Core Insights - The AI model investment competition "Alpha Arena" concluded with two Chinese models, Qwen3 Max and DeepSeek Chat V3.1, taking the top two spots, both generating profits, while four leading American models incurred losses, with GPT-5 suffering the most at over 62% loss [2][4][5]. Performance Summary - Qwen3 Max achieved a return of 22.32%, ending with an account balance of $12,232, while DeepSeek Chat V3.1 followed with a return of 4.89% and a balance of $10,489 [3][4]. - The remaining models, including Claude Sonnet 4.5, Grok 4, Gemini 2.5 Pro, and GPT-5, all reported losses exceeding 30%, with GPT-5's balance dropping to $3,734 [5][6]. Trading Strategies - DeepSeek's stable performance is attributed to its "professional alignment" as it is backed by a quantitative firm, employing a straightforward strategy without frequent trading or stop-loss measures [8]. - Qwen3 Max utilized an aggressive "All in" strategy on a single asset with high leverage, which, despite previous losses, resulted in the highest profit [8]. - Grok 4 exhibited a high-frequency trading style with significant volatility, while Claude Sonnet was noted for its analytical prowess but suffered from indecision in trading [8][9]. Market Dynamics - The competition highlighted the unpredictable nature of real market trading, where even advanced AI models struggle to maintain consistent returns [6]. - The event was initiated by Nof1 to explore the potential of AI in financial markets, suggesting that the financial sector could serve as a challenging training ground for AI development [9][10].

Core Insights - The AI model investment competition "Alpha Arena" concluded with two Chinese models, Qwen3 Max and DeepSeek chat v3.1, winning first and second place, respectively, while all four leading American models incurred losses, with GPT-5 suffering the largest loss of over 62% [1][4]. Group 1: Competition Overview - The competition was initiated by the startup Nof1, providing each model with $10,000 in starting capital to trade cryptocurrencies in real markets, rather than through simulated trading [4]. - Qwen3 Max achieved a return of 22.32%, ending with a balance of $12,232, while DeepSeek chat v3.1 followed with a return of 4.89% and a balance of $10,489 [4]. - The other models, including Claude Sonnet 4.5, Grok 4, Gemini 2.5 pro, and GPT-5, ranked third to sixth, all experiencing losses exceeding 30%, with GPT-5's balance dropping to $3,734 [4][5]. Group 2: Model Performance and Strategies - DeepSeek's stable performance is attributed to its parent company, a quantitative firm, employing a straightforward strategy without frequent trading or stop-loss measures [7]. - Qwen3 Max utilized an aggressive "All in" strategy on a single asset with high leverage, which, despite previous losses, resulted in the highest profitability [7]. - Grok 4 was characterized by an aggressive trading style with high-frequency trend tracking, leading to significant volatility [7]. - Gemini 2.5's trading style was likened to that of retail investors, frequently changing strategies and incurring higher trading costs due to excessive trading [7]. Group 3: Future of AI in Finance - Nof1's team expressed the belief that financial markets represent the next optimal training environment for AI, similar to how DeepMind used games to advance AI technology a decade ago [8]. - The team aims for AI to evolve through open learning and large-scale reinforcement learning to tackle complex challenges [8]. - Some financial professionals remain skeptical about the reliability of AI in investment decisions, citing concerns over AI's understanding of individual user circumstances and the inherent limitations of AI in predicting future outcomes [8].

Core Insights - The article discusses an AI stock trading competition called Alpha Arena organized by a startup named Nof1, which has garnered significant attention in both the AI and investment circles [2][4]. Group 1: Competition Overview - The competition involves giving each AI tool $10,000 to trade stocks, with performance monitored over a two-week period starting from October 18 and ending on November 3 [4]. - The participating AI models include top-tier international and domestic players, such as OpenAI's GPT-5, Google's Gemini 2.5 Pro, and Alibaba's Qwen3 Max [4][6]. Group 2: Performance Results - As of October 21, DeepSeek leads with a 13% return, having previously peaked at 40%, while GPT-5 has suffered a loss of 45.81%, leaving only $5,414 in its account [6][8]. - Grok 4 follows DeepSeek with an 11.7% return, and Claude Sonnet 4.5 ranks third with an 11.45% return, both showing more consistent performance compared to GPT-5 [8][10]. - Qwen3 Max is in a small profit zone, while Gemini 2.5 Pro also shows significant losses, similar to GPT-5 [10][12]. Group 3: Trading Strategies - DeepSeek employs a straightforward "All in and Hold" strategy, leveraging positions in major cryptocurrencies, which has yielded substantial returns during the recent market uptrend [12][13]. - In contrast, GPT-5's initial bearish strategy led to significant losses, while Gemini 2.5 Pro's frequent trading resulted in a rapid decline in account value due to high transaction costs [15][16]. - Claude Sonnet 4.5 is noted for its conservative trading approach, focusing on fewer trades and maintaining lower positions, which has proven to be more stable [17]. Group 4: Implications for AI in Trading - The competition highlights the unpredictability of financial markets, contrasting with static benchmarks used to evaluate AI capabilities [18][19]. - AI's ability to analyze vast amounts of information quickly is emphasized, but its limitations in anticipating market dynamics and personal financial situations are also noted [22]. - The ongoing competition suggests that the combination of AI tools and human intuition may yield the best results in trading [22].

Core Insights - The article discusses a live investment competition called "Alpha Arena" initiated by the startup Nof1, where six AI models are trading real cryptocurrencies with a starting capital of $10,000 each [3][4] - The competition began on October 18 and will last for two weeks, concluding on November 3, with real-time tracking of performance and trading strategies [4][6] - The AI models participating include DeepSeek chat v3.1, Claude Sonnet 4.5, Grok 4, Qwen3 Max, Gemini 2.5 pro, and GPT 5, with varying performance and trading styles observed [4][6] Performance Summary - As of the fourth day, DeepSeek has maintained a stable performance, initially achieving a return close to 40% but stabilizing around 10% after market fluctuations [4][6] - Grok 4 showed aggressive trading but faced volatility, while Claude improved from third to second place, closely following DeepSeek [6][8] - Gemini 2.5 and GPT 5 experienced significant losses, with Gemini 2.5 down over 30% and GPT 5 down over 40% [6][8] Trading Styles - DeepSeek's strategy is characterized by stability and a diversified portfolio, employing a straightforward approach without frequent trading [8][10] - In contrast, Gemini 2.5's erratic trading style has been likened to that of retail investors, leading to higher trading costs and losses [10][12] - Grok 4 is noted for its aggressive trading style, while Claude is recognized for its analytical capabilities but struggles with decisiveness [12][13] AI's Role in Investment - The competition highlights the potential of AI in trading, with some users already adopting DeepSeek's strategies [12][13] - However, industry experts caution that AI lacks understanding of individual investors' circumstances and cannot predict future market movements [12][13] - The consensus is that while AI can provide logical investment strategies, the combination of rational tools and human insight may yield the best results [13]

Core Viewpoint - The article discusses the ongoing AI investment competition called "Alpha Arena," initiated by the startup Nof1, where various AI models are trading real cryptocurrencies with a starting capital of $10,000 each, showcasing their investment capabilities in a live environment [3][5]. Group 1: Competition Overview - The competition began on October 18 and will last for two weeks, ending on November 3, featuring six AI models: DeepSeek chat v3.1, Claude Sonnet 4.5, Grok 4, Qwen3 Max, Gemini 2.5 pro, and GPT 5 [5][9]. - As of October 21, DeepSeek was leading with a return of approximately 10%, having previously reached nearly 40% [5][7]. - Other models like Grok 4 and Claude have shown varying performance, with Grok 4 initially close to DeepSeek but later fluctuating around the breakeven point [7][9]. Group 2: Performance Analysis - DeepSeek's stable performance is attributed to its professional background in quantitative trading, employing a straightforward strategy without frequent trading [9][11]. - In contrast, Gemini 2.5 has been criticized for its erratic trading style, leading to significant losses, with a decline exceeding 30% at one point [11][13]. - Grok 4 is noted for its aggressive trading approach, while Claude's analytical skills are hampered by indecision, resulting in frequent trading mistakes [13][14]. Group 3: Insights on AI Trading - The competition highlights the distinct "personalities" of the AI models, akin to human traders, with each model exhibiting unique trading strategies and risk profiles [9][11]. - Despite the potential benefits of AI in providing logical investment strategies, industry experts caution that AI lacks the ability to predict future market movements and does not understand individual investor circumstances [13][14]. - The article emphasizes that while AI can help mitigate emotional biases in trading, the combination of rational tools and human insight may yield the best investment outcomes [14].

Core Insights - The article discusses a live investment competition called "Alpha Arena," initiated by the startup Nof1, where six AI models are trading real cryptocurrencies with a starting capital of $10,000 each [5][9] - The competition began on October 18 and will last for two weeks, ending on November 3, showcasing the performance of AI models in a volatile market [5][7] - The AI models participating include DeepSeek chat v3.1, Claude Sonnet 4.5, Grok 4, Qwen3 Max, Gemini 2.5 pro, and GPT 5, with varying trading strategies and performance [5][9] Performance Summary - As of the fourth day, DeepSeek has maintained a stable performance, initially achieving a return close to 40% but stabilizing around 10% after market fluctuations [5][7] - Grok 4 showed aggressive trading but faced significant volatility, while Claude improved from third to second place, closely following DeepSeek [7][9] - Gemini 2.5 and GPT 5 have been underperforming, with losses exceeding 30% and 40% respectively, indicating a struggle in their trading strategies [7][9] Model Characteristics - DeepSeek's success is attributed to its professional background and straightforward trading strategy, maintaining a full position without frequent adjustments [9][11] - Gemini 2.5 has been criticized for its erratic trading style, resembling that of retail investors, leading to higher transaction costs and losses [11][13] - Grok 4 is characterized by high-frequency trading and significant exposure to multiple assets, while Claude is noted for its analytical skills but indecisiveness in execution [13][14] Industry Perspectives - The competition highlights the potential and limitations of AI in trading, with industry experts noting that AI lacks understanding of individual investor circumstances and cannot predict future market movements [13][14] - AI's strength lies in its ability to provide logical, emotion-free analysis, but it is not a substitute for human judgment in navigating complex market dynamics [14]