# Connect any OpenAI-compatible endpoint

> Point Big-AGI at vLLM, llama.cpp, LiteLLM, a proxy or a company gateway: models are scanned and join the list automatically.

- Canonical: https://big-agi.com/docs/connect-custom-endpoints
- Minimum tier: open  [Open ⊂ Free ⊂ Pro - a tier only ever ADDS to the Open baseline]
- Kind: how-to · Last content update generation: 2026-07-27 · Review by: 2027-01-23
- Answers: My provider isn't in the list - can I still use it? · Which URL and which fields do I enter? · Why do my models show no context size or price? · Can I route through a company proxy or gateway?

Any endpoint that speaks the OpenAI API connects. Big-AGI accepts what the endpoint returns without strict validation, since dialects carry fields validation would strip. That covers vLLM, llama.cpp's server, LiteLLM, an inference startup nobody has heard of, a company gateway, and proxies in front.

## Adding one

In the add-service menu, the **OpenAI** entry carries a small **Add** button on top - tooltip `Add another OpenAI-compatible service`. Press it and a new copy appears, labelled `OpenAI #2`, `#3` - type over the label to rename it, up to 32 characters. Up to ten copies can exist side by side, each with its own endpoint, key, name and route.

1. **API Endpoint** is the required field, behind the panel's **Advanced** toggle: enter your custom host. A few example services and one gateway come pre-filled - picking one fills the URL, renames the service and links its documentation.
2. A key is optional: one is required only when the effective host is OpenAI's own, so a keyless internal endpoint works with the field empty.
3. Choose whether the service uses [Direct Connection](/docs/feature-direct-connection).
4. Press **Models**: the endpoint is scanned and its models join the list.

| API Endpoint | What happens |
|---|---|
| `https://host.example/v1/` -> `https://host.example` | trailing `/v1` stripped |
| `host.example` -> `https://host.example` | scheme becomes `https` |
| appended for you | `/v1/chat/completions` · `/v1/responses` · `/v1/models` · `/v1/images/generations` · `/v1/images/edits` · `/v1/audio/speech` |

## Models without the bells and whistles

The built-in AI services ship their model metadata; a custom endpoint rarely publishes any: no context window, no price, no capability flags. The models work; they arrive plain, and stay plain until you set the numbers yourself. The gear on each model carries overrides for context window, maximum output and price, each with a **Reset**.

## Proxies and company gateways

A proxy or gateway in front of the endpoint works. Two behaviours matter.

**Only your credentials are used.** With a custom endpoint set, the key and organisation you entered are the ones sent - the deployment's own key is never substituted, so a gateway issuing its own tokens works.

**Reachability depends on the route.** With Direct Connection off, the *Big-AGI server* must reach the endpoint, so a gateway published only inside an office network fails from the hosted site. With it on, your *browser* makes the call and the endpoint's CORS policy has to allow it.

> **Direct Connection works only with your API key stored in the browser**, and with an AI service that permits direct browser calls (CORS). Where it cannot be used, requests route through the Big-AGI fast edge servers instead - everything still works, within the standard upload size and time limits.

One shape to get right: Cloudflare AI Gateway expects the account and gateway in the path - `/v1/<account>/<gateway>/openai` - and accepts only OpenAI upstream.

## Related

- [Connect an AI service](/docs/connect-models)
- [Models on your own machines](/docs/connect-models#models-on-your-own-machines)
- [Keep your key safe](/docs/key-storage)
- [Key and access errors](/docs/issue-key-and-access)