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ChatGPT Last In Crypto Trading Race, Qwen3 Wins With 20x Bitcoin Long - news.adtechsolutions ChatGPT Last In Crypto Trading Race, Qwen3 Wins With 20x Bitcoin Long - news.adtechsolutions

ChatGPT Last In Crypto Trading Race, Qwen3 Wins With 20x Bitcoin Long


Two Chinese artificial intelligence chatbots beat some of the world’s most advanced models, including OpenAI’s ChatGPT, in a standalone cryptocurrency trading competition that ended on Tuesday.

Budget AI models QWEN3 MAX and DeepSeek finished first and second in the business challenge, beating higher-profile and more expensive competitors.

QWEN3 was the only AI chatbot to generate positive returns, making a total profit of $751 at a return rate of 7.5%, while all other AI bots finished the competition in the red. according to to the CoinGlass data aggregator.

AI models, crypto trading competition. Source: CoinGlass

OpenAI’s ChatGPT brought up the rear with a 57% loss, reducing their initial investment of $10,000 to just $4,272 by the end of the competition.

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To win the business competition, QWEN3 was running a 20x leveraged long position on Bitcoin (BTC), as the AI ​​models only opened positions from Wednesday.

QWEN 3 started the leveraged bet when Bitcoin traded at $104,556 and is to be liquidated if BTC falls below $100,630, CoinGlass data shows.

QWEN 3 crypto wallet on Wednesday. Source: CoinGlass

Before the end of the competition, QWEN 3 had mainly held long leveraged positions in Bitcoin, Ether (ETH) and Dogecoin (DOGE).

Related: $19B market crash paves way for Bitcoin’s rise to $200K: Standard Chartered

OpenAI’s ChatGPT is underperforming in crypto trading, despite a massive budget

The surprising results of the competition highlight that even the most well-funded AI models still lack real-time capabilities in crypto trading.

ChatGPT came in last despite OpenAI spending $5.7 billion on research and development initiatives in the first half of 2025 alone, according to to Reuters.

While QWEN3’s budget was not public, building the model could have cost between $10 million and $20 million, according to estimates by machine learning engineer Aakarshit Srivastava.

DeepSeek took second place, despite being developed at a total training cost of $5.3 million, according to to the technical document of the model.

The Alpha Arena competition started with $200 in seed capital for each bot, which was later increased to $10,000 per model, with trades executed on the decentralized exchange Hyperliquid.

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