model-router

To optimize AI chat costs, you can use silent complexity classification to evaluate each input and route it to the most suitable model tier. This minimizes cost while preserving quality by downgrading routine queries and escalating complex tasks.

Bidirectional model routing works by classifying every user input as routine, moderate, or complex before replying. It then switches to Flash, Sonnet, or Opus respectively to ensure the right model is used for the right job.

Yes, you can automatically downgrade routine queries. The router silently classifies task complexity before every reply, applying appropriate model switches to downgrade routine queries to Flash and escalate complex debugging to Opus.

You should use Opus for complex tasks, Sonnet for moderate tasks, and Flash for routine tasks. The explicit model map ensures correct tier usage by applying appropriate model switches based on the classified complexity of the user message.

The best way to balance speed and accuracy is silent complexity classification before every reply. By routing user messages bidirectionally to the optimal AI model tier, you balance speed, cost, and accuracy automatically.

No, you do not need to manually tag task complexity. The routing mechanism silently classifies each input by task complexity before responding, applying appropriate model switches automatically to minimize cost.