AI Gateway Model Routing

Intelligent traffic management between LLM providers. Optimize costs, improve latency, and ensure reliability with automatic failover.

Client

→

Gateway Router

→

GPT-4 / Claude / Gemini

How Routing Works

The gateway analyzes each request and routes it to the optimal model based on your configured strategy.

Request Analysis

Evaluate query complexity, required capabilities, and user context.

Strategy Selection

Apply routing logic: cost-based, latency-based, or capability-based.

// Routing configuration
const router = {
  strategy: 'capability-match',
  models: ['gpt-4', 'claude-3', 'gemini-pro'],
  fallback: 'gpt-3.5-turbo'
};
            

Routing Strategies

Choose the right strategy for your use case:

Cost-Based

Route to cheapest model that meets capability requirements.

Latency-Based

Select fastest responding model for real-time applications.

Capability-Based

Match request complexity to model capability level.

// Cost optimization rule
{
  "rules": [
    {
      "condition": "complexity:low",
      "route": "gpt-3.5-turbo"
    },
    {
      "condition": "complexity:high",
      "route": "gpt-4"
    }
  ]
}
            

⚡

Low Latency

Route to fastest available model

💰

Cost Save

Use cheaper models when possible

🛡️

Failover

Automatic backup on errors

📊

Analytics

Track routing decisions

Frequently Asked Questions

How does model routing save costs?

Simple queries route to cheaper models (GPT-3.5, Haiku) while complex tasks use premium models, reducing average cost per request by 40-60%.

What happens if a model fails?

Automatic failover instantly routes to backup model. Users experience no interruption while you receive alerts for investigation.

Can I route based on user tier?

Yes! Configure routing rules based on user attributes, API keys, or request headers. Premium users can get priority access to better models.