A unified AI API: one endpoint, every provider dialect

Routing many models behind one endpoint solves half the fragmentation problem. The other half is dialect: OpenAI's SDK expects /chat/completions, Anthropic's SDK expects /messages, and OpenAI's newer Responses API expects /responses. A unified AI API implements all three request shapes on one surface, so whichever SDK your codebase already speaks keeps working unchanged.

Because the contract is the standard API, you keep the client library you have and just point it at AnyRouter. An OpenAI client:

from openai import OpenAI

client = OpenAI(base_url="https://anyrouter.dev/api/v1", api_key="sk-ar-v1-...")
resp = client.chat.completions.create(
  model="anthropic/claude-opus-4-8",
  messages=[{"role": "user", "content": "Hello"}],
)

…or an Anthropic client, against the same account and key:

from anthropic import Anthropic

client = Anthropic(base_url="https://anyrouter.dev/api", api_key="sk-ar-v1-...")
msg = client.messages.create(
  model="anthropic/claude-opus-4-8",
  max_tokens=256,
  messages=[{"role": "user", "content": "Hello"}],
)

A unifying layer is only safe if leaving it is easy. Every surface here is a public standard, not a proprietary protocol — the same code points straight back at OpenAI or Anthropic if you ever move on. Model ids become provider/model strings, so choosing a model is a config value, and you get one key, one bill, and one audit log across every dialect.

This is the contract side of the story. For the routing side — automatic failover and provider preferences across 170+ models — see /blog/one-api-every-llm.