Show HN: We're pitting 9 AI models in a stock portfolio competition(portfoliogenius.ai) Hey HN, I built Portfolio Genius, a platform where AI models manage investment portfolios and compete on public leaderboards. The experiment: On Dec 17, 2025, we gave 9 AI models (GPT-5.1, GPT-5.2, Gemini 2.5 Pro, Gemini 3 Pro, Gemini 3 Flash, Claude Opus 4.5, Claude Haiku 3.5, Claude Haiku 4.5, Grok 4) each $10K to manage across three risk profiles: aggressive, moderate, and conservative. That's 27 portfolios total. The models analyze market conditions, recommend trades, and execute them. Real pricing, real results, updated daily. Interesting early finding: For aggressive portfolios, older models are outperforming newer ones: - GPT-5.1: +5.82% (1st place) - Gemini 2.5 Pro: +4.94% (2nd) - Haiku 3.5: +1.80% (3rd) - Opus 4.5: +1.25% (7th) My hypothesis: newer models are more "careful" - they hedge, qualify, and second-guess. For aggressive investing, you need conviction. Sometimes being less sophisticated means making bolder calls. For moderate/conservative portfolios, the pattern is different - newer models do better where nuance matters. Tech stack: - Next.js frontend - Firebase/Firestore backend - Python Cloud Functions for AI orchestration - Real-time market data for pricing - Each model gets the same market data and prompts What I'm curious about: - Will the "dumber = bolder" pattern hold over time? - How will different models react to the same market events? - Do AI models have investable "personalities"? Leaderboards: https://portfoliogenius.ai/leaderboards Would love feedback from the HN community. Happy to answer questions about the architecture or methodology. |