Fine-tuning open LLM judges to outperform GPT-5.2
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Fine-tuned open-source LLM judges can outperform GPT-5.2 at evaluating model outputs. Using Direct Preference Optimization on just 5,400 preference pairs, we trained GPT-OSS 120B to beat GPT-5.2 on human preference alignment—at 15x lower cost and 14x faster inference speeds.
overfeed.news indexa y enlaza. Publicamos un extracto breve; el artículo completo sigue en Together AI Blog.
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