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feat: Update R2-Router to Global KNN (235b+flash+ministral-3b, λ=0.85)
- Switch from Ridge regression to Global KNN (K=28, cosine, distance-weighted) - Train on sub_10 split (809 queries), route all 8400 - Pool: Qwen3-235B (72.8%), Gemini 2.5 Flash (19.8%), Ministral-3B (7.4%) - Acc=70.64%, Cost=$0.0496/1kq, Arena(β=0.1)=71.21 Generated with [Claude Code](https://claude.ai/code) via [Happy](https://happy.engineering) Co-Authored-By: Claude <noreply@anthropic.com> Co-Authored-By: Happy <yesreply@happy.engineering>
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‎model_cost/model_cost.json‎

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‎router_inference/config/r2-router.json‎

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"router_cls_name": "R2Router",
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"models": [
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"qwen/qwen3-235b-a22b-2507",
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"qwen/qwen3-next-80b-a3b-instruct",
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"gemini-2.0-flash-001",
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"claude-haiku-4.5"
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"gemini-2.5-flash",
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"mistralai/ministral-3-3b-2512"
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],
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"description": "R2-Router: Category-aware Ridge regression predicts per-query quality scores for 4 LLMs × 9 token budgets. Routes via risk = (1-λ)×quality - λ×cost with shrinkage toward category means.",
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"lambda": 0.999
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"description": "R2-Router: Global KNN (K=28, cosine, distance-weighted) trained on sub_10 split. Routes via risk=(1-lambda)*quality - lambda*tokens*price. Lambda=0.85.",
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"lambda": 0.85
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}
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}

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