Token Efficiency is the Real Bottleneck, Not LLM Routing
AdditionalWeb107 · reddit · 2026-08-03
The author argues that the recent influx of LLM routers (Ramp, Cursor, etc.) is misguided. Benchmark-based routing is broken because model performance is highly conditional on the application context (system prompts, tool definitions, history); isolated leaderboard rankings are irrelevant.
The real challenge is token efficiency, requiring a closed-loop evaluation system. Citing Coinbase as an example, the company didn't lower usage caps to control costs but optimized through a combination of:
- Better defaults: Preventing every request from defaulting to the most expensive model.
- Preference-aware routing: Selecting models based on task and developer priorities.
- Cache-aware routing: Preserving agentic session value, boosting cache hit rates from 5% to 60%.
The ultimate goal is not blindly minimizing token price, but maximizing useful intelligence per dollar.
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