alt Hacker NewsShow HN: Watch LLMs play 21,000 hands of Poker
PokerBench is my attempt at a new LLM benchmark wherein frontier models play Texas Hold'em in an arena setting. It also features a simulator to view individual games and observe how the different models reason about poker strategy. Opus/Haiku, Gemini Pro/Flash, GPT-5.2/5 mini, and Grok 4.1 Fast Reasoning have all been included.
All code -> https://github.com/JoeAzar/pokerbench
Comments
Finally, a way to settle the model wars that actually matters: Texas Hold'em. That 3D replay view is sick! ♠♦ I spent way too long watching the replay on Game 2a58900d. It’s wild to see the chain of thought mapped against the betting rounds. It really exposes when a model is hallucinating a strong hand versus actually calculating pot odds. This 'PokerBench' might actually become the standard for measuring agentic risk-taking.
Fun, any idea how much would be the cost per game? I am worried 160 isnt a big enough sample size.
Do you have idea why smaller models are better then large ones?
Very very fun. Just glancing at this quickly at lunch but is there any idea of incorporating tool use?
What about the open source models? I remember from the trading benchmarks Deepseek performed pretty well.
Do you have any idea why the win rate for GPT-5.2 is higher than Gemini 3 Flash yet the former loses money while the latter earns money? Is it just bet sizing (betting more when it has a good hand) or something else?