Trustworthy
Lean's minimal trusted kernel guarantees absolute correctness in mathematical proof, software and hardware verification.
Lean is an open-source programming language and proof assistant that enables correct, maintainable, and formally verified code
Powerful automation
Mathematics
-- 'Grind' efficiently manages complex pattern matching and
-- case analysis beyond standard tactics.
example (x : Nat) : 0 < match x with
| 0 => 1
| n+1 => x + n := by
grind
-- Automatically solves systems of linear inequalities.
example (x y : Int) :
27 ≤ 11*x + 13*y → 11*x + 13*y ≤ 45
→ -10 ≤ 7*x - 9*y → 7*x - 9*y > 4 := by
grind
/-- A prime is a number larger than 1 with no trivial divisors -/
def IsPrime (n : Nat) := 1 < n ∧ ∀ k, 1 < k → k < n → ¬ k ∣ n
/-- Every number larger than 1 has a prime factor -/
theorem exists_prime_factor :
∀ n, 1 < n → ∃ k, IsPrime k ∧ k ∣ n := by
intro n h1
-- Either `n` is prime...
by_cases hprime : IsPrime n
· grind [Nat.dvd_refl]
-- ... or it has a non-trivial divisor with a prime factor
· obtain ⟨k, _⟩ : ∃ k, 1 < k ∧ k < n ∧ k ∣ n := by
simp_all [IsPrime]
obtain ⟨p, _, _⟩ := exists_prime_factor k (by grind)
grind [Nat.dvd_trans]
/-- The factorial, defined recursively, with custom notation -/
def factorial : Nat → Nat
| 0 => 1
| n+1 => (n + 1) * factorial n
notation:10000 n "!" => factorial n
/-- The factorial is always positive -/
theorem factorial_pos : ∀ n, 0 < n ! := by
intro n; induction n <;> grind [factorial]
/-- ... and divided by its constituent factors -/
theorem dvd_factorial : ∀ n, ∀ k ≤ n, 0 < k → k ∣ n ! := by
intro n; induction n <;>
grind [Nat.dvd_mul_right, Nat.dvd_mul_left_of_dvd, factorial]
/--
We show that we find arbitrary large (and thus infinitely
many) prime numbers, by picking an arbitrary number `n`
and showing that `n! + 1` has a prime factor larger than `n`.
-/
theorem InfinitudeOfPrimes : ∀ n, ∃ p > n, IsPrime p := by
intro n
have : 1 < n ! + 1 := by grind [factorial_pos]
obtain ⟨p, hp, _⟩ := exists_prime_factor (n ! + 1) this
suffices ¬p ≤ n by grind
intro (_ : p ≤ n)
have : 1 < p := hp.1
have : p ∣ n ! := dvd_factorial n p ‹p ≤ n› (by grind)
have := Nat.dvd_sub ‹p ∣ n ! + 1› ‹p ∣ n !›
grind [Nat.add_sub_cancel_left, Nat.dvd_one]
Powerful
From elementary concepts to cutting-edge research, Lean's expressive language and extensive built-in tools let users focus on the big picture rather than routine details.
Extensible
Lean's metaprogramming capabilities enable users to extend the language with domain-specific notations and new proof automation techniques.
Get Started with Lean
Lean lets you write precise, verifiable code and formal proofs. Whether you are new or experienced, now is a great time to start.
FEATURED PROJECTS
Lean in Action
Showcasing Real-World Applications
ArkLib
ArkLib, a project supported by the Ethereum Foundation, anchors a growing ecosystem of Lean libraries for formally verifying succinct non-interactive arguments of knowledge (SNARKs). It mechanizes the subtle, probabilistic security proofs these cryptographic systems depend on, giving zk engineers and cryptography researchers machine-checked specifications and executable references. This brings high assurance to proof systems where a single soundness bug can be catastrophic.
Read More
Veil
Veil is an open-source multi-modal verification framework for distributed protocols, embedded in Lean. In contrast to standalone verifiers, Veil uses Lean as a platform, combining symbolic and concrete model checking, SMT-based automated proofs, and interactive theorem proving in a single cohesive tool with foundational guarantees and rich in-editor feedback. It shows Lean is not just a proof assistant, but a platform for industrial-strength verifiers with great user experience.
Read More
Cedar
AWS uses Lean and verification-guided development to formally verify Cedar, the AWS authorization policy language. The approach involves creating executable models in Lean, proving security properties, and validating them against production code through differential testing. This achieves high assurance with minimal runtime overhead, demonstrating Lean's viability for verifying critical software.
Read More
Aeneas
Aeneas takes a novel approach to Rust verification. Unlike other verification approaches that must reason about memory directly, Aeneas leverages Rust's rich type system to eliminate memory reasoning entirely for many Rust programs.
Read More
Mathlib
Mathlib is Lean's comprehensive mathematical library containing over a million lines of formalized mathematics spanning algebra, analysis, topology, probability, and computer science. This community-driven resource enables mathematicians to tackle frontier research problems and engineers to build verified systems by providing a rigorously verified foundation of mathematical knowledge that eliminates duplication of effort.
Read More
Fermat's Last Theorem
The Fermat's Last Theorem project is formalizing one of mathematics' most complex proofs in Lean, demonstrating the proof assistant's capacity to handle frontier research mathematics. This ambitious work is creating formalized definitions for advanced number-theoretic objects, enabling mathematicians to build machine-verified proofs of cutting-edge results while establishing Lean as a powerful platform for mathematical collaboration.
Read More
PROGRESS
Growth and Impact
Tracking Lean's reach across math, research, and industry
JULY 2026
Microsoft Research reports on how Lean, via the Aeneas toolchain, formally verifies production cryptographic algorithms in SymCrypt; New Scientist reports on AI use supporting the Lean formalization of Fermat's Last Theorem
JUNE, 2026
Quanta Books publishes The Proof in the Code, "the definitive account of the birth and rise of Lean"; Fortune magazine announces Axiom's EconLib, formalizing economic theory in Lean; StatLib, a library for mathematical statistics, is launched
MAY, 2026
Google DeepMind announces AlphaProof Nexus and autonomous proofs of 9 Erdős problems; SAIR convenes the Science x AI Summit in Palo Alto, foregrounding Lean and AI-assisted proof discovery; NASA holds its Formal Methods Symposium with keynotes on Lean, CSLib and Aristotle; TorchLean is released, bridging PyTorch and Lean
"
Lean enables large-scale collaboration by allowing mathematicians to break down complex proofs into smaller, verifiable components. This formalization process ensures the correctness of proofs and facilitates contributions from a broader community. With Lean, we are beginning to see how AI can accelerate the formalization of mathematics, opening up new possibilities for research.
"
Lean has become a key enabler in scaling automated reasoning at Amazon. Its capacity to verify complex systems involving advanced mathematical concepts has transformed how we tackle problems once thought too complex or impractical. Lean is an indispensable tool in modern, large-scale software engineering, helping ensure soundness, correctness, and verified AI across our systems.
Byron Cook
VP and Distinguished Scientist, AWS
"
At Google DeepMind, we used Lean to build AlphaProof, a new reinforcement-learning based system for formal math reasoning. Lean’s extensibility and verification capabilities were key in enabling the development of AlphaProof.
Pushmeet Kohli
VP, Science and Strategic Initiatives, Google DeepMind
"
Mathematical Superintelligence (MSI) with Lean will play a critical role in any industry where safety is paramount, including aerospace, automotive, and medical technology. In addition, we look forward to providing early access to our technology to students and researchers to accelerate advancement in mathematics, science, and engineering.
Tudor Achim
Co-Founder and CEO, Harmonic
"
Lean is the core verification technology behind Cedar, the open-source authorization language that powers cloud services like Amazon Verified Permissions and AWS Verified Access. Our team rigorously formalizes and verifies core components of Cedar using Lean’s proof assistant, and we leverage Lean’s lightning-fast runtime to continuously test our production Rust code against the Lean formalization. Lean’s efficiency, extensive libraries, and vibrant community enable us to develop and maintain Cedar at scale, while ensuring the key correctness and security properties that our users depend on.
Emina Torlak
Senior Principal Applied Scientist, AWS