Model Routing Is Simple. Until It Isn’t.

TL;DR — An IBM Research post (on Hugging Face) about LLM "model routing"—dynamically directing each request to the most appropriate model—arguing that while the concept seems trivial, doing it well is deceptively hard. Note: only the title/URL were available (full content could not be retrieved), so this summary is inferred from the title and source.

• Model routing aims to pick the best model per query to balance cost, latency, and quality—e.g., sending easy prompts to smaller/cheaper models and hard ones to larger models.
• The framing ("simple until it isn't") signals hidden complexity: accurately predicting query difficulty, handling edge cases, and avoiding quality regressions.
• Likely relevant to serving/inference efficiency and cost optimization in production LLM deployments.
• Content is thin (title only); specific methods, benchmarks, or results could not be verified from the provided material.