google-deepmind/alphageometry

Health v2 · maintenance only

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4879 stars · 572 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Google DeepMind's implementation of AlphaGeometry and DDAR, AI systems that solve Olympiad-level geometry theorem proving problems. It combines a neural language model with a symbolic deduction engine to produce human-readable proofs without human demonstrations.

Use cases

• solve olympiad geometry problems automatically
• reproduce AlphaGeometry research results from the Nature 2024 paper
• run symbolic deduction for geometry theorem proving with DDAR
• generate synthetic geometry proofs with a language model
• research neuro-symbolic mathematical reasoning

When to choose

• you need a state-of-the-art automated geometry theorem prover
• you are reproducing or extending published AI math reasoning research
• you have GPU resources and want to run the full proof search pipeline

When to avoid

• you need a general-purpose theorem prover beyond Euclidean geometry
• you lack the compute (multiple GPUs and many CPU workers) for full-scale search
• you want a production-ready library with pip installation and stable API

Facets

library · maturity active

machine-learning deep-learning llm-inference math parser artificial-intelligence machine-learning mathematics python geometry-prover theorem-proving olympiad-math symbolic-reasoning research-code algorithms linux gpu

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markdown · JSON · MCP: product_card(name="google-deepmind/alphageometry")