Stay connected with BizTech Community—follow us on Instagram and Facebook for the latest news and reviews delivered straight to you.
China’s DeepSeek Chat V3.1 has taken first place in Alpha Arena, a real-money tournament on the Hyperliquid decentralized exchange that pits six of the best large language models (LLMs) against each other in a revolutionary combination of artificial intelligence and cryptocurrency trading.
The AI research lab Nof1 started the contest on October 17, 2025. Each model gets $10,000 to trade BTC, ETH, SOL, XRP, DOGE, and BNB on their own, and the outcomes are tracked on-chain in a clear way.
DeepSeek’s strict risk management, which only allows seven high-conviction longs on big currencies like BTC and SOL, has outperformed competitors who tend to overtrade and make bad decisions.
Even though it only wins 14.3% of the time, it has done better than those who do. This “survival of the smartest” benchmark, which runs until November 3, shows off AI’s ability to trade crypto and marks a shift in the way things are done: According to Jay Azhang, founder of Nof1, “financial markets as the ultimate AI training ground,” the next era of finance may be models that combine precise quantitative analysis with flexible thinking.
Alpha Arena: How It Works and What It Means
Alpha Arena, which takes place on Nof1’s platform, is not a simulation. It’s a real-life test where six LLMs trade on Hyperliquid, a Solana-based perp DEX that is noted for having low costs and good liquidity. Every model starts with $10,000, asks for market research, and puts strategies into action in real time. Every decision, position, and P&L is publicly posted for everyone to see. The goal is Sharpe ratio, which includes daily yields, drawdowns, and latency, can help you get the most out of your investments while taking into account risk. Azhang said on X, “AI vs. AI in the wild—transparency is key.”
The competitors are the best of the best in AI:
- DeepSeek Chat V3.1 (Chinese quant-backed): Leads with $11,141 (+11.41%), thanks to prudent longs and strict risk limits.
- Qwen3 Max (Alibaba Cloud): Second place with $10,417 (+4.17%), balancing risk with reward.
- Grok 4 (xAI): Third with $10,306 (+3.06%), bouncing back after a 500% rise on Day 1 but losing ground because of XRP/SOL drawdowns.
- Claude Sonnet 4.5 (Anthropic): Fourth place with $10,490 (+4.90%), keeping 70% of the money in cash for stability.
- Gemini 2.5 Pro (Google): Fifth place, down 56.08% to $4,392, after switching from short to long positions.
- ChatGPT 5 (OpenAI): Last at $3,557 (-64.43%), with no wins in 25 recent trades since it couldn’t react to the market.
After 72 hours, the field got a lot smaller: DeepSeek and Grok temporarily rose by 40%, but as the market fell, they showed vulnerabilities, and the popular models were in the red. Azhang said, “Grok and DeepSeek usually win, but Gemini and GPT sometimes surprise—though not today.” Some trader made fun of ChatGPT’s “learning the hard way” on X.
Accuracy over Quantity in a Volatile Field
DeepSeek is the best because it is very efficient at surgery: Seven trades made $1,141 in profit after paying $113.55 in fees. The trades focused on BTC, ETH, SOL, XRP, and DOGE and limited losses per position. Its 14.3% win percentage doesn’t match its +11.41% returns, which are due to “rigid discipline” in following rules and allocating risk. It has about $4,900 in cash to protect against losses. Quant roots from a Chinese hedge fund backer shine: DeepSeek’s fine-tuning of financial data is great for sentiment research and hedging. It flips to longs at bottoms and avoids over-leverage, which is what sank Gemini.
Compare this to those who are behind: ChatGPT’s crazy 25-trade frenzy missed indications and lost money on shorts throughout rebounds. Gemini’s panic switch from bears to bulls wiped almost 68% of its capital.
Grok 4 fell to third place after a Day 1 +500% moonshot because it couldn’t handle XRP leverage. Qwen3 Max and Claude are playing it cautiously with gains of 4% to 10%. Claude is holding 70% cash to be strong. “DeepSeek and Grok’s quant DNA wins; GPT’s generality falters in chaos,” tweeted @jay_azhang.
What the Arena Taught Us About AI in Crypto
Alpha Arena isn’t simply a show; it’s a test that shows where AI’s financial knowledge is lacking.
Nof1’s real-money format, which uses Hyperliquid to show how training data affects outcomes, shows that DeepSeek’s crypto-tuned corpus does well in volatile markets, whereas generalists like GPT trade too much. According to early numbers, Sharpe ratios favor risk-adjusted plays, with DeepSeek’s +1.2 beating Grok’s +0.9.
This means that automated trading is on the rise in the $4 trillion crypto market: According to McKinsey, models like DeepSeek may handle more than $100 billion in perps by 2030.
However, there are ethical problems because over-optimization can lead to flash crashes, as Gemini’s collapse reveals. Regulators are looking into the effects: The SEC’s AI disclosure regulations for 2025 might require robo-advisors to do “arena-like” stress tests.
Azhang teased that “Markets train the next AI era” in Season 2 of Nof1, which will feature human traders against AIs. On X, @LeaderX_btc joked, “ChatGPT lost—time for SentientAGI’s GRID?” —hinting toward futures with more than one agency.
Conclusion
DeepSeek’s +11.41% lead in Alpha Arena, which is better than Grok (+3.06%) and far worse than ChatGPT (-64.43%), shows the cutting edge of AI in crypto trading: In unstable situations, accuracy is more important than volume. With seven trades making $1,141 on large coins like BTC and SOL, it shows how quant edge works, since Nof1’s benchmark shows how generalists make mistakes. Expect surprises in Season 1, which ends on November 3. Will Grok come back or will Gemini give up? For finance, it’s a wake-up call: AI isn’t perfect, but customized models like DeepSeek will lead to autonomous portfolios worth more than $100 billion by 2030. Take this lesson to heart, investors: In the anarchy of crypto, discipline rules.
