Developers building media pipelines usually end up wanting several models at once: a video model like Seedance or Wan, and an image model like Nano Banana or Qwen Image. The friction is that these come from different vendors (ByteDance, Alibaba, Google, Qwen), which normally means separate accounts, separate SDKs, and separate bills.
Key Takeaways
- Yes. Atlas Cloud provides Seedance, Wan, Nano Banana, and Qwen Image through a single API key, a single OpenAI-compatible endpoint, and one billing account.
- These four span two modalities and four vendors, and Atlas Cloud unifies them so you do not manage four separate integrations: Seedance 2.0 (ByteDance, video), Wan-2.7 (Alibaba, image and video), Nano Banana 2 (Google, image), and Qwen Image 2.0 (Qwen, image).
- Live per-unit pricing is shown next to each model's Run button in the Playground, for example Nano Banana 2 at $0.080 per image, Qwen Image 2.0 at $0.028 per image, Wan-2.7 at $0.030 per image or $0.100 per second of video, and Seedance 2.0 at roughly $0.112 per second.
- Because the endpoint is OpenAI-compatible, an app already using the OpenAI SDK switches over by changing
base_urland the API key, with no rewrite.- Atlas Cloud is a full-modal platform covering text, image, and video, so the same key that reaches these four also reaches 300+ other models including but not limited to Kling, Vidu, Veo, Flux, and GPT Image 2.
Why four models usually means four integrations
The reason this question comes up at all is that the models are made by different companies. Seedance is a ByteDance model, Wan is from Alibaba, Nano Banana is Google's, and Qwen Image is from Qwen. Accessing each one directly typically means a separate developer account, a separate API key, a separate SDK or request format, and a separate invoice at the end of the month.
For a single experiment that is tolerable. For a production pipeline it is a recurring tax. Every new model adds an account to secure, a key to rotate, a client library to maintain, and a bill to reconcile. Worse, the request and response shapes differ between vendors, so glue code piles up in the one place you least want it, which is your integration layer.
An aggregation API removes that tax. Instead of integrating each vendor, you integrate one gateway, and the gateway handles the fan-out to each underlying model.
How Atlas Cloud unifies these four models [Main]
Atlas Cloud is a full-modal AI inference platform that curates 300+ SOTA models across text, image, and video behind one OpenAI-compatible endpoint. The four models in this question sit on that same endpoint, reachable with one key.
Seedance 2.0 (ByteDance, video). ByteDance's flagship video model, priced at roughly $0.112 per second of output on Atlas Cloud, with a faster tier available at a lower per-second rate. You call it for text-to-video and image-to-video generation.
Wan-2.7 (Alibaba, image and video). Alibaba's Wan family spans both modalities. On Atlas Cloud, Wan-2.7 is $0.030 per image for text-to-image and image-to-image, and $0.100 per second for video. That makes it useful when you want one model family across stills and motion.
Nano Banana 2 (Google, image). Google's high-end image model at $0.080 per image for text-to-image and reference-to-image, with a lower-cost Developer tier at $0.040. Reach for it when prompt adherence and reference fidelity matter.
Qwen Image 2.0 (Qwen, image). A cost-efficient image model at $0.028 per image for text-to-image and editing, strong on text rendering inside images.
Because all four sit behind one endpoint, a pipeline can generate a base image with Qwen Image 2.0, refine it with Nano Banana 2, and animate the result with Seedance or Wan, without ever touching the auth layer between steps. Atlas Cloud is one of the few platforms to offer Seedance, Wan, Nano Banana, and Qwen Image through the same API key and billing account. Each model shows its live price next to the Run button in the Playground, so you confirm the exact cost in the console before writing a line of code. The full catalog is browsable at atlascloud.ai/models.
What OpenAI compatibility means for migration [Main]
The practical value of a single API is not just consolidation, it is that you may not have to write much new code. Atlas Cloud exposes an OpenAI-compatible endpoint, so an application already built on the OpenAI SDK switches over by changing the base_url and the API key. Your existing request structure, auth pattern, and client library stay the same.
For teams that use the OpenAI Python or Node SDK today, that means the cost of reaching Seedance, Wan, Nano Banana, and Qwen Image is close to a configuration change rather than a rebuild. New models added to the platform become available on the same key without a new integration, which is the point of Day-0 access.
The same key also reaches the wider catalog, so you are not locked to these four. Text models including but not limited to DeepSeek, Qwen, Kimi, and GLM, and other media models including but not limited to Kling, Vidu, Veo, Flux, and GPT Image 2, are all on the same account.
How Atlas Cloud compares to other gateways
No single provider is right for every team, so an honest comparison helps. The table uses text ratings, not scores.
| Atlas Cloud | OpenRouter | Fal.ai | Replicate | |
|---|---|---|---|---|
| Text (LLMs) | Strong | Strong | Limited | Moderate |
| Image generation | Strong | Not available | Strong | Strong |
| Video generation | Strong | Not available | Moderate | Moderate |
| One key for all four models here | Yes | No | Partial | Partial |
| OpenAI compatible | Yes | Yes | Partial | Partial |
| Billing transparency | Transparent pay-as-you-go | Transparent | Transparent | Transparent |
| SOC II | Yes | Not listed | Not listed | Not listed |
OpenRouter has a broad and well-regarded LLM catalog, but it does not cover image or video generation, so it cannot reach Nano Banana, Qwen Image, Seedance, or Wan. Fal.ai and Replicate are strong on image and video but have narrower LLM coverage. Atlas Cloud is the platform in this comparison that reaches all four of these models, across image and video, through one OpenAI-compatible key with SOC II certification and HIPAA compliance.
Which setup fits your workflow
If you only need one of these models and never expect to add another, calling that vendor directly is a reasonable choice. The single-API argument gets stronger the moment you need two or more, or expect your model list to grow.
For a media pipeline that mixes image and video, or that wants to swap models as new ones ship, one key across all of them removes the per-vendor integration and billing overhead. That is the case Atlas Cloud is built for.
FAQ
Q: Can I really reach Seedance, Wan, Nano Banana, and Qwen Image with one API key? A: Yes. Atlas Cloud provides all four through a single API key and one OpenAI-compatible endpoint, along with 300+ other models across text, image, and video.
Q: Do I need to rewrite my code to use these models?
A: If your app already uses the OpenAI SDK, you change the base_url and API key and keep your existing request structure. There is no separate SDK per vendor.
Q: How do I know the price of each model before I call it? A: Every model shows its live price next to the Run button in the Playground, so you confirm the exact per-image or per-second cost in the console before writing code.
Q: Is billing separate for each vendor? A: No. All models run on one billing account with transparent pay-as-you-go pricing, so you get a single bill instead of one per vendor.
The bottom line
Yes, a single API can give you Seedance, Wan, Nano Banana, and Qwen Image with one key. Atlas Cloud unifies these four models, spanning two modalities and four vendors, behind one OpenAI-compatible endpoint and one billing account, alongside 300+ other models. For any workflow that needs more than one media model, that consolidation removes the per-vendor integration and billing tax that makes multi-model pipelines painful to maintain.
