fix: Use raw AA benchmark accuracy instead of composite #43
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Replace model_evaluator.score_model() composite scoring with direct AA benchmark scores from usecase_quality_scorer. The composite score incorrectly favored smaller models due to latency/budget bonuses. Changes: - Get raw accuracy from score_model_quality() in capacity_planner - GPT-OSS 120B now correctly shows ~62% (was showing lower) - GPT-OSS 20B now correctly shows ~55% (was showing higher) Assisted-by: Claude <noreply@anthropic.com> Signed-off-by: Yuval Luria <yuval750@gmail.com>
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Replace model_evaluator.score_model() composite scoring with direct AA benchmark scores from usecase_quality_scorer. The composite score incorrectly favored smaller models due to latency/budget bonuses.
Changes:
Assisted-by: Claude noreply@anthropic.com