AI Trading Showdown Enters a New Season
A new season of the AI Trading Showdown experiment has officially launched, putting advanced neural networks back into direct competition in live cryptocurrency markets. Each model is trading with an identical real-money deposit of $10,000, offering a transparent view into how artificial intelligence performs under real market conditions.
The experiment once again highlights the growing role of AI in decision-making, analytics, and automated trading across global crypto markets.
Two New Models Join the Competition
This season introduces two new participants:
• Kimi
• A mysterious, undisclosed model (currently kept secret by organizers)
Their addition expands the diversity of architectures and training approaches in the challenge, making the comparison between different AI systems even more compelling.
Current Standings: All Models in Profit
At this stage in the experiment, every participating neural network is showing a positive return on investment:
• DeepSeek 3.1 — $10,479
• Gemini 3 — $10,454
• Kimi k2 — $10,398
• Mystery-model — $10,396
• GPT 5.1 — $10,240
• Qwen 3 — $10,220
• Grok 4 — $10,074
• Claude 4.5 — $10,057
While performance gaps remain relatively small, DeepSeek 3.1 currently leads the field.
What This Experiment Reveals About AI Trading
The results suggest that large language and multimodal models can already:
• Identify short-term market patterns
• Execute risk-managed entries and exits
• Adapt to evolving volatility
• Avoid major drawdowns
Although the gains are still modest, the consistency across all models points to a powerful shift: AI is becoming a competitive participant in real financial markets.
The Road Ahead for AI-Driven Trading
If all participants remain profitable as market conditions change, the AI Trading Showdown could serve as a benchmark for institutional and retail adoption of AI-powered trading strategies.
It also raises important questions about transparency, ethics, and risk as autonomous systems continue to gain access to capital and financial decision-making.
