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Reward Modeling on IFBench

69.3AccuracyGemini-2.5-Flash
46.62852.51458.464.286Feb 2, 2026

Evaluation results

MethodLinks
Gemini-2.5-Flash2026.0269.3
Rubric-RM-voting@5voting=52026.0267.1
Rubric-ARM-voting@5voting=52026.0267.1
API (Rubric+Judge)Rubric Model=GPT-4.1-Mini, Judge Model=Gemini-2.5-Flash Lite2026.0266.2
Rubric-ARM2026.0265.9
Rubric-RM2026.0265.4
RM-R1-14B (Qwen-2.5-Inst)Backbone=Qwen-2.5-Inst, Size=14B2026.0260.8
RRM-32BSize=32B2026.0260.8
API (direct Judge)Judge Model=Gemini-2.5-Flash Lite2026.0260.4
RM-R1-32B (Qwen-2.5-Inst)Backbone=Qwen-2.5-Inst, Size=32B2026.0260.4
RM-R1-14B (DeepSeek-Dist)Backbone=DeepSeek-Dist, Size=14B2026.0259
RM-R1-32B (DeepSeek-Dist)Backbone=DeepSeek-Dist, Size=32B2026.0258.6
RM-R1-7B (DeepSeek-Dist)Backbone=DeepSeek-Dist, Size=7B2026.0256.5
Qwen-3-8B (Rubric+Judge)Backbone=Qwen-3-8B2026.0255.6
RM-R1-7B (Qwen-2.5-Inst)Backbone=Qwen-2.5-Inst, Size=7B2026.0255.2
RRM-7BSize=7B2026.0253.2
JudgeLRM-7BSize=7B2026.0247.5