AI LAB / Local AI / Model Routing
Local Inference Routing
Evaluating when a local model should handle a request and when the system should fall back.
Local AIModel RoutingLatency
- EXPERIMENT
- EXP-018
- STATUS
- complete
- DATE
- Aug 6, 2026
- TAGS
- Local AI · Model Routing · Latency
EXPERIMENT / HYPOTHESIS
A lightweight complexity classifier can route at least half of requests locally without meaningful quality loss.
- 01Label 600 tasks by minimum capable model
- 02Train a small routing classifier
- 03Replay requests with quality and cost scoring
- Local route
- 58%
- Quality delta
- -1.8%
- Cost saved
- 46%
CONCLUSIONRouting worked well for extraction and classification. Multi-step reasoning needed conservative fallback rules.
Routing features
The classifier used task type, input length, requested schema, and a lightweight uncertainty estimate.
- No sensitive content leaves device
- Fallback remains available
- Decision is logged
Result
A policy layer delivered meaningful savings without requiring application code to know which provider executed the request.
- Good for bounded tasks
- Conservative for agents
- Monitor drift