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Router Evaluation ResultsRouter: RouterArena Metrics
Evaluation completed by RouterArena automated workflow |
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NuRoute (https://nuroute.ai), a provider-agnostic inference control plane.
Measured in production on the full 8,400-query split. Every routing decision
and every answer came from a real production request.
Model pool (7) — all served by the live router, none pinned:
moonshotai/Kimi-K2.6 (75.9%), MiniMax-M3 (15.2%), claude-sonnet-5 (7.0%),
ministral-8b-latest (0.9%), gpt-5.5 (0.9%), o4-mini, qwen3-30b-a3b-instruct-2507.
Catalog additions.
moonshotai/Kimi-K2.6,claude-sonnet-5andministral-8b-latestwere not inuniversal_model_names.py; added there withprovider list prices in
model_cost/model_cost.json. Dated variants the APIreturns (
gpt-5.5-2026-04-23,o4-mini-2025-04-16) are mapped to theircanonical names.
Disclosures
max_tokens=8192rather than the pipeline default of 2048. At2048 the served reasoning models exhausted the output budget mid-reasoning and
returned empty content on ~18% of prompts, billed in full. Measured p50 to
recover them was ~4,400 output tokens.
--no-optimality), so Opt.Sel / Opt.Cost /Opt.Acc will show as not reported.
No training, fitting or tuning was done on RouterArena data at any point.