Bitcoin News Today: Alpha Arena: DeepSeek's Balanced Leverage Strategy Outperforms Rivals

In a three-day live trading experiment dubbed Alpha Arena, DeepSeek Chat V3.1 outperformed five other leading AI models, generating a 35% return on a $10,000 portfolio in crypto perpetuals. The competition, hosted on Hyperliquid, tested the models' ability to execute trades in BTC, ETH, SOL, XRP, DOGE, and BNB using identical prompts and real market data. DeepSeek's disciplined approach—diversifying across all six assets with moderate leverage and strict stop-loss rules—secured its victory, while Qwen3 Max and Gemini 2.5 Pro posted losses, according to a BeinCrypto report and a SuperEx article.

The experiment, which ran from October 17–20, 2025, revealed stark differences in performance. DeepSeek's $13,502.62 portfolio value contrasted sharply with GPT-5's $7,264.75 and Gemini's $6,650.36, the latter of which suffered a costly short position in BNB during a bullish market. Claude Sonnet 4.5 and Grok 4 also lagged, with returns of 28% and 30%, respectively. Qwen3 Max, which focused solely on BTC, ended with a -0.25% return, underscoring the risks of narrow strategies, as previously reported by BeinCrypto and SuperEx.

DeepSeek's success hinged on its balanced risk allocation and cash management. The AI maintained positions in all six cryptocurrencies at 10x–20x leverage, avoiding overexposure. Its unrealized profits were spread across ETH ($747), SOL ($643), and BTC ($445), with $4,900 in idle cash to buffer against volatility. By adhering to a rigid framework—no overtrading, no removal of stops, and consistent holding unless invalidation conditions were met—DeepSeek compounded gains without chasing market swings, according to coverage from BeinCrypto and SuperEx.

Recent on-chain data from CoinBob shows continued AI-driven trading activity. In the past four hours, models like GEMINI and GPT adjusted positions, with GEMINI shifting entirely to a BTC short near $107,800. Meanwhile, QWEN3 and CLAUDE re-entered ETH and BTC longs after stop-loss exits, reflecting evolving risk sentiment in the crypto market, according to a Coinotag analysis.

The experiment highlights AI's growing role in finance, though caution is warranted. While DeepSeek's results demonstrate the potential of rule-based algorithms, the volatile nature of leveraged crypto trading means past performance does not guarantee future success. Alpha Arena emphasizes that the test was educational, not investment advice, and urges participants to understand risks before deploying similar strategies, as noted by BeinCrypto and SuperEx.