Results. As shown in Figure 12, Llama 2-Chat models outperform open-source models by a significant
margin on both single turn and multi-turn prompts. Particularly, Llama 2-Chat 7B model outperforms
MPT-7B-chat on 60% of the prompts. Llama 2-Chat 34B has an overall win rate of more than 75% against
equivalently sized Vicuna-33B and Falcon 40B models.

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RLHF-v5(with PPO)RLHF-v5(no PPO)RLHF-v4RLHF-v3            RLHF-v2      RLHF-v1SFT-v2       SFT-v110%20%30%40%50%60%70%80%90%10%20%30%40%50%60%70%80%HelpfulnessJudge: Meta Reward ModelsHarmlessness  RLHF-v5  (with PPO)RLHF-v5  (no PPO)  RLHF-v4RLHF-v3     RLHF-v2RLHF-v1     SFT-v2    SFT-v110%20%30%40%50%60%70%80%90%10%20%30%40%50%60%70%80%HelpfulnessJudge: GPT-4HarmlessnessFigure 12: Human evaluation results for Llama 2-Chat models compared to open- and closed-source models
across ~4,000 helpfulness prompts with three raters per prompt.
Llama2