OpenAI o1 introduces inference-time reasoning with a large AIME performance jump

The o1 series was trained to spend more inference-time computation on multi-step reasoning before producing an answer.

What happened?

OpenAI reported o1 at 74% single-sample accuracy on AIME 2024 and 93% after reranking 1,000 samples, far above GPT-4o's 12% baseline.

Why it matters

The release helped establish test-time compute and long reasoning traces as central levers for frontier mathematical performance, providing context for later math-specific systems.

Significance rationale: OpenAI o1 was a major general-purpose reasoning-model release, but its place in the AI4Math Chronicle is contextual: AIME demonstrated capability rather than the release itself contributing a new mathematical result, proof, formalization, or math-specific system.

Historical context

Primary evidence

Evidence & status at a glance

Significance
H3 · Context event
Verification
Claimed
Evidence level
E1 · Primary claim
AI role
Computation only
Formal assurance
No formal assurance

How should these labels be read? →

Contribution & verification

Mathematical novelty
Benchmark result
Interface
Informal, Symbolic
AI contribution
The model performs extended internal reasoning before answering mathematical problems.
Human contribution
OpenAI researchers designed the reasoning training method and benchmark evaluations.
Verification
Claimed · E1 · Primary claim · No formal assurance
Last reviewed
2026-09-11

Technical details

Systems
openai-o1
Organizations
openai
Problems
aime-2024
Methods
reasoning-model, test-time-compute, reinforcement-learning

Sources & artifacts

Verification history

  • 2024-09-12 · Claimed · E1 · Primary claim

    The Chronicle records this event from the cited primary or official source; the status does not imply independent Chronicle verification.

Corrections

No corrections recorded.