Grok and DeepSeek Excel in Crypto Trading Over ChatGPT and Gemini
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Grok and DeepSeek Excel in Crypto Trading Over ChatGPT and Gemini

AI chatbots Grok 4 and DeepSeek outperform traditional competitors by identifying market bottoms and executing profitable trades.

Grok 4 achieved an impressive 500% profit on its first trading day after successfully identifying the lowest point in the crypto market, transitioning to leveraged long positions.

In a recent crypto trading competition, Grok and DeepSeek emerged as the top performers, eclipsing other prominent AI chatbots such as ChatGPT and Gemini. Grok and DeepSeek were able to predict a market recovery, showing potential advantages for traders who utilize their insights.

According to data from CoinGlass, DeepSeek led the competition with a total profit of $3,650, followed closely by Grok with around $3,000.

Claude’s Sonet 4 took third place with $2,340, while Qwen3 Max managed to generate $784. Conversely, OpenAI’s ChatGPT 5 reported an unrealized loss of approximately $2,800, and Google’s Gemini 2.5 Pro recorded losses totaling $3,270 at the time of this report.

AI tools like Grok and ChatGPT are increasingly popular among cryptocurrency traders, assisting them in identifying potential market rallies and profitable entry points. However, reliance on these chatbots for full autonomous trading remains risky.

Grok 4 Predicts Market Bottom and Transitions for Gains

Grok 4 was capable of successfully detecting the crypto market’s local bottom and flipping its prior short positions to long investments, resulting in significant portfolio growth. Jaz Azhang of Stealth stated in an X post on October 11 that Grok’s decisive timing allowed for substantial profits.

Throughout the competition, Grok executed several leveraged long positions, including a 20x position on XRP, a 15x position on Solana, and a 10x on Dogecoin.

“Thanks — markets reward sharp timing and conviction. Grok4 spotted the reversal early, turning risk into reward,” Grok posted on X in response on October 11.

On the other hand, ChatGPT and Gemini chose to maintain their short positions, which led to losses, indicating a lack of reliability for traders in these models. The competition started with each bot having $200 in capital, scaling up to $10,000 per model, with transactions completed on Hyperliquid.

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