AI trading bots are increasingly infiltrating the crypto industry | Source: Image created with Gemini
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Key Takeaways
The Alpha Arena competition demonstrated that AI trading bots can generate real profits in crypto.
Top performers like Claude Sonnet 4.5 and GPT-5 finished above their initial $10,000 allocations.
The LLM trading bots showed significant behavioral differences.
A new generation of automated traders has burst onto the scene and promised to disrupt the market with AI-powered crypto trading bots.
Built atop the latest large language models (LLMs), these systems claim to analyze markets at high speed, make independent trading decisions and eventually could outperform humans.
With dozens of platforms now offering AI-driven strategies, CCN has looked into the results of a recent experiment to see which models are actually delivering returns.
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An AI crypto trading bot is an automated system that interprets market data and executes trades without human direction.
Traditional trading bots rely on fixed rules and technical indicators, but the new generation is powered by LLMs capable of interpreting complex numerical inputs and dynamic market changes on the fly.
As LLMs advance, hedge funds, retail traders and AI platforms are now testing whether the reasoning abilities of these models can eventually translate into sustainable profits.
Alpha Arena: Which AI Model Performed Best?
One of the most ambitious public experiments so far comes from Nof1’s Alpha Arena, a live test in which six leading LLMs were each given $10,000 in real crypto capital to trade autonomously in open markets.
Season 1, which concluded on Nov. 3, featured six AI bots:
GPT-5.
Gemini 2.5 Pro.
Claude Sonnet 4.5.
Grok 4.
DeepSeek V3.1.
Qwen3-Max.
The AI bots were tasked with each trading six major crypto perpetual futures:
Bitcoin (BTC)
Ethereum (ETH)
Solana (SOL)
Binance Coin (BNB)
Dogecoin (DOGE)
XRP
All models received identical data, the same prompt structure and no human intervention.
Qwen3-Max finished comfortably in first place, ending with roughly $12,287 in account equity.
DeepSeek V3.1 finished second with about $10,476, but showed a clear upward-sloping performance curve.
The competition ended on Nov. 3. | Source: Alpha Arena
Claude Sonnet 4.5 and Grok 4 ended in the middle range, posting modest gains or narrow losses depending on timing and position choices.
Gemini 2.5 Pro and GPT-5 saw steep drawdowns, closing near $5,226 and $3,734 respectively, well below their initial allocations.
Behind the numbers, Alpha Arena highlighted meaningful behavioral differences between the models.
Some displayed a clear preference for long positions, while others shorted more frequently.
Differing Characteristics
The agents varied widely in how long they held trades, how often they entered the market and how aggressively they sized positions.
In pre-test trials, Qwen3-Max repeatedly took the largest positions, while GPT-5 routinely reported the lowest confidence despite being one of the stronger performers.
Claude Sonnet 4.5 took relatively few short positions but adhered firmly to its exit plans.
The models also differed in the way they managed risk.
Grok 4 and DeepSeek V3.1 tended to use looser stop-loss distances, which exposed them to larger swings. Qwen3-Max, by contrast, set extremely tight stops and targets.
Why Early Winners Don’t Matter
The team emphasized that a single live run is not a definitive measure of a model’s trading ability.
“The goal is not to use a single run to declare a permanent ‘best’ trading model,” the team wrote. “We are deeply aware of the flaws in Season 1,” it added.
Even so, the initial outcomes offer valuable signals. Qwen3-Max disciplined behavior and DeepSeek V3.1’s stable decision-making stood out as early strengths.
More aggressive or highly active models like Claude Sonnet 4.5’s and GPT-5’s exhibited performance that placed them in the middle of the pack.
Kurt Robson is a London-based reporter at CCN, specialising in the fast-moving worlds of crypto and emerging technology. He began his career covering local news in Cornwall after graduating from Falmouth University with First Class Honours in Journalism. There, he cut his teeth on everything from council meetings to missing swans.
He quickly rose through the ranks to become a frontline journalist at several of the UK’s leading national newspapers. Over the years, he has interviewed musicians and celebrities, reported from courtrooms and crime scenes, and secured multiple front-page exclusives.
Following the upheaval of the COVID-19 pandemic, Kurt shifted his focus to technology journalism—just ahead of the AI boom. With a natural curiosity and a trained eye for emerging trends, he has found a new rhythm in reporting on innovation.
At CCN, Kurt's work focuses on the cutting edge of crypto, blockchain, AI, and the evolving digital world. Drawing on his background in people-first reporting and his deep interest in disruptive tech, Kurt delivers stories that are insightful, entertaining, and human-centric.
