Best The Many Faces of Go Alternatives ranked by AI · updated Aug 2026

Many Faces of Go is a commercial computer program for playing and studying the board game Go. It targets players who want adjustable computer opponents, handicap games, and traditional game-analysis tools in a desktop application.

Developer: David Fotland and Smart Games Price: N/A 🎯 smart-games.com/manyfaces.html

Top 6 The Many Faces of Go alternatives

1

KataGo

KataGo contributors

πŸ’‘ Pick it for the strongest free analysis and modern ownership estimates.

KataGo is a free, open-source neural-network engine for playing and analyzing Go. It is primarily a command-line and engine component rather than...

Pros

  • Provides the underlying analysis engine used by KaTrain
  • Excellent analysis strength with territory and score estimation features
  • Highly configurable for custom frontends and automated review pipelines

Cons

  • Lacks KaTrain's integrated training and user-interface features
  • Requires a compatible GUI or command-line workflow for practical study
  • Model, configuration, and hardware setup are technical
2

Leela Zero

Leela Zero contributors

πŸ’‘ Choose it for a free, AlphaGo-style engine with broad GUI compatibility.

Leela Zero is an open-source neural-network Go engine inspired by AlphaGo Zero. It is designed for strong computer play and analysis, particularly...

Pros

  • Far stronger than Many Faces of Go at serious play
  • Open-source engine with widely supported neural-network workflows
  • Works with common Go interfaces and analysis tools

Cons

  • Requires separate GUI and network-weight setup
  • Less feature-rich for score estimation than KataGo
  • Older project with slower development than newer leading engines
3

Crazy Stone

Remi Coulom and Unbalance Corporation

πŸ’‘ Pick it for a ready-to-use commercial Go opponent with less technical setup.

Crazy Stone is a commercial Go program for playing against the computer and reviewing games. It is intended for players who want...

Pros

  • More complete out-of-the-box product than standalone Go engines
  • Offers approachable play settings for casual and intermediate players
  • Available across multiple consumer platforms and editions

Cons

  • Modern neural-network engines generally provide stronger analysis
  • Platform availability and features differ between editions
  • Commercial purchase is less flexible than free open-source options
4

AI Sensei

AI Sensei

πŸ’‘ Choose it for browser-based lessons and automated reviews instead of legacy desktop play.

AI Sensei is a web-based Go game review and training service that uses neural-network analysis to identify mistakes and suggest improvements. It...

Pros

  • No local engine installation or GPU configuration is required
  • Provides structured game reviews and training problems
  • More accessible for beginners than KaTrain's technical desktop setup

Cons

  • Free usage is more limited than KaTrain's unlimited local analysis
  • Requires uploading games to an online service
  • Advanced features depend on a subscription

Freemium, paid plans from $9.99/mo

5

GNU Go

GNU Go contributors

πŸ’‘ Use it when you want a lightweight, scriptable, and fully free Go engine.

GNU Go is a free, open-source Go engine that plays through standard interfaces and supports game analysis. It suits developers, educators, and...

Pros

  • Lightweight and easy to run on modest hardware
  • Free software with a mature, well-documented codebase
  • Integrates with multiple Go clients and server software

Cons

  • Much weaker than modern engines such as KataGo
  • Usually needs a separate GUI for comfortable play
  • Provides less detailed analysis and visualization than newer tools
6

Lizzie

Lizzie contributors

πŸ’‘ Pick it for a visual desktop analysis board paired with a modern Go engine.

Lizzie is an open-source desktop Go analysis interface for engines such as KataGo and Leela Zero. It is aimed at players who...

Pros

  • Mature analysis interface with strong variation and win-rate visualization
  • Supports KataGo and other compatible Go engines
  • More flexible for engine experimentation than many hosted services

Cons

  • Less focused on guided training than KaTrain
  • Engine and model setup can be technically demanding
  • Interface feels older and less streamlined than newer web apps

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