LeelaChessZero/lc0

Health v2 · maintenance only

Adoption not part of the score

3193 stars · 604 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Lc0 is an open-source, UCI-compliant chess engine that plays chess using neural networks trained via AlphaZero-style self-play reinforcement learning. It supports GPU acceleration through CUDA, cuDNN, onnxruntime, Apple Metal, and experimental SYCL backends, plus CPU via OpenBLAS or DNNL.

Use cases

• play chess against a neural network engine
• run a strong UCI chess engine in a chess GUI
• analyze chess positions with deep positional insight
• generate self-play games for neural network training
• benchmark GPU inference for board game AI
• study AlphaZero-style reinforcement learning in practice

When to choose

• you want a strong, human-bias-free neural network chess opponent or analysis engine
• you have a GPU (NVIDIA, AMD, Intel, or Apple) and want accelerated engine play
• you want to contribute to or study open AlphaZero-style self-play training
• you need a UCI engine compatible with standard chess GUIs

When to avoid

• you need a lightweight CPU-only engine with minimal dependencies
• you want a traditional hand-crafted evaluation engine like Stockfish's classical approach
• you need a general-purpose game AI framework rather than a chess-specific engine
• you cannot install GPU toolchains like CUDA or onnxruntime and need top-level strength

Facets

application · maturity active

machine-learning deep-learning reinforcement-learning gpu-computing game machine-learning deep-learning reinforcement-learning gpu-computing windows cpp cli chess-engine uci alphazero neural-network self-play mcts chess-ai onnxruntime metal game-development linux macos cuda gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="LeelaChessZero/lc0")