The AI video generation landscape has shifted dramatically in 2026. Models like Seedance 2.0, Kling v3.0, Wan-2.7, Vidu, and Hailuo now produce cinematic-quality footage from a single prompt — but nearly all of them are closed-source, cloud-hosted, API-only models.
For ComfyUI users, this creates a real infrastructure gap. ComfyUI was designed to run local model weights through a node-based graph. Cloud video models don’t ship weights — they expose APIs. Bridging that gap individually means managing five separate API keys, five custom node sets, and five billing dashboards.
Atlas Cloud is a full-modal AI inference platform that closes this gap with one unified, OpenAI-compatible API. ComfyUI users can reach Seedance, Kling, Wan, Vidu, Hailuo, and 300+ other models through a single integration — without rebuilding their workflow for each provider.
Why ComfyUI Can’t Natively Run Cloud Video Models Like Seedance and Kling
ComfyUI’s core architecture is built around local diffusion model weights. A node loads a checkpoint, processes a latent through a sampler, and decodes the output. That pipeline works well for models you can download and host yourself.
Cloud video models like Seedance 2.0 and Kling v3.0 work differently. They never expose downloadable weights — generation happens on the provider’s proprietary infrastructure and is returned as a video file via API response. There is no checkpoint to load into ComfyUI’s default nodes.
The typical workaround is installing third-party custom node packages, one per provider. That approach fragments your workflow quickly:
· Each provider uses a different authentication format
· Node packages go out of date independently
· Billing and usage monitoring are spread across multiple dashboards
· Switching models mid-project means context-switching between completely different node sets
Consequently, the fragmentation grows proportionally to the number of video models a creator or developer wants to use. For teams that want Seedance, Kling, Wan, Vidu, and Hailuo available simultaneously, the maintenance overhead alone can outpace the creative work.
How Atlas Cloud Connects ComfyUI to 300+ Models Through One API
Atlas Cloud provides one API key, one endpoint, and one consolidated account for 300+ SOTA models across text, image, and video. The platform is OpenAI-compatible — an API pattern that works with familiar OpenAI-style SDK calls — which means existing ComfyUI HTTP request nodes can reach Atlas Cloud without custom wrappers.
In practice, the setup takes minutes. Developers update base_url to point to Atlas Cloud’s endpoint, add their API key, and select the target model by name in the request payload. The same node handles Seedance one request and Kling the next — no node swaps, no re-authentication.
Atlas Cloud also exposes a native MCP Server — a protocol layer that lets AI tools connect with external services — and integrates with developer tools including n8n, Cursor, VS Code, and Claude Desktop. For ComfyUI specifically, this means video model access can sit inside a broader automated pipeline alongside other modalities without introducing a separate auth system.
More specifically, the unified billing layer removes one of the most persistent pain points for production teams: unpredictable costs spread across providers. With Atlas Cloud, every video generation — regardless of which model it calls — appears in one consolidated usage report.
Which Video Models You Can Use in ComfyUI Through Atlas Cloud
Atlas Cloud’s video catalog includes the five models named in this article’s title, plus several additional options for specialized tasks.
| Model | Task | Price |
| Seedance 2.0 | Text-to-Video | ≈ $0.096/s |
| Kling v3.0 Std | Text-to-Video | $0.071/s |
| Wan-2.7 | Text-to-Video | $0.1/s |
| Vidu Q3-Pro | Text-to-Video | $0.042/s |
| Hailuo-2.3 | t2v Standard | $0.28/s |
Most models also support image-to-video and reference-to-video at comparable pricing. Seedance 2.0 Image-to-Video runs at ≈ $0.096/s; Kling v3.0 Pro Image-to-Video at $0.095/s; Hailuo-2.3 i2v Standard at $0.28/s.
That said, video is only one modality. The same API key reaches image models like Seedream v5.0 Lite and Wan-2.7 Text-to-image, and LLMs including DeepSeek, Qwen, and Kimi. All are routed through the same endpoint, making Atlas Cloud a practical foundation for workflows that mix generation types within a single ComfyUI graph.
How to Set Up the Atlas Cloud ComfyUI Integration
The integration requires three steps:
1. Open an Atlas Cloud account at atlascloud.ai and retrieve your API key from the console.
2. Add an HTTP Request node in ComfyUI — or use an existing custom node that supports external API calls — and set the endpoint to Atlas Cloud’s unified API.
3. Update base_url and your API key in the node configuration, then specify the target model name in the request payload.
For teams already using the OpenAI SDK in other parts of their stack, Atlas Cloud works as a drop-in replacement. No request logic needs to be rewritten — only base_url and the model parameter change. Switching from Seedance to Kling is a one-line edit in the payload.
What You Can Build in ComfyUI With These Models
Access to multiple cloud video models through one API key opens up multi-stage production workflows that were previously impractical to wire together inside ComfyUI.
A typical content production graph might look like this: a prompt enters a text node, routes to Wan-2.7 Text-to-video for a fast concept draft at $0.1/s, then passes the best output frame to Kling v3.0 Pro Image-to-Video for a higher-fidelity extension at $0.095/s. The same graph can branch in parallel — sending the same prompt to Seedance 2.0 simultaneously and routing both outputs to a comparison node before a human review step.
Three workflow patterns become practical when all five models share one API key:
· Chained generation: Use Vidu Q3-Pro at $0.042/s to iterate quickly on motion concepts, then route the approved concept to Seedance 2.0 or Hailuo-2.3 Pro for final output — without rewiring the graph between rounds.
· Parallel A/B comparison: Route one prompt to Kling and another to Wan simultaneously, compare outputs inside ComfyUI, and select the keeper before passing downstream.
· Mixed-modality pipeline: Generate a reference image with Wan-2.7 Text-to-image ($0.03/张), pass it to Hailuo-2.3 i2v Standard for animation, then feed the output to a Video Upscaler — all within one connected graph, billed to one account.
This level of workflow composability is what a unified API makes practical. Each model swap is a parameter change, not a node rebuild. As a result, teams can ship faster without rewriting core application logic each time a newer model releases.
Conclusion
For ComfyUI users who want to work with Seedance, Kling, Wan, Vidu, and Hailuo in a single workflow, the most direct path is through a unified API that handles authentication, routing, and billing in one place.
Atlas Cloud gives developers access to all five models — and 300+ others — through one API key and one OpenAI-compatible endpoint. Setup takes minutes: open an account, update base_url, and the entire video model catalog is available from any HTTP-capable node in ComfyUI.
Explore the full model list or open the Atlas Cloud console to make your first API call.
