How TokenSwitcher Works

A simple integration that gives you powerful control over your LLM infrastructure.

Architecture Overview

TokenSwitcher sits between your application and LLM providers, intelligently routing each request.

Every request goes through a 5-step process optimized for speed and intelligence.

Your app sends a request to TokenSwitcher's API

We classify the task type and requirements

Select the optimal model based on your rules

Forward to the selected provider

Return the result to your application

See how teams use TokenSwitcher to solve real infrastructure challenges.

Route simple queries to cost-effective models while reserving premium models for complex tasks.

Example: A chatbot uses GPT-3.5 for FAQs and routes to GPT-4 only for technical support questions.

Minimize latency by routing to the fastest available model that meets quality requirements.

Example: Real-time applications route to the provider with lowest current latency for immediate responses.

Automatically fail over to backup providers when your primary model is unavailable.

Example: When OpenAI experiences an outage, requests automatically route to Anthropic with no code changes.

Compare model performance by routing a percentage of traffic to different providers.

Example: Route 10% of traffic to a new model to evaluate quality before full rollout.

Integration takes just a few minutes. Replace your existing API endpoint and start routing.