AI VIDEO API GUIDE
Catalog verified August 2, 2026
Best AI video
generation API for agents
For most AI-agent workflows, start with Veo 3.1 when output polish is the priority, Seedance 2.0 for repeatable multimodal video work, or Kling 3.0 for cinematic motion. The bigger decision is the runtime: an agent needs live model discovery, schema inspection, durable task recovery, and output delivery—not only an API endpoint.
Which AI video API should an agent choose?
| Model | Best fit | Modes | AnyCap ID | Credit estimate |
|---|---|---|---|---|
| Veo 3.1 | Premium video output, polished motion, and story-driven clips where the first pass needs to look strong. | text-to-video, image-to-video | veo-3.1 | ~20 credits / second |
| Seedance 2.0 | High-quality cinematic and product video workflows where agents need the newer Seedance model entry. | text-to-video, image-to-video | seedance-2 | Varies by catalog pricing |
| Kling 3.0 | Cinematic motion, realistic scene animation, and image-to-video workflows that need controllable camera dynamics. | text-to-video, image-to-video | kling-3.0 | ~9 credits / second |
| Hailuo 2.3 | Short narrative clips, expressive character motion, visual storytelling, and reference-image animation. | text-to-video, image-to-video | hailuo-2.3 | Varies by catalog pricing |
| Sora 2 Pro | High-end narrative, cinematic, product, and realistic video generation when teams want an OpenAI video model through the same CLI. | text-to-video, image-to-video | sora-2-pro | Varies by catalog pricing |
Availability, IDs, modes, and estimates come from the current AnyCap catalog. Provider announcements are not treated as callable API support until discovery and live execution are verified.
What makes a video API agent-ready?
Discovery before generation
An agent should be able to list active models and inspect their schema instead of relying on a model name copied from an old prompt.
Text and reference inputs
The API should expose whether a model starts from text, images, video, or multimodal references so the agent can choose a valid path.
Durable task handling
Video calls are long-running. A production agent needs polling, recovery, download, and a stable output reference—not only a synchronous demo response.
One contract across models
A shared command and authentication layer lets an agent switch models without rebuilding provider-specific glue for every experiment.
A durable AI video generation workflow
1. Discover
List the current video catalog and filter by supported input mode.
2. Inspect
Read the selected model schema before constructing the generation request.
3. Generate
Submit the prompt and references through a durable task that can be resumed.
4. Review
Inspect the resulting clip, then route it into analysis, Drive, Page, or another agent step.
Where Seedance 2.5 fits
Seedance 2.5 is now a featured callable model on AnyCap. Agents can discoverseedance-2.5, inspect its live schema, and generate from text, images, first and last frames, or multimodal references without adding a separate provider SDK or authentication path.
AI video API questions
What is the best AI video generation API for an AI agent?
The best API is the one the agent can discover, inspect, call, recover, and route without provider-specific glue. Through AnyCap, Veo 3.1 is a strong premium default, Seedance 2.0 suits repeatable multimodal video work, and Kling 3.0 is useful when cinematic motion matters.
Should an agent use one video model for every task?
No. Text-to-video, image-to-video, reference-heavy generation, preview speed, cinematic motion, and cost are different requirements. Model discovery should happen inside the workflow rather than being hard-coded forever.
Is Seedance 2.5 available through the AnyCap API?
Yes. AnyCap exposes Seedance 2.5 as seedance-2.5 for text-to-video, image-to-video, first-last-frame-to-video, and multi-modal-reference generation. Inspect the live schema before sending references.
Why use a CLI instead of calling each provider SDK?
A CLI gives coding agents an automation-friendly surface they can invoke from the same workspace. It also centralizes authentication, model discovery, schema inspection, task recovery, and output delivery.