Which LLM is the best stock picker? I built a benchmark to find out.

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. Seven frontier LLMs, $100,000 of paper capital each, identical tools, identical prompts, identical data. Every Monday they pick stocks. The market grades them.

The project is . The clock started January 20, 2026.

The contestants

• 
  GPT-5.5 (OpenAI)


• 
  Gemini 3.1 Pro Preview (Google)


• 
  Grok 4.3 (xAI)


• DeepSeek V4 Pro


• 
  GLM-5.1 (Zhipu)


• 
  Kimi K2.6 (Moonshot)


• MiniMax M2.7

Each model gets its own isolated Alpaca paper account. Same tool registry, same prompts, same screener output. The LLM is the only variable.

Why this isn't a hedge fund pitch

I want to be upfront. I don't think a weekly LLM-driven portfolio is going to beat the S&P. If it could, hedge funds would already be doing it. Some are; results so far are mixed.

The point of 1rok isn't alpha. It's that "which model should I use" is the most-asked question in AI engineering, and most of the answers are vibes. Coding evals are saturated. Math benchmarks get gamed. I wanted a downstream task where the model has to plan, call tools, synthesize conflicting signals, and commit to a decision, with an objective scoreboard at the end.

Stock picking happens to fit. The fact that everyone has an opinion about it is a bonus.

The pipeline

Every Monday at 9:45 ET, a cron fires and kicks off one run per model in parallel. Each run is 10 agents in 4 stages:

for the live leaderboard, agent traces, and per-trade reasoning.

Star the repo if you want milestones. I'll write up findings as the leaderboard separates.