Putnam 2025

Gold definitionUpdated Apr 2, 2026

Definition

Putnam 2025 refers to a specific set of 12 challenging mathematical problems, serving as a high-stakes benchmark for evaluating the advanced reasoning capabilities of AI systems, particularly in formal theorem proving. It represents a significant milestone for agentic AI in solving complex, competition-level mathematics.

At a glance

Executive summary

Putnam 2025 is a difficult set of 12 math problems used to test how well advanced AI can solve complex mathematical challenges. Recently, an AI system called Numina-Lean-Agent managed to solve all of them, showing that AI is getting much better at reasoning and proving theorems like humans.

TL;DR

Putnam 2025 is a tough 12-problem math test that a new AI system passed perfectly, proving AI's growing ability in advanced mathematical reasoning.

Key points

A challenging benchmark for evaluating AI's mathematical reasoning and formal theorem proving capabilities.
Provides a high-bar, standardized test for agentic AI systems in complex math, pushing beyond task-specific solutions.
Used by researchers and developers in AI, machine learning, and formal methods, particularly those working on agentic systems and general math reasoners.
Unlike simpler, domain-specific math tasks, Putnam 2025 represents a broad, complex, and highly competitive challenge requiring advanced reasoning and tool coordination.
Focus on developing general coding agents as versatile math reasoners, capable of solving human-level competition problems without task-specific training.

Use cases

Benchmarking AI Math Reasoners: Evaluating the performance and generality of new AI architectures designed for mathematical problem-solving and formal verification.
Developing Agentic AI Systems: Guiding the development of AI agents that can autonomously interact with formal proof assistants, retrieve theorems, and perform auxiliary reasoning.
Advancing Automated Theorem Proving: Pushing the state-of-the-art in automated theorem proving by providing problems that require deep understanding and strategic problem-solving.
Assessing General Intelligence in Math: Serving as a metric for how close AI is to human-level performance in complex, creative mathematical problem-solving.