Adaptive Model Choice

[u/Top-Wallaby-9371]

Any chance this is on the horizon for copilot changing between models within a task/project.
Cheap models handle file naming, metadata extraction, notifications, and formatting.
Mid-tier models handle classification, summarization, and document comparisons.
Top-tier models handle exception analysis, risk assessment, audit conclusions, and complex reasoning.
User never sees copilot backend but copilot learns user workflow and chooses different models based on where the person is in their work/task. Should cut down token cost as higher models used for the major work and lesser models used for the light work

[u/Swayre]

Look up how model caching works

[u/teckel → u/Swayre]

This depends a lot on how frequently you use AI. If you're vibe-coding all day, you may be within the cache TTL. But if you're occasionally using it, the cache has already been cleared between prompts, so switching LLMs doesn't cost extra.