AI · alternatives · 2026

24 alternatives to A Implementation of Alpha Zero for Chess in MLX

A chess engine implementation inspired by AlphaZero, using MLX for neural network computations and Monte Carlo Tree Search (MCTS) for move selection.

This is a chess engine built using MLX for neural network computations combined with Monte Carlo Tree Search for selecting moves, following the AlphaZero approach. It is designed for developers and chess enthusiasts… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier.

1AS
AlphaZero Science paper▲200
2018 · deepmind.com · its alternatives →
2
Noctie – A chess AI that predicts your rating▲134
I built over the last two years a human-like neural network chess engine that tries to predict your rating from a single game. It automatically adapts to your play and tries to play like a human at your level would play, giving you a balanced game. At the core I’m using an AlphaZero / Leela Chess Zero style neural network that I have trained on 1 billion human games from the lichess.org open database. Around this network I have built a chess engine in Rust with algorithms that use the outputs from the NN to produce human-like moves at a given rating from beginner to world champion, as…
2022 · noctie.ai · its alternatives →
3CA
ChessCoach – A neural chess engine that comments on each player's moves▲506
2021 · chrisbutner.github.io · its alternatives →
4
Sameshi – a ~1200 Elo chess engine that fits within 2KB▲230
I made a chess engine today, and made it fit within 2KB. I used a variant of MinMax called Negamax, with alpha beta pruning. For the board representation I have used a 120-cell "mailbox". I managed to squeeze in checkmate/stalemate in there, after trimming out some edge cases. I am a great fan of demoscene (computer art subculture) since middle school, and hence it was a ritual i had to perform. For estimating the Elo, I measured 240 automated games against Stockfish Elo levels (1320 to 1600) under fixed depth-5 and some constrained rules, using equal color distribution. Then converted…
Feb 2026 · github.com · its alternatives →
5
A competition for small neural networks that play strategy gamesfree▲116
A ranked ladder for small neural networks that play strategy games. Train a model, write an adapter, upload two files, and get measured into a weight class from 8 KiB up.
Sep 2026 · tinybrains.dev · its alternatives →
6
I built a game to help you learn neural network architectures▲321
2024 · graphgame.sabrina.dev · its alternatives →
7
Fabraix▲196
We built Adversarial Cost to Exploit (ACE), a benchmark that measures the token expenditure an autonomous adversary must invest to breach an LLM agent. Instead of binary pass/fail, ACE quantifies adversarial effort in dollars, enabling game-theoretic analysis of when an attack is economically rational. We tested six budget-tier models (Gemini Flash-Lite, DeepSeek v3.2, Mistral Small 4, Grok 4.1 Fast, GPT-5.4 Nano, Claude Haiku 4.5) with identical agent configs and an autonomous red-teaming attacker. Haiku 4.5 was an order of magnitude harder to break than every other model; $10.21 mean…
May 2026 · fabraix.com · its alternatives →
8
Recurrent neural net plays 'neural slime volleyball' in JavaScript▲147
2015 · otoro.net · its alternatives →
9
Improving search ranking with chess Elo scores▲193
Hello HN, I'm Ghita, co-founder of ZeroEntropy (YC W25). We build high accuracy search infrastructure for RAG and AI Agents. We just released two new state-of-the-art rerankers zerank-1, and zerank-1-small. One of them is fully open-source under Apache 2.0. We trained those models using a novel Elo score inspired pipeline which we describe in detail in the blog attached. In a nutshell, here is an outline of the training steps: * Collect soft preferences between pairs of documents using an ensemble of LLMs. * Fit an ELO-style rating system (Bradley-Terry) to turn pairwise comparisons into…
2025 · zeroentropy.dev · its alternatives →
10
Easily train AlphaZero-like agents on any environment you want▲87
Easily train AlphaZero-like agents on any environment you want! - s-casci/tinyzero
2023 · github.com · its alternatives →
11
Shoot the neural network before it shoots you▲146
Play BangBang against a Neural Network. Contribute to victorqribeiro/bangBang development by creating an account on GitHub.
2022 · github.com · its alternatives →
12BP
Beating Pokemon Red with RL and <10M Parameters▲183
Hi everyone! After spending hundreds of hours, we're excited to finally share our progress in developing a reinforcement learning system to beat Pokémon Red. Our system successfully completes the game using a policy under 10M parameters, PPO, and a few novel techniques. With the release of Claude Plays Pokémon, now feels like the perfect time to showcase our work. We'd love to get feedback!
2025 · drubinstein.github.io · its alternatives →
13
Play rock paper and scissors against a untrained neural network▲101
Can a neural network predict your next move on a game of rock, paper and scissor? - victorqribeiro/jokenpo
2019 · github.com · its alternatives →
14CG
Chessdream – Generate realistic chess positions with AI▲45
For no specific reason, I trained a neural network to generate random chess positions that look similar to positions from actual games (from lichess db). I also made it so you can condition it on some fixed pieces, and adjust the number of pieces. It turned out to be quite effective and I find it surprisingly fun and instructive to generate e.g. endgame positions with a certain pawn structure (set low temperature, place some pawns and position the kings, adjust number of pieces to get an endgame), and then figure out how to win vs. the computer in those positions. I hooked it up so that you…
2024 · chessdream.ai · its alternatives →
15IT
I trained a chess engine to play like humans▲14
I built 1e4.ai - a chess web app where you play against neural networks trained to mimic human Lichess players at specific Elo ranges. There's a separate model for each 100-point rating bucket from ~800 to 2200+, and the bots not only choose human-like moves but also burn clock time, play worse under time pressure, and blunder in human-like ways. Live demo: https://1e4.ai Code: https://github.com/thomasj02/1e4_ai A few things that might be interesting: - Trained on almost a full year of Lichess blitz games, around 1B total games - Architecture is an a small…
May 2026 · its alternatives →
16CE
ChessBoss – enhancing physical chessboards with computer vision▲83
We built ChessBoss at the TechCrunch Disrupt hackathon this week. It didn’t make the top 10 but I thought Hacker News might think it’s pretty cool. https://devpost.com/software/chess-boss There are these really cool smart chessboards that can suggest moves and track your games... but they’re $400 and weigh 19 pounds. And of course there are apps that can analyze games but tracking and inputting games by hand is a huge pain. Or fully-digital chess apps... but board games are way more fun in real life! We wondered: “why can’t you just do that in software and bring the best…
2019 · devpost.com · its alternatives →
17
Self-taught neural network learns to shoot a target▲60
Watch a Neural Network learns to shoot a target. Contribute to victorqribeiro/bangBangML development by creating an account on GitHub.
2020 · github.com · its alternatives →
18
Praex▲68
The coding agent that runs on its own AI models
3d ago · praex.ai · its alternatives →
19AQ
AI QLearning Robot Simulation in JavaScript and WebGL▲42
2015 · qlearning.4ck5.com · its alternatives →
20
Play Chess Without Moving Pieces▲36
Guess AI Engine Tournament Position, Fun Stury Tool. Play Chess Without Moving Pieces. Crazy Chess is a Variant of Random Fisher and Really Bad Chess. Because of the rearranged pieces, players cannot use typical chess opening moves. study tool to understand chess, and learning how to read the board.
2017 · ba.net · its alternatives →
21
Symbolic AI at Silver Medal, Boosts AlphaGeometry to Beat IMO Geo Gold▲6
Abstract page for arXiv paper 2404.06405: Wu's Method can Boost Symbolic AI to Rival Silver Medalists and AlphaGeometry to Outperform Gold Medalists at IMO Geometry
2024 · arxiv.org · its alternatives →
22
Maia, a human-like neural network chess engine▲10
We're thrilled to announce that www.maiachess.com is now in open beta, meaning everyone can access it! Maia is the most human-like chess AI, and is an ongoing research project at the University of Toronto developing fun, useful, and novel human-AI collaboration in chess. Please give it a try and let us know what you think. We're still rapidly improving and iterating on it. * Play Maia-2: Play the (updated) most human-like chess engine, tailored to your skill level * Analyze your games: See how you (or the pros!) stack up with both Maia’s human-based predictions and classic Stockfish…
2020 · maiachess.com · its alternatives →
23MA
Monsiv – A lightweight alternative to Chess▲17
Tautan Daftar Slot Online Mudah JP & Banyak Bonus 2024
2018 · monsiv.com · its alternatives →
24
Chessterm – Rust-based terminal chess engine for chess notation▲6
Hi HN! I just built chessterm, a Rust-powered TUI chess engine to practice chess notation (PGN) for an upcoming chess competition. This was also a way for me to learn Rust more deeply, particularly bitboards for move generation and terminal UI development with ratatui Unlike typical chess UIs that wrap around Stockfish, this is built completely from scratch, with: - PGN-only input (no AI, just human vs human) - Bitboard-based move generation (u64, precomputed attack masks) - Built with ratatui for a smooth terminal experience Would love to hear your feedback!
2025 · github.com · its alternatives →

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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →