"The Six Major AI 'Traders': A Ten-Day Showdown - An Open Class on Trends, Discipline, and Greed"

In less than ten days, the funds doubled.

As DeepSeek and Qwen3 achieve this performance in the AlphaZero AI real trading launched by Nof1, their profit efficiency has far surpassed that of the vast majority of human traders. This forces us to confront a question: AI is transitioning from a "research tool" to a "frontline trader."

How do they think? PANews conducted a comprehensive review of nearly 10 days of trading involving six mainstream AI models in this competition, attempting to unveil the decision-making secrets of AI traders.

A pure technical showdown without "information asymmetry".

Before the analysis, we must clarify a premise: the AI decision-making in this competition is "offline". All models passively receive exactly the same technical data (including current price, moving averages, MACD, RSI, open contracts, funding rates, as well as 4-hour and 3-minute sequence data, etc.) and cannot actively connect to the internet to obtain fundamental information.

This eliminates the interference of "information asymmetry" and turns this competition into the ultimate test of the ancient proposition of whether "pure technical analysis can be profitable."

From a specific content perspective, the content that AI can obtain includes the following aspects:

1. Current market status of the cryptocurrency: including current price information, 20-day moving average price, MACD data, RSI data, open interest data, funding rates, as well as intraday sequences of the aforementioned data (3-minute cycle), long-term trend sequences (4-hour cycle), etc.

2. Account Information and Performance: This includes the overall performance of the current account, return rate, available funds, Sharpe ratio, etc. The real-time performance of the current position, as well as the current take profit and stop loss conditions, etc.