smart-router

Route LLM requests to cheaper models by classifying task complexity dynamically, sending simple tasks like profanity checks to budget models and complex tasks like marketing strategies to flagship models.

You can manage LLM costs across Anthropic, OpenAI, and Google Gemini by tracking operational expenses in real-time, enabling profitability monitoring and per-organization cost attribution.

Provider failover for LLM infrastructure works by dynamically rerouting requests across configured Anthropic, OpenAI, and Google Gemini providers when a failure occurs, ensuring continuous task completion.

The best way to select the optimal LLM model is using dynamic classification and resolver logic to evaluate task complexity and route requests across budget, mid, and flagship tiers automatically.

LLM cost optimization supports budget, mid-tier, and flagship model routing by evaluating provider capabilities and task requirements to select the most cost-effective model without compromising output quality.

You should not use dynamic LLM model routing when strict output consistency from a single specific flagship model is required, as the resolver automatically shifts requests between budget and mid-tier tiers based on task complexity.