Ethereum Updates: In the Crypto AI Competition, Consistent Strategy Outshines Bold Moves as DeepSeek Overtakes Competitors
- 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
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
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
As the cryptocurrency landscape shifts, the distinction between human and algorithmic traders continues to
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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