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Thinking Machines

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AXLE: A Cloud Infrastructure for Lean 4 Theorem Proving Utilities

Jun 24, 2026

Existing infrastructure struggles to meet the demands of AI-driven mathematical research for Lean 4, particularly in high-throughput processing, scalable verification, multi-version support, and request-level isolation. This work proposes the first cloud-native Lean 4 service platform, which uniquely enables high concurrency, per-request isolation, and coexistence of multiple Lean 4 and Mathlib versions. The platform integrates 14 metaprogramming tools—including proof checking, semantic source code manipulation, deterministic repair, and lemma extraction—and provides seamless access via HTTP API, Python SDK, CLI, and a web UI, eliminating the need for local deployment. Already publicly deployed, it has processed over 500 million requests and powered Axiom Math’s perfect score in the 2025 Putnam Competition, thereby addressing a critical gap in scalable theorem-proving infrastructure.

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Latest Papers

AXLE: A Cloud Infrastructure for Lean 4 Theorem Proving Utilities

Jun 24, 2026

Existing infrastructure struggles to meet the demands of AI-driven mathematical research for Lean 4, particularly in high-throughput processing, scalable verification, multi-version support, and request-level isolation. This work proposes the first cloud-native Lean 4 service platform, which uniquely enables high concurrency, per-request isolation, and coexistence of multiple Lean 4 and Mathlib versions. The platform integrates 14 metaprogramming tools—including proof checking, semantic source code manipulation, deterministic repair, and lemma extraction—and provides seamless access via HTTP API, Python SDK, CLI, and a web UI, eliminating the need for local deployment. Already publicly deployed, it has processed over 500 million requests and powered Axiom Math’s perfect score in the 2025 Putnam Competition, thereby addressing a critical gap in scalable theorem-proving infrastructure.

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