When you are building small AI apps, the first few demos usually feel cheap.
Then you start testing more prompts, adding retries, generating longer outputs, letting friends try it, and suddenly the API bill becomes part of the product decision.
For indie developers and vibe coders, this is a real problem: many ideas are not ready for expensive infrastructure yet. They just need a cheaper way to validate whether the workflow is useful.
The simple pattern
If your app already uses an OpenAI-style API client, the easiest migration path is usually:
const client = new OpenAI({
apiKey: process.env.API_KEY,
baseURL: "https://your-compatible-endpoint.com/v1"
})
In many cases, you do not need to rewrite your app. You only change:
- base_url
- API key
- model name
When this works well
This pattern is useful for:
- side projects
- internal tools
- AI workflow demos
- vibe coding experiments
- early SaaS prototypes
- low-cost user testing
It is not magic, and it is not a replacement for evaluating model quality, latency, privacy, and reliability for your own use case.
Why I built DeepAPI
I'm building DeepAPI as a lower-cost OpenAI-compatible API endpoint for solo builders and small teams.
The goal is not to pretend every model is the same. The goal is to make prototyping cheaper and easier when you are still testing ideas.
Current public models include:
- deepapi-everyday
- deepapi-advanced
- deepapi-vision
New users can register directly. Credits are topped up manually for now because this is still an early-stage builder project.
Site: https://deepapi.click
GitHub: https://github.com/ouyangevan-ui/deepapi-proxy
What I'm looking for
I'd love feedback from other builders:
- Is the pricing page clear?
- Are the docs enough to test quickly?
- What examples should I add first?
- Would you use this for prototypes or side projects?
Top comments (0)