Alibaba’s Qwen large language model has taken first place in the “Alpha Arena” real-time AI investment competition, achieving a 22.32% return over 17 days.
The contest, launched on October 18 by research firm Nof1, featured six leading global AI models — Qwen3-Max, DeepSeek v3.1, GPT-5, Gemini 2.5 Pro, Claude Sonnet 4.5, and Grok 4 — each given $10,000 in initial capital to autonomously trade in live markets with no human intervention.
Alibaba’s Qwen and China’s DeepSeek were the only two models to end the competition with profits, while all four U.S.-based models posted losses. OpenAI’s GPT-5 performed the worst, recording a loss of more than 62%, according to the final results.
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Insights
What is the concept of AI investment models?
How did Alibaba's Qwen model originate and what technology underpins it?
What were the objectives of the 'Alpha Arena' competition?
What were the overall results of the AI models in the competition?
How does the performance of Qwen compare to other AI trading models?
What trends are currently shaping the AI trading market?
What feedback have users provided regarding AI trading models like Qwen?
What recent developments have occurred in AI trading technologies?
What are the implications of Alibaba's Qwen winning the competition for the future of AI trading?
What challenges do AI trading models face in achieving consistent profitability?
What controversies exist surrounding AI trading and its effectiveness?
How does the performance of U.S.-based models compare to those from China in this context?
What are the potential long-term impacts of successful AI trading models on financial markets?
How might geopolitical factors influence the development of AI trading technologies?
Are there historical examples of AI models competing in trading competitions?
What differentiates Alibaba's Qwen from models like GPT-5 in terms of trading performance?
