Reasoning & Test-Time Compute · 2024
OpenAI o1 / o3 Reasoning Systems
These were the first widely deployed systems trained to spend additional inference-time computation on an internal chain of reasoning before answering, trading longer per-query compute for markedly higher accuracy on math, science, and coding problems.
Editorial record
Plain-language summary
Rather than answering immediately, these models generate an extended internal reasoning process and can allocate more or less thinking time to a query. Accuracy on hard reasoning benchmarks improved as more inference compute was spent, establishing test-time compute as a scaling axis distinct from making the model or its training set larger. The reasoning details were released through system cards rather than a formal paper, and the internal chain of thought was kept hidden from users.
Knowledge graph
Relationships
Descendants
Parallel workEvidence: Probable
DeepSeek-R1: Incentivizing Reasoning via RL (RLVR)
R1 openly parallels closed o-series behavior
P-225 system card
Source record
Provenance
- Record ID
- P-225
- Record created
- 2026-07-13
- Last reviewed
- 2026-07-14
- Record version
- 2
Citation caveat: Citation metadata is approximate and marked unverified in the source dataset.