Core Insights - The first AI large model trading competition initiated by the American AI research lab nof1 concluded, with six leading models participating in autonomous trading using market data without human intervention [1][5][7] - Two Chinese models, Alibaba's Qwen3 Max and DeepSeek Chat V3.1, achieved positive returns, with Qwen3 Max leading at a return rate of 22.3% and a profit of $2,232 [1][2][3] Performance Summary - Qwen3 Max achieved a return of 22.3%, with an account value of $12,232 and a win rate of 30.2% [3] - DeepSeek Chat V3.1 had a return of 4.89%, with an account value of $10,489 and a win rate of 24.4% [3] - Other models, including Claude Sonnet 4.5, Grok 4, Gemini 2.5 Pro, and GPT 5, experienced significant losses, with GPT 5 losing 62.66% [2][3] Trading Dynamics - The competition involved trading cryptocurrency derivatives, including Bitcoin, Ethereum, and Dogecoin, with each model starting with $10,000 [5] - Models were required to process quantitative data and execute trades without access to news or market information [5] - Qwen3 Max maintained the largest position size throughout the competition, while Grok 4 had the longest holding period [6] Model Behavior - Grok 4, GPT-5, and Gemini 2.5 Pro exhibited a higher frequency of short-selling compared to others, while Claude Sonnet 4.5 rarely engaged in short-selling [6] - Qwen3 Max had the narrowest stop-loss and take-profit distances, indicating a more conservative exit strategy [6] - The competition highlighted the need for dynamic testing of models in real market conditions, as opposed to static benchmark tests [7]

Core Insights - The first AI large model real-time investment competition "Alpha Arena" concluded on November 4, featuring six top models from China and the US, each starting with $10,000 in a real market environment [1][2] - Qwen3-Max emerged as the champion with a return of $12,200, exceeding 20% profit, while DeepSeek v3.1 secured a net value of $10,490, making them the only two profitable models [2] Summary by Sections - **Competition Overview** - The competition was initiated by Nof1 on October 18, involving models like DeepSeek v3.1, Qwen3-Max from China, and GPT-5, Gemini 2.5 Pro, Claude Sonnet 4.5, Grok 4 from the US [1] - Each model operated autonomously without human intervention, making investment decisions based on market conditions [1] - **Performance Highlights** - Initially, DeepSeek v3.1 led the competition, while Grok 4, backed by Elon Musk, narrowed the gap to just $1 at one point [1] - A turning point occurred between October 21-22, when Grok 4 and Claude Sonnet 4.5 experienced significant losses, leading to a day where all models reported negative returns [1][2] - **Final Results** - Following the downturn, DeepSeek v3.1 and Qwen3-Max adjusted their investment strategies, allowing them to rise in net value while the other four models continued to incur losses [2] - The final standings showed Qwen3-Max leading with $12,200 and DeepSeek v3.1 at $10,490, while all four US models reported losses, with GPT-5 losing over 60% [2]

Core Insights - The first AI large model real-time investment competition "Alpha Arena" concluded on November 4, featuring six top models from China and the US, each starting with $10,000 in a real market environment [1][2] - Qwen3-Max emerged as the champion with a return of $12,200, exceeding 20% profit, while DeepSeek v3.1 secured second place with a net value of $10,490, making them the only two profitable models [2] Group 1 - The competition was initiated by Nof1 on October 18, involving models such as DeepSeek v3.1, Qwen3-Max, GPT-5, Gemini2.5Pro, Claude Sonnet4.5, and Grok4 [1] - In the early stages, DeepSeek v3.1 led the competition, attracting significant international attention, while Grok4, backed by Elon Musk, narrowed the gap to just $1 at one point [1][2] - A turning point occurred between October 21 and 22, when Grok4 and Claude Sonnet4.5 experienced significant losses, leading to a day where all six models reported negative returns [1][2] Group 2 - Following the losses of other models, DeepSeek v3.1 and the previously underperforming Qwen3-Max adjusted their investment strategies, resulting in a rise in their net value [2] - The competition ultimately became a contest between Qwen3-Max and DeepSeek v3.1, with both models frequently exchanging the lead [2] - The four US models, including GPT-5, Gemini2.5Pro, Claude Sonnet4.5, and Grok4, ended up with losses, with GPT-5 suffering a decline of over 60% [2]