I have been evaluating the three major AI video generation APIs for a project and figured this might save others some research time. Curious what experiences people here have had.

The problem

We needed to pick an AI video generation model for a production integration. The requirements: reasonable per-second cost, API access (not just a web UI), and enough documentation to satisfy our engineering review. As of March 2026, there are really three contenders – Seedance 2.0, Kling 3.0, and Sora 2. They are in surprisingly different positions.

What I found

Kling 3.0 – the budget-friendly option that is actually live

Kling 3.0 is available now with text-to-video and image-to-video. It supports 3-15 second clips at 720p or 1080p. The pricing starts at $0.075 per second, which is the lowest verified price point among the three.

For our use case (generating short product clips at scale), this looked like the most practical starting point. The flexible clip duration is a real advantage if you do not need fixed-length outputs.

Has anyone here integrated Kling 3.0 into a production pipeline? Curious about reliability and queue times.

Sora 2 – strongest documentation, higher price

OpenAI has a proper video API (`POST /v1/videos`) with `sora-2` at $0.10/s and `sora-2-pro` at $0.30-0.50/s depending on output size. Duration presets are 4s, 8s, and 12s.

The documentation is the most complete of the three – model names, endpoint specs, pricing, size presets. If your team needs to go through any kind of vendor review or procurement process, Sora 2 makes that easier. The output quality leans toward realism and physical coherence.

The downside is cost. At $0.10/s base, it is 33% more than Kling 3.0 per second. For high-volume workflows, that adds up.

Seedance 2.0 – most interesting, least accessible

This is the one I am most curious about long term. ByteDance built it around a multimodal reference workflow – you can use images, video clips, and audio as structured references during generation, not just text prompts. They describe an `@`-style reference system for directing the model. It also supports synchronized audio.

The problem: as of March 9, 2026, the broader public API story is still not straightforward. You can access it through ByteDance products like Dreamina and Doubao, but there is no simple self-serve API pricing page like OpenAI has. For teams that need to ship now, that is a blocker.

If your workflow specifically benefits from reference-driven generation (creative tools, co-pilot interfaces, enterprise content where users want more than one-shot prompting), Seedance 2.0 is worth watching closely.

My current thinking

For immediate production use, it seems like the choice is between Kling 3.0 (cost-optimized, flexible) and Sora 2 (quality-optimized, well-documented). Seedance 2.0 is a watchlist item.

The one thing that makes this comparison less painful is that if you build behind a unified API layer, switching models later does not require rewriting the integration. That is the approach we are leaning toward – start with Kling 3.0 for volume work, potentially add Sora 2 for premium outputs, and evaluate Seedance 2.0 when the API access situation clarifies.

Questions for the community

1. Has anyone here used Kling 3.0 or Sora 2 in production? What was your experience with output consistency and latency?

2. For those tracking Seedance 2.0 – have you found any clearer API access path beyond the ByteDance product integrations?

3. Are there other models I should be looking at that have launched API access recently?

4. How are you handling model switching in your video generation pipelines? Building your own abstraction layer or using a gateway?

Would appreciate any data points or experiences. Happy to share more details about our evaluation if useful.

*All pricing and availability info based on official documentation and provider changelogs as of March 9, 2026.