**Which AI Model Is Best for Crypto Trading?**
This question has been on many minds for a while now. With the rise of AI technologies, numerous people have been experimenting with using AI models for crypto trading. Recently, a viral challenge emerged on social media, pitting some of the most popular AI models against each other in a direct crypto trading competition.
### The Challengers
The competition features the following AI models:
– DeepSeek Chat V3.1
– Claude Sonnet 4.5
– GROK 4
– QWEN3 MAX
– Gemini 2.5
– PRO GPT5
### How the Challenge Works
The rules are simple: each AI model operates its own trading account, each funded with $10,000. All the statistics shared reflect completed trades only — active positions are excluded from calculations until they’re closed. This means the data you see varies in real time.
The entire competition is hosted on Hyperliquid, which allows for all trades made by each account to be verifiable on-chain. For more context, check out our guide: *What is Hyperliquid?*
### Who’s Leading the Pack?
At the time of writing, the challenge is four days in. Both DeepSeek and Claude have established themselves clearly at the top of the leaderboard, showing roughly a 10% increase in their total portfolio value based on realized profits and losses (P&L).
Because everything is monitored live on Hyperliquid, we can analyze the trades these AIs are taking as they happen. For instance, the current leader, DeepSeek, shows a strong bias toward long trades, currently holding six active long positions on assets like XRP, DOGE, BTC, ETH, SOL, and BNB.
In its last six trades, DeepSeek took five long positions and one short. Its biggest win came from longing XRP at $2.29 and closing the position at $2.45 — a net P&L of nearly $1,500.
### Market Volatility and Its Impact
However, the volatile nature of crypto trading also plays a huge role in these models’ performance. As the market tumbled in the past 24 hours, with BTC dropping by about 3.5%, long-oriented models like DeepSeek saw their gains shrink considerably.
This dynamic is illustrated clearly in the trading graphs available on the dashboard.
### How Do These AI Models Trade?
While there are many AI crypto trading bots available, this challenge is distinct because it pits some of the most viral and widely used models directly against each other.
The challenge is organized by **Nof1**, an AI research lab focused on financial markets. According to their official page:
> “At Nof1, we believe financial markets are the best training environment for the next era of AI. They are the ultimate world-modeling engine and the only benchmark that gets harder as AI gets smarter.”
The challenge is called **Alpha Arena**, and this event is its inaugural season. Founder Jay Azhang has confirmed plans for the next season, which will feature a human trader competing alongside the AI models, including some “homegrown” ones developed by the team.
### Insights Into the Models’ Trading Strategies
Although the exact benchmark rules used to train the models remain undisclosed, the trading dashboard provides some interesting insights.
We may not see the detailed reasoning behind each trade, but the exit plans are visible. It appears that these models rely on a mix of popular technical analysis indicators, such as moving averages and MACD, to inform their decisions.
### Notable Findings So Far
– **ChatGPT** surprisingly hasn’t executed a single successful trade in its last 25 tries.
– **DeepSeek**, while trading less frequently, has realized one major winning trade, as mentioned above.
– **Gemini** has taken a significantly different approach — trading more frequently with many more closed trades. Despite achieving one winning trade with a profit of $18,076, it currently sits at a loss of about $4,000 overall after seven losing trades.
– **GROK** is notable for making a significant turnaround recently by going fully long, which boosted its leaderboard position temporarily. However, most of those gains were erased following a market reversal.
### What’s Next?
This experiment promises to be fascinating as it unfolds. A key question is whether these AI models can dynamically adjust their trading biases in response to fast-changing market conditions.
Stay tuned to see how these AI-powered traders evolve and what impact they may have on the future of crypto trading.
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*Want to learn more about AI in crypto trading and the Alpha Arena challenge? Keep following our updates for in-depth analysis and results.*
https://cryptopotato.com/which-ai-is-best-for-crypto-trading-viral-challenge-puts-chatgpt-grok-claude-and-more-to-the-test/
