Athene-V2 — это мощная языковая модель на 72 миллиарда параметров, созданная на базе Qwen 2.5. Благодаря продвинутому пайплайну RLHF, этот ИИ успешно конкурирует с GPT-4o в сложных рассуждениях и генерации текста.
We’re thrilled to announce Athene-V2, our latest 72B model suite. Fine-tuned from Qwen 2.5 72B, Athene-V2 competes with GPT-4o across key capabilities, powered by a meticulously designed data and RLHF pipeline. As the industry recognizes the slow-down of scaling law—where increasing model size alone no longer delivers universal capability improvements—there’s a growing need for specialized customization to enhance specific capabilities. Our post-training process illustrates this shift, demonstrating how our data and tuning solutions allow us to finely optimize for distinct skills and use cases. Here’s a look at the unique specializations that position Athene-V2 models along the Pareto frontier of LLM post-training: Athene-V2-Chat-72B: A state-of-the-art chat model, matching GPT-4o across multiple benchmarks. It outperforms GPT-4o in chat helpfulness (Arena-Hard), excels in code completion (ranking #2 on bigcode-bench-hard), mathematics (MATH), and handles long log extraction with higher precision (our internal benchmark). Athene-V2-Agent-72B: Striking a balance between chat and agent capabilities, this model offers concise, directive chat responses, surpassing GPT-4o in our latest Nexus-V2 function calling benchmarks that focus on hard enterprise-level function calling use cases.