One endpoint, every provider, consistent behaviour. LLM Gateway handles credentials, routing, retries and cost accounting so your application code only ever talks to one API.
Every AI feature eventually meets the same problem: more than one model provider, each with its own SDK, error model, rate limits and price list. Wrapping that inside your product turns a feature into a maintenance project.
An LLM API gateway moves that work into one routing layer. Your application sends an OpenAI-shaped request, and the gateway selects the provider, applies policy, recovers from failures and records what the call cost.
The gateway becomes the only place that knows about providers, which keeps provider churn out of your codebase.
Direct calls are fine for a prototype and expensive for a product. The cost shows up as duplicated retry logic, silent price changes, single-provider outages that take your feature down with them, and no reliable answer to which customer spent what.
The gateway sits between your services and the vendors: server-side traffic, background jobs and agent frameworks all use the same endpoint, so policies and budgets apply everywhere at once instead of per team.
Short answers about the gateway, the providers and how billing works.
The routing decision is a lookup, not a model call: overhead stays in the low tens of milliseconds and is dominated by the provider response time that follows.
Yes. The API is OpenAI compatible, so official SDKs and frameworks work after changing the base URL and API key.
More than 40 providers, including OpenAI, Anthropic, Google, Meta Llama, Mistral, DeepSeek, xAI, Groq, Cohere, Perplexity, Together and Fireworks, plus custom OpenAI-compatible endpoints.
You can bring your own provider credentials, and the gateway also offers managed access so a project can start routing before every vendor account exists.
Sign in with Google, open the playground and price a request against the whole catalog before you change a line of production code.
