Bitcoin News Today: China's AI Edge in Crypto Trading Signals Financial Power Shift

China's AI Models Outperform ChatGPT in High-Stakes Crypto Trading Contest

In a landmark demonstration of artificial intelligence's evolving role in finance, Chinese models DeepSeek and Alibaba's Qwen 3 Max outperformed Western counterparts like OpenAI's GPT-5 and Google's Gemini in a live cryptocurrency trading competition. The contest, organized by U.S. research firm nof1 under its Alpha Arena initiative, saw DeepSeek's Chat V3.1 generate a 126% return on a $10,000 initial investment, while Qwen 3 Max secured a 108% profit. By contrast, GPT-5 and Gemini both suffered losses exceeding 50%, underscoring the growing competitiveness of China's AI-driven financial strategies, according to a Bitrue blog post https://www.bitrue.com/blog/deepseek-and-alibabas-qwen-beat-chatgpt-in-crypto-trading.

The Alpha Arena experiment, which ran for 18 days on Hyperliquid, pitted six of the world's top AI models against each other in real-time trading of major cryptocurrencies like Bitcoin (BTC) and Ethereum (ETH). Participants operated under identical conditions: $10,000 in capital, 10–20× leverage, and access to technical indicators such as EMA and RSI. Qwen 3 Max's disciplined approach—focusing on BTC and maintaining a single position at a time—proved resilient during a late-stage market downturn, while DeepSeek's adaptive learning algorithm adjusted dynamically to market sentiment, as described in a BingX article https://bingx.com/en/learn/article/how-to-use-qwen-3-max-for-live-ai-alpha-crypto-trading.

Qwen 3 Max's success hinged on its focus on Ethereum during a mid-October rebound, leveraging 20× leverage to amplify gains. Analysts noted that its Sharpe ratio of 0.328, the highest among participants, reflected a balance between risk and reward. Meanwhile, DeepSeek's blend of macro sentiment analysis and short-term momentum trading mirrored strategies typically employed by human hedge funds, as reported by Bitrue. The contest also highlighted the limitations of Western models: GPT-5's rigid algorithm struggled to adapt to volatile conditions, while Gemini's reliance on pre-set commands hindered its responsiveness, according to a Markets.com article https://www.markets.com/news/openai-ipo-2026-trillion-dollar-valuation-1453-en.

The competition's outcomes have sparked broader debates about AI's role in finance. "This isn't just a trading test—it’s a signal of how far AI has progressed in quantitative finance," said one analyst. The results underscore China's growing influence in AI-powered financial technology, a sector once dominated by U.S. firms. As AI models like Qwen and DeepSeek refine their ability to execute trades in milliseconds and adapt to global macro events, they could reshape crypto investing, Bitrue observed earlier.

The contest also coincided with OpenAI's rumored plans for a 2026 IPO, which could value the company at $1 trillion. Despite its resources, OpenAI's ChatGPT lagged in the trading test, raising questions about the firm's ability to maintain dominance in AI applications beyond chatbots. A spokesperson emphasized OpenAI's focus on artificial general intelligence (AGI), but the Alpha Arena results suggest immediate financial use cases may be outpacing theoretical advancements, a Markets.com analysis later suggested.

Critics argue that the competition's short duration and reliance on technical indicators alone limit its conclusiveness. Nassim Nicholas Taleb's theory of randomness in markets complicates interpretations of AI "success," as luck may have played a role in Qwen's and DeepSeek's gains. However, the contest's organizers plan to expand future rounds with multi-prompting and human trader participation, aiming to test AI's adaptability in more complex scenarios, according to an Odaily report https://www.odaily.news/en/post/5207254.

As AI continues to evolve, the crypto trading arena may become a proving ground for the next generation of financial tools. For now, China's AI models have set a new benchmark, challenging the West to accelerate its own innovations in algorithmic finance.