Chinese AI Bots Outperform ChatGPT in Crypto Trading Test

5 November 2025 at 08: 39

Reading time: 2 minutes

A recent autonomous cryptocurrency trading competition highlighted the performance of two Chinese AI chatbots, QWEN3 MAX and DeepSeek. These models easily outperformed some of the most advanced, globally recognized models, such as OpenAI's ChatGPT. QWEN3 took first place, while DeepSeek secured second place, even outperforming more expensive and well-promoted competitors.

Of particular note, QWEN3 was the only AI chatbot to generate positive returns, with a total profit of $751 and a 7,5% return. In stark contrast, all other AI models in the competition closed with losses, according to CoinGlass data. OpenAI's ChatGPT took last place, with a significant 57% loss, shrinking its initial $10.000 investment to just $4.272.

At the time of the competition closing, QWEN3 held a 20x manipulated long position Bitcoin (BTC), which was the only open asset. This position was initiated when Bitcoin was trading at $104.556 and is poised to be liquidated if BTC falls below $100.630, as CoinGlass indicates. Throughout the competition, QWEN3 primarily maintained long positions on Bitcoin, Ether (ETH), and Dogecoin (DOGE), indicating an aggressive trading strategy.

OpenAI's ChatGPT's Shortcomings in the Cryptocurrency Market

The competition's outcome highlights that even the best-funded AI models lack the necessary real-time capabilities for successful cryptocurrency trading. Despite a staggering $5,7 billion investment budget in research and development initiatives in the first half of 2025, according to Reuters, ChatGPT proved unable to achieve profitability in this specific market environment.

In contrast to the monumental investments in ChatGPT, experts speculate that the cost of training QWEN3 is between $10 million and $20 million, while DeepSeek reached the podium with a total training cost of $5,3 million. The competition, which began on October 18th with an initial investment of $200 per bot, later increased to $10.000 per model, took place on the decentralized trading platform Hyperliquid.

These results raise important questions about the future of AI in the cryptocurrency market. It's clear that while artificial intelligence holds promise, its implementation and execution in the dynamic world of crypto trading pose significant challenges. Investors and analysts should be aware of the limitations of this technology before deciding to delve deeply into the world of AI-powered trading strategies.

Frequently Asked Questions

What made QWEN3 so successful in the competition?
QWEN3 distinguished itself with a well-thought-out trading strategy that focused primarily on highly leveraged long positions on Bitcoin and other cryptocurrencies, resulting in a positive ROI while other AI models recorded losses.

Why did OpenAI's ChatGPT perform so poorly?
ChatGPT, despite its substantial R&D budget, lacks the real-time trading capabilities crucial for successfully navigating the volatile crypto market. This demonstrates that funding doesn't always translate into better performance in this sector.

What do the results teach us about the future of AI in cryptocurrency trading?
The results suggest that significant development and refinement of AI models is still required to apply them effectively in the cryptocurrency market, and that investors should be cautious about implementing such technologies without a thorough understanding of their limitations.

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