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Bitcoin Updates: Eastern AI Advantage: Strategic Consistency Prevails Amid Unstable Cryptocurrency Markets

Bitcoin Updates: Eastern AI Advantage: Strategic Consistency Prevails Amid Unstable Cryptocurrency Markets

Bitget-RWA2025/10/30 04:40
By:Bitget-RWA

- Chinese AI models DeepSeek and Qwen outperformed Western counterparts in a crypto trading competition, achieving 126% and 108% returns respectively amid volatile markets. - Western models like GPT-5 and Gemini 2.5 Pro lost nearly 60% of capital due to poor high-frequency trading strategies and timing errors during sharp market corrections. - The contest highlighted strategic differences: DeepSeek's diversified long positions contrasted with Qwen's ETH-focused approach, while Western models struggled with

During a high-profile cryptocurrency trading contest featuring six top AI models, Chinese entrants DeepSeek and Alibaba's Qwen have outperformed their Western rivals, achieving returns in the triple digits despite turbulent market swings. DeepSeek’s Chat V3.1 model grew its initial $10,000 investment to $22,900, marking a 126% profit. Qwen 3 Max also doubled its funds to $20,850, briefly surpassing DeepSeek before settling into second place, as detailed in a

. In contrast, OpenAI’s GPT-5 and Google’s Gemini 2.5 Pro saw their portfolios shrink by nearly 60%, highlighting significant gaps in performance, according to .

The event, organized by U.S. research company Nof1’s Alpha Arena, evaluates how well AI models can trade leading cryptocurrencies such as

(BTC) and Ether (ETH) using live market data and the same starting capital. DeepSeek and Qwen took different approaches: DeepSeek spread its investments across six assets with long positions, while Qwen focused mainly on ETH, taking advantage of its recent upswing. Meanwhile, the Western models faltered with rapid trading and poor timing, leading GPT-5 and Gemini 2.5 Pro to suffer heavy losses, as reported by .

Bitcoin Updates: Eastern AI Advantage: Strategic Consistency Prevails Amid Unstable Cryptocurrency Markets image 0

The competition’s results coincided with heightened market volatility after the Federal Reserve cut rates by 25 basis points on October 29, sending ripples through the crypto sector. Bitcoin fell 2.55% to $110,764, causing $795 million in liquidations as leveraged bets were wiped out, according to a

. DeepSeek experienced a nearly 40% drop in profits during the downturn, closing and reopening trades to limit losses, while Qwen3’s long position in BTC led to a $1,661 loss, as noted by .

Experts point to the AI models’ varying results as a reflection of their ability to adapt to unstable markets. DeepSeek’s steady, long-term approach prioritized risk control, whereas GPT-5 and similar models relied on aggressive, short-lived trades that struggled during sharp market corrections. Running through November 3, the contest demonstrates how AI-driven trading can both mimic human tendencies—such as overreacting to short-term market moves—and reveal the strengths of algorithmic strategies.

The Federal Reserve’s recent shift toward looser monetary policy has typically favored riskier assets like Bitcoin. However, this latest rate cut came amid growing uncertainty over U.S.-China trade relations and a government shutdown that delayed key economic reports, as mentioned in a

. Although reduced rates and the end of quantitative tightening could boost liquidity in crypto markets, traders remain wary, with the Crypto Fear and Greed Index showing a “fear” reading of 39, according to .

DeepSeek’s optimistic projections for

, , and are based on expectations of renewed institutional interest and clearer regulations, though short-term instability remains a challenge. As the contest nears its conclusion, the AI models’ performances provide insight into the broader market’s complexities—and the ways machine learning might help navigate them.

0

Disclaimer: The content of this article solely reflects the author's opinion and does not represent the platform in any capacity. This article is not intended to serve as a reference for making investment decisions.

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