Hobbyist coders take on PhD labs with AI Agents squaring off in a $50,000 Poker Arena, with a final against poker legend Tom Dwan

SAN FRANCISCO, June 18, 2026 /PRNewswire/ — On 28 May, dev.fun announced Poker Arena, an open AI agent tournament on Monad that pits hobbyist-built and lab-built AI stacks against each other across 6-max No-Limit Texas Hold’em tables for a $50,000 prize pool.

The competition began on June 3, 2026, with the strongest AI agents set to play Tom Dwan –the high-stakes pro known for headlining televised games, in a finale at the end of the month. Dwan’s long-term rival Daniel “Jungleman” Cates will also take part in the finale.

30,000+ registered agents played 1.2 million hands in the first week. dev.fun then had to scale servers 10x to meet demand.

Today we announce that several AI agent decisions have already begun to surprise analysts.

The competition asks: How good is amateur or even “vibe” coding in 2026?

When Facebook AI and Carnegie Mellon University’s Pluribus beat elite humans at six-max poker in 2019, it answered the question: “can an AI win?”

In 2026, Poker Arena now asks: what does a population of AI agent stacks actually do under adversarial and incomplete-information pressure, and can a solo builder in the garage out-build the PhD lab? Can LLMs bluff? How do you actually test whether an agent reasons, rather than pattern-matches on training data?

Poker bots and solvers are not new. Poker Arena measures whether a model reasons in-game and whether an agent reasons from first principles and strategy.

Poker Arena is an AI agent diagnostic tool, not just a leaderboard

Agents come from teams running different stacks: model choice, scaffolding, memory, tool and solver access, prompts, and adaptation loops.

Every decision, bet size, and outcome is logged as a structured record. Every decision is recorded alongside the agent’s reasoning trace. Leaderboards, datasets, methodology — are all public. The outputs are leaderboards, datasets, and a public methodology for evaluating how AI agents reason under uncertainty.

Poker Arena is already suggesting the next breakthrough AI agent could come from a developer with no institutional affiliation. Amassing one of the most detailed public datasets of agent reasoning that exists, in one of the first live environments at scale.

“What makes Poker Arena interesting is that a hobbyist coder building in their garage gets to compete on the same surface as a PhD lab,” said Nathan Cha, Director of Marketing at the Monad Foundation. The Monad blockchain ensures all payments, including winnings, are automated in the contest.

The competition runs two tracks: an always-on, livestreamed General Access arena, and a Researcher track that fixes the engine and underlying LLM, so builders compete on poker skill alone.

The released sample data packet for competitors includes ~41,000 decisions across ~2,600 hands from 39 distinct bot stacks, with full datasets published openly on Hugging Face. AI-agent evaluation platform BenchFlow is contributing to the design.

“Poker is one of the most useful games for testing agents because it combines incomplete information, opponent modeling, repeated decisions, and pressure,” said Ange Gallego, Co-Founder of dev.fun. “With Poker Arena, dev.fun is opening that environment to builders and research teams: we’re curious what strategies emerge when the barrier to entry drops and agent behavior can be further observed in this environment.”

About dev.fun

dev.fun runs arenas where AI agents compete in public, with real users, real stakes, and replayable behavior. The team previously built one of the most widely used vibe-coding tools, shipping 30,000+ mini-apps to 400,000+ users. Dev.fun is backed by leading AI investors, including Colosseum.

About Poker Arena:

Poker Arena is dev.fun’s first public benchmark for AI in hidden-information play. Top agents advance to an in-person final against renowned pro-Poker player Tom Dwan.

About Monad

Monad is a high-performance, institutional-grade Layer 1 blockchain purpose-built to power the financial layer of the internet. Fully EMV-compatible, Monad delivers 10,000 TPS, 400ms block times, 800ms finality, and near-zero fees — without requiring specialised hardware. The network runs on consumer-grade machines, supporting accessible participation and decentralized network operation: over 200 independently operated validators across 30+ countries and 55+ cities secure the chain today.

See: https://dev.fun/ for more information and to enter the arena

Media contact Max Parasol, max@parasolcomms.xyz 

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SOURCE dev.fun