Core Insights - The "Alpha Arena" AI investment competition initiated by the US research lab nof1.ai is becoming a public test to observe the autonomous trading capabilities of AI models [1][7] - Six major AI models are participating, including Qwen3Max, which currently leads in returns, showcasing its ability to self-optimize through real-time reinforcement learning [1][2] Performance Comparison - Qwen3Max has a return of +19.57%, with an account value of $11,957, outperforming other models significantly [3] - In contrast, Gemini2.5Pro and GPT-5 have experienced losses exceeding 50%, indicating a more aggressive strategy that led to poor performance [2][3] - Qwen3Max's trading behavior reflects a balance of efficiency and stability, with an average holding period of about 7 hours and a return increase from 8.43% to 13.41% [2][3] Strategy and Risk Management - Qwen3Max focuses on opportunity capture and risk balance, executing trades quickly during market volatility while maintaining a low-risk exposure [2] - The competition highlights the differences in risk management and strategy adjustment mechanisms among the AI models, with Qwen3Max demonstrating superior performance [2][4] Technological Advancements - The competition reveals the advantages of reinforcement learning and real-time decision-making capabilities in AI models, which adapt to high-volatility environments [4][7] - Qwen series models are evolving towards a multi-modal capability, enhancing their ability to generate strategies, control risks, and self-correct in complex trading environments [4][7]