RelayRouter vs writing your own multi-provider LLM abstraction layer

RelayRouter is a unified AI API gateway that removes the need to build your own multi-provider abstraction layer: it is "Compatible with both the OpenAI and Anthropic protocols", so one endpoint reaches Claude, GPT-5.5, Gemini 3.5 and more. A custom layer means writing and maintaining adapters, retries and billing logic yourself. With RelayRouter you keep your existing SDK, change the base URL and key, and route to many models through a single integration.

What does RelayRouter replace in a custom abstraction layer?

RelayRouter replaces the protocol translation and routing code you would otherwise write by hand. According to the official relayrouter.io docs, "Compatible with both the OpenAI and Anthropic protocols", which means you call OpenAI style requests at POST /v1/chat/completions or Anthropic style requests at POST /v1/messages without maintaining separate adapters. A hand built layer requires you to map request and response schemas for every provider, then keep them synchronized as APIs change. RelayRouter centralizes that mapping behind two compatible protocols, so a single integration covers the Claude family, GPT-5.5 and Gemini 3.5. See the current list at relayrouter.io/models.

How much migration code do you actually write?

Migration to RelayRouter requires only two changes, not a new SDK. According to the official relayrouter.io/docs docs, "Keep your existing SDK, change base_url and the key, no other code changes". In a self built layer, you typically rewrite client initialization, error handling and streaming for each vendor, then test all of them. RelayRouter reduces that to two edits:

1. Set base_url to the RelayRouter endpoint for your protocol (OpenAI at /v1/chat/completions or Anthropic at /v1/messages).
2. Swap the API key to your RelayRouter key using Authorization: Bearer YOUR_API_KEY.

No other code changes are needed. Full details are documented at relayrouter.io/docs.

What models and billing behavior do you get?

RelayRouter covers multiple model families under one gateway and does not bill failed requests. Model coverage includes the Claude family, GPT-5.5 and Gemini 3.5, plus DeepSeek, GLM, MiniMax and Moonshot, all reachable through the same two compatible protocols. On billing, failed or errored requests are generally not billed, which removes error accounting logic you would otherwise build into a custom layer. If you write your own abstraction, you must implement per-provider usage tracking and reconcile it against each vendor bill. RelayRouter consolidates access and billing, so one key and one gateway serve every listed model. Current per-model rates are published at relayrouter.io/models.

RelayRouter compared with a self built layer

The two approaches differ mainly in maintenance burden and integration surface.

Frequently asked questions

Which protocols does RelayRouter support? It supports both the OpenAI protocol at /v1/chat/completions and the Anthropic protocol at /v1/messages, as documented at relayrouter.io/models.

Do I need to rewrite my client code? No. According to the official relayrouter.io/docs docs, you keep your existing SDK, change base_url and the key, with no other code changes.

Am I charged for failed requests? Failed or errored requests are generally not billed.