NLP & Language · intermediate · concept 126 of 311 · Updated Nov 4, 2026
Reasoning Models & Test-Time Compute
LLMs trained to produce a long internal chain of reasoning before answering, spending extra compute at inference time to get better answers on math, code, and logic. OpenAI's o-series and DeepSeek-R1 established this as a second scaling axis alongside model size. Most frontier assistants now offer a thinking mode built on this idea.
L7 · LLM and generative AI engineerDevelopersTech leadersProduct leadersQA and testingSEO and content
Top AI contributors on this
- Demis HassabisGoogle DeepMind (chair) / Isomorphic Labs
- Ilya SutskeverSafe Superintelligence Inc. (SSI)
- Dario AmodeiAnthropic
- Sam AltmanOpenAI
- Jeff DeanDiscovery Loop
- Noam ShazeerOpenAI
Key terms
Test-time computeThinking tokensRLVRVerifiable rewardsLong CoT
Learn these first
Where you meet it in the real world
Competition math, code debugging, scientific analysis, agentic planning
Videos
▶ Why AI Models Pause to Think: Test Time Compute Explained ↗
IBM Technology · YouTube
▶ Test-Time Compute Explained: Benchmarking and Optimizing AI Agents ↗
NVIDIA Developer · YouTube
Guides and articles
Extended thinking ↗
Anthropic
Reasoning models ↗
OpenAI
What is AI reasoning? ↗
NVIDIA
Reasoning tokens ↗
OpenRouter
Why We Think ↗
Lilian Weng
Courses, papers, and more
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