Core Insights - The article discusses a unique competition where AI models are tested in real-time trading of cryptocurrencies, aiming to determine which model can generate the highest returns without human intervention [1][2]. Group 1: AI Trading Competition - The competition involves six AI models, each with a capital of $10,000, trading major cryptocurrencies like BTC, ETH, and others [1]. - The event has generated significant interest, surpassing traditional stock trading discussions among participants [1][2]. - The performance of the models is evaluated based on their ability to analyze market data and sentiment, akin to human traders [2]. Group 2: Performance of AI Models - After six days, the leading model, DeepSeek Chat v3.1, initially achieved a return of nearly 40%, but has since stabilized around 10% due to market fluctuations [3]. - The most well-known model, GPT-5, has suffered a loss of 68.9%, indicating a poor performance compared to its peers [4]. - Qwen3 Max has outperformed DeepSeek Chat v3.1 with a return of 13.41% by employing a more aggressive trading strategy [7]. Group 3: Insights on AI Models - DeepSeek's strong performance may be attributed to its quantitative background, although initial tests showed mixed results for various models [7]. - The competition highlights the unpredictability of the market and the need for models to adapt to changing conditions [9]. - Observing the trading strategies and decisions of the models provides valuable insights beyond just the final returns [11]. Group 4: AI in Stock Trading - The article emphasizes the importance of selecting the right AI model for stock trading, as many retail investors are beginning to rely on AI tools for investment decisions [12]. - The development of financial AI models has evolved significantly, with notable examples like BloombergGPT, which faced challenges due to its high costs and closed systems [14]. - Despite the potential of AI in trading, many users report dissatisfaction with the outputs, indicating a need for better data quality and model customization [15][18]. Group 5: Challenges and Limitations of AI - AI models often struggle with understanding complex market dynamics and may produce similar strategies, limiting their effectiveness against larger, more sophisticated quantitative firms [16]. - The article warns that relying solely on AI without a solid understanding of investment principles can lead to significant losses [19][23]. - AI's limitations in predicting "black swan" events and its reliance on historical data highlight the need for human oversight in investment decisions [24][26].

全球首次AI炒币混战 这几天，各大AI社群被一场"投资直播"刷屏。网友们实时追踪六大AI模型的交易表现，讨论的热情程度甚至超过研究自己炒股，这是 一场用真金白银进行的AI投资对决。 10月17日晚在 Alpha Arena 的实验平台上，来自中美的顶级AI模型被同时放进加密市场，每个模型获得 1万美元实盘资金，自由买卖 BTC、ETH、SOL、DOGE、BNB、XRP等主流币。没有人类干预，没有额外提示，谁能让账户价值最高，谁就是真正的"会炒币的 AI"。 这场比赛最有趣的地方在于，它把AI从枯燥的榜单，扔进了最真实、最不可预测的金融市场。 过去，市场用MMLU、ImageNet这些静态的排行榜来衡量AI的能力。但市场不一样，它是一个由无数信息、情绪构成的生命体，在这 里，没有标准答案，只有不断变化的概率。模型不仅仅要去分析数据，还要去分析市场的情绪，跟一个真正的交易员一样。 目前过去了6天，已经历了一些波动。前三天，排名第一的DeepSeek Chat v3.1收益率还一度接近40%，盈利超过4000美元，但10月21日 随着大盘下跌，也回吐了部分收益，DeepSeek Chat v3.1收益率稳定在10% ...