Use RouterBase as an OpenAI-compatible API gateway

RouterBase provides an OpenAI-compatible API gateway at https://routerbase.com/v1, enabling developers to switch between multiple AI models with minimal code changes. By simply altering the base URL and API key, users can experiment with different models like Google's Gemini 2.5 Flash, comparing output quality, latency, cost, and error rates before routing production traffic.

Many AI applications begin with one provider and then need more flexibility: fallback models, model experiments, or different models for different product workflows. RouterBase https://routerbase.com gives developers an OpenAI-compatible API shape at https://routerbase.com/v1 , so the first experiment can stay small: change the base URL, set a RouterBase API key, and choose a model id. curl https://routerbase.com/v1/chat/completions \ -H "Authorization: Bearer $ROUTERBASE API KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "google/gemini-2.5-flash", "messages": { "role": "user", "content": "Explain RouterBase in one sentence." } }' js const response = await fetch "https://routerbase.com/v1/chat/completions", { method: "POST", headers: { Authorization: Bearer ${process.env.ROUTERBASE API KEY} , "Content-Type": "application/json" }, body: JSON.stringify { model: process.env.ROUTERBASE MODEL || "google/gemini-2.5-flash", messages: { role: "user", content: "Draft a short product update." } } } ; if response.ok { throw new Error RouterBase request failed: ${response.status} ; } console.log await response.json ; Start with a low-risk workflow, keep the model id configurable, and compare output quality, latency, cost, and error rate before routing more traffic through the new setup. Good first workflows: