The GTO trainer allows you to practice specific spots repeatedly, reinforcing optimal play patterns. Consistent practice is key to improving your poker skills.

You can upload your hand histories directly into the Analyze section of GTO Wizard. It shows how to play any hand perfectly against your opponents. Detect superhuman plays and assess the closeness of a player’s strategy versus the optimal strategy. Detect superhuman plays and assess the closeness of a player’s strategyversus the optimal strategy.

With current rake levels and competition, grinding manually at micro stakes is a questionable pursuit. The bot follows sound baseline strategy but deviates when it detects specific opponent weaknesses, and profits from their mistakes. Can evaluate any game state without pre-computed tables. Solver-based , GTO lookup, — use pre-computed solutions from GTO solvers as lookup tables.

The project directory will store your public data combinations in a file named *card_info_lut.joblib*.

• The profiling engine tracks VPIP, PFR, 3-bet frequency, fold-to-c-bet, and aggression factor per player.
• We begin the action with the effective stacks between 220bb and 520bb.
• Online Poker Bot AI supports up to six simultaneous tables, each with its own independent opponent models and strategy context.
• These aren’t mere tools—they’re cunning predators, the most advanced poker AI ever designed to exploit every weakness in your gameplay before you even spot your own leaks.
• This serves as a testbed for cutting-edge machine reasoning, particularly assessing how large language models perform in poker AI applications.
• CFR produces bluffs based upon the requirements of mathematical certainty.

Villain Ranges

Preflop in early position , UTG+1 after UTG fold,, is a premium suited ace with strong playability, high equity against calling ranges, and flush/straight potential. The action begins with the effective stacks of U8 Grok holding ATs with 600+bb covering table and always-happy-to-splash LLAMA in U7 holding 88 and 150bb. In this hand — we witness a wild exploitive decision-making that leads to an all-in preflop of ATs vs 88 for 300bb pot. Like all other LLMs, it gets excited about extracting value from the bluffs and neglects to consider the risks of being stacked by the overpairs. It successfully reasons against a 5-bet and decides to call in position (closing the action), which is not unreasonable.

Once there is a working prototype — write in a systems level language like C++ and optimise for performance. This engine is now the first pass that will be used support self play. The following code is how one might program a round of poker that is deterministic using the engine. A low level thing to first to is to implement a poker engine class that can manage a game of poker. There are two parts to this repository, the code to manage a game of poker, and the code to train an AI algorithm to play the game of poker. Later on in the code, as proxy for some code that obtains a new state …

If you’re a club owner, bots can be a threat or an opportunity. For earning — automatic mode generates profit while you’re doing other things A bot lets you play more tables, more hours, with less time investment.

Initial Access

Our AI opponents only see their own cards, just like in real poker. Friendly opponents who play solid poker with realistic decision-making. Train against AI that plays like humans, not calculators.

• Strengthen the game engine with more tests and allow users to see live visualisation of game state.
• With QQ facing a flop raise to $3,200 , ~93% pot, after calling our 4-bet and flop bet, the vulnerable hand now confronts a J-high board (5♦, J♥, 2♠).
• This hand might demonstrate how a misguided aggression may have helped it to achieve this impressive result.
• Most training tools pit you against a perfect GTO solver or generic AI opponents with no real personality.

The majority of these approaches rely on data from zoom or Fast Forward simulations. The model captures the disciplined, forceful approach of Patrik Antonius—mastery of calculated aggression, unwavering composure, and razor-sharp decision-making. It mirrors Phil Ivey’s balanced, instinctive high-pressure style, featuring flawless timing, subtle opponent reads, and composed aggression. Discover techniques to dominate opponents while maintaining absolute control. Become the unseen “calling station” that opponents never anticipate. A refined twist on the traditional loose-passive strategy—filled with calling, flop-heavy play, and deceptive value bets.

Overfolds in many situations and avoids big pots. Plays too many hands but avoids aggression. Choose your move (observe QuintAI’s suggestion), and compare it to Melika’s actual play. UTG opened; BB matched; BB checked. While none match CFR-based solvers in performance, they act as valuable research tools and benchmarks for evaluating LLM reasoning.

It scans the live game—your cards (the board), pot size, stack depths, seating positions, and the action history—then cross-checks this data against a full GTO strategy database to pinpoint the best move. Poker Helper AI functions as an Android-compatible decision aid integrated into your poker client or emulator. Poker Helper AI bridges the gap by embedding a real-time GTO coaching engine directly into your gameplay — analyzing each scenario live and delivering high-EV recommendations before you act. To excel consistently at online poker, you must out-decide opponents on every betting round of every hand.