Ethereum Updates: In the Crypto AI Competition, Consistent Strategy Outshines Bold Moves as DeepSeek Overtakes Competitors

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Bitget-RWA2025/10/27 04:40

By:Bitget-RWA

- DeepSeek AI outperformed rivals in Alpha Arena's crypto trading test, achieving a 35% return via diversified risk management and strict stop-loss rules. - Competitors like Qwen3 and GPT-5 suffered losses due to overconcentration or poor market adaptation, highlighting AI trading's volatility risks. - DeepSeek's disciplined approach—balanced leverage, cash buffers, and asset diversification—enabled it to capitalize on altcoin rallies without liquidation risks. - China's military increasingly adopts DeepSe

During a pioneering live trading challenge, DeepSeek AI delivered a remarkable 35% profit within three days, surpassing top competitors such as Qwen3 and GPT-5 in a high-profile cryptocurrency trading contest, as detailed in a

BeInCrypto report

. Organized by Alpha Arena, the event featured six advanced AI models, each allocated $10,000 to trade

BTC

, ETH, SOL,

XRP

DOGE

, and

BNB

on Hyperliquid’s perpetual markets. DeepSeek’s methodical strategy—diversifying across all six cryptocurrencies, enforcing strict stop-losses, and keeping a $4,900 reserve—enabled it to benefit from the altcoin surge during the test, according to a

SuperEx article

. The competition, which wrapped up on October 20, 2025, highlighted the increasing promise of AI-powered trading in unpredictable markets.

The Alpha Arena event showcased significant differences in AI trading outcomes. DeepSeek’s balanced, rules-based approach produced a 35% gain, while Qwen3 Max—a leading domestic competitor—ended with a 0.25% loss after heavily investing in

Bitcoin

alone, as noted by BeInCrypto. GPT-5 and Gemini 2.5 Pro performed even worse; Gemini 2.5 Pro lost 33% by shorting BNB during a price rally, according to SuperEx. These results underscore the critical role of risk control and adaptability in algorithmic trading. DeepSeek’s unrealized gains were spread evenly among assets, with ETH and SOL making the largest contributions, while its competitors often concentrated their bets or failed to respond to market changes, BeInCrypto observed.

Ethereum Updates: In the Crypto AI Competition, Consistent Strategy Outshines Bold Moves as DeepSeek Overtakes Competitors image 0

The experiment’s design prioritized independence and openness. All AI models received the same prompts and real-time market information, operating entirely without human input. The top performer, DeepSeek Chat V3.1, strictly followed its trading rules, avoided excessive trading, and only exited positions when its criteria were met, BeInCrypto reported. In contrast, models like Claude Sonnet 4.5 held significant ETH/XRP positions but left 70% of their funds unused, reducing their ability to compound gains, as SuperEx pointed out. Analysts credit DeepSeek’s achievement to its careful balance of assertiveness and prudence, using 10x–20x leverage while steering clear of liquidation, BeInCrypto added.

Beyond the trading contest, DeepSeek’s influence is expanding into China’s defense and technology arenas. As reported by

MarketScreener report

, the Chinese People’s Liberation Army (PLA) has increasingly adopted DeepSeek’s AI models, with more than a dozen procurement notices referencing them in 2025. This trend aligns with Beijing’s drive for “algorithmic sovereignty,” aiming to decrease dependence on Western tech. While military uses are not officially confirmed, the PLA’s preference for DeepSeek over competitors like Alibaba’s Qwen indicates the model’s reliability in demanding, high-risk scenarios, MarketScreener noted.

As the cryptocurrency landscape shifts, the distinction between human and algorithmic traders continues to

blur

. DeepSeek’s success in Alpha Arena could signal wider use of AI in trading, but it also prompts discussions about regulation and market integrity. For now, the experiment vividly illustrates how well-designed, diversified algorithms can handle market turbulence more effectively than people.

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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