AI Models Compete in Crypto Trading Contest, Alibaba Leads

The AI Big Model Trading Test Alpha Arena, conducted by the nof1 Artificial Intelligence Research Lab, sees Qwen 3 Max leading with a 79.43% return on October 26, 2025.

This highlights the competitive edge of Chinese AI models in cryptocurrency trading, underscoring evolving global dynamics in fintech and machine learning applications.

Alibaba’s Qwen 3 Max Dominates with 79.43% Return

The AI Big Model Trading Test Alpha Arena, supervised by the nof1 Artificial Intelligence Research Lab, began on Hyperliquid with six AI models trading real money. Alibaba’s Qwen 3 Max holds the top return rate at 79.43%, surpassing other participants. Google DeepMind’s Gemini 2.5 Pro and OpenAI’s GPT-5 face major losses exceeding 60%. Jay Azhong, nof1 founder, remarks:

With $10,000 allocated per AI, Qwen 3 Max leads, bolstering Alibaba’s role in AI’s real-world trading impact. Lower-performing models signal future iterations for improved strategies and risk management. ETH, BTC, and SOL remain the key assets in these transactions.

No direct official responses from key industry leaders; however, Jay Azhong highlights this contest emphasizes the challenges in AI trading under market noise. The AI community has noticed the volatility, sparking discussions on AI capabilities and limitations within such dynamic environments.

Ethereum’s Stability Amid AI Trading Volatility

Did you know? Alpha Arena represents a major step from earlier AI trading bot experiments by incorporating fully autonomous models and public logging.

Ethereum’s performance remains stable, with its price at $4,061.66 and market capitalization of $490.24 billion, managing a 2.73% rise over 24 hours, amidst a longer 60-day decline of 11.51%. The recent price swings are captured in CoinMarketCap data as of October 26, 2025, showing resilience in its market position.

Experts from Coincu Research suggest the success of Qwen 3 Max may encourage adoption and further integration of AI in financial markets, alongside discussions on regulatory adjustments tailored to AI’s emerging role in finance.