Athene-V2-Chat is a large language model developed by Nexusflow, designed for high-performance conversational interactions and technical reasoning. It is a 72B parameter model fine-tuned from the Qwen2.5-72B-Instruct base. The model was trained using reinforcement learning from human feedback (RLHF) to optimize its capabilities in mathematics, software development, and general instruction following.
The model is part of the Athene-V2 suite, which includes specialized variants such as Athene-V2-Agent. Athene-V2-Chat is specifically tailored for conversational helpfulness and long-form text processing. It demonstrates strong performance in coding and complex query handling, maintaining coherence across multi-turn dialogues within its 32,768-token context window.