RecPokerCoach
AI poker coaching in plain English
What it does
I couldn't afford a poker coach. So I built one. Paste your hand history from GGPoker or PokerStars and get told exactly what you're doing wrong — in plain English. No GTO, no ICM. Just honest feedback on your leaks. Select your format — cash game, bounty tournament, MTT, or Sit and Go — and the coach tailors the analysis specifically to how that game type works. First session free. No signup required.
Does the same job
all alternatives →- APAllocate poker chips optimally with mixed-integer nonlinear programming2024 · github.com · ▲213
Every time I play a casual cash poker game with friends, we spend the first several minutes struggling to figure out chip denominations. I built this to automate that process. Try it out here (the submitted link goes to the GitHub repo): https://jstrieb.github.io/poker-chipper/ It turns out that picking chip denominations optimally—such that as many chips are distributed as possible, and such that the denominations are nice—is hard (in the computational complexity sense). Upon reflection, the problem seemed to be a perfect fit for constrained optimization. I first got a…
Estimate PokerJul 2026 · estimatepoker.com · ▲19Planning poker for agile teams. No account, free & real-time
- WLWatch LLMs play 21,000 hands of PokerJan 2026 · pokerbench.adfontes.io · ▲36
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
- PAPokerbattle.ai – A week-long poker tournament for LLMsSep 2025 · pokerbattle.ai · ▲14
What PokerBattle.ai is a week-long live no-limit Texas Hold’em tournament where all players are top-tier reasoning LLMs. We’re testing how different models handle imperfect information and whether they can sustain consistent, math-driven poker without tool use or custom code. Why - In poker you can do well with basic math + consistent logic. - Superhuman poker AIs exist, but they rely on massive simulation/game-theory solvers and are effectively black boxes. - We want a rough, apples-to-apples comparison of LLM reasoning on poker decisions, and to collect public reasoning summaries that…
- OCOffsuit – Casual Poker, Redesigned2023 · offsuit.app · ▲6
For the past year my friend and I have been building a dead simple offline poker app that we actually wanted to spend time in. No constant pop-ups. No account needed. No waiting for tables. No fake felt or neon. Just free poker against intelligent AI opponents with helpful in-game stats. We’ve started offline, but are working towards online-multiplayer, tutorials for new players, and more in-game stats. Would love your feedback!
- MMMake money playing online poker with AI2020 · pokerhelper.app · ▲7
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
Launched alongside, May 2026
the whole month →
Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai
- NW
Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
Life & fun · May 2026 · github.com
- FM
Dev tools · May 2026 · github.com