific options). You get back a job id.
• Poll for the result. Call GET /api/ai/jobs/{id} until it reports done, then read the output URL. Generation is asynchronous, so you poll rather than block.

You write this loop once and it works for Veo, Kling, Seedance, Wan, and anything added later. You can compare every model on the same axes instead of reading several different sets of docs.

When a unified API is the wrong choice

Honesty builds trust, so here's the case against: if you only ever need one model, and you've already integrated it, a unified API may be unnecessary. The benefit of a single key and a one-field swap only pays off if you actually swap. A team locked to one provider for good reasons — an existing contract, a model that exactly fits, a workflow already built around its SDK — doesn't gain much by adding an abstraction layer. Don't adopt a unified API as a reflex; adopt it because you value the optionality it gives you.

Start building

If you want the freedom to pick the right model per job without re-integrating each time, start with the unified AI video API — one key, one request shape, every model. Try a prompt through the text-to-video API, then read the full request contract in the AI API docs to wire it into your pipeline.