Which LLM is the best stock picker? I built a benchmark to find out.
A new benchmark project called 1rok evaluates the stock-picking abilities of seven frontier large language models (LLMs). Each model is given $100,000 in paper capital and uses identical tools and prompts to select stocks weekly. The project aims to determine which LLM performs best in making investment decisions under uncertainty.
- ▪The project involves seven LLMs including GPT-5.5 and Gemini 3.1 Pro Preview.
- ▪Each model operates in isolation with its own Alpaca paper account and follows a structured decision-making process.
- ▪The goal of the project is not to outperform the S&P but to provide a clear evaluation of LLM capabilities in stock selection.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 485869) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Achal Jhawar Posted on May 20 • Originally published at github.com Which LLM is the best stock picker? I built a benchmark to find out. #ai #llm #opensource #showdev Every other week there's a new GPT-vs-Claude-vs-Gemini benchmark on coding or math or reasoning. None of them tell you whether the model can actually make a decision under uncertainty, where the answer isn't in the training data and the result shows up two weeks later in a P&L. So I built a different kind of eval.
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