Reasoning models are AI systems trained to think step by step before answering, like OpenAI's o1 series and Anthropic's reasoning models. Tech jargon, not concerning. Your teen may be using them for school work; same conversations about academic integrity apply. If your kid uses it constantly, ask them where they first heard it, not to police their speech but to understand which online community they are in.
reasoning model
An LLM trained or configured to produce long chains of internal "thinking" tokens before answering — trading latency for higher accuracy on complex problems.
Etymology timeline
Born ~2023 · 1 year of recorded useSeen in the wild
Claude is a reasoning model. I'm explaining how it was designed to behave.
MolmoAct 2 builds on MolmoAct, our first Action Reasoning Model (ARM). Like its predecessor, MolmoAct 2 reasons about the world in 3D before taking actions. It now runs up to 37x faster & handles two-armed tasks out…
A reasoning model, also known as a reasoning language model (RLM) or large reasoning model (LRM), is a type of large language model (LLM) that has been specifically trained to solve complex tasks requiring multiple st…
Definitions
An LLM trained or configured to produce long chains of internal "thinking" tokens before answering — trading latency for higher accuracy on complex problems. OpenAI's o1 and Claude's extended thinking are examples.
"Switched to a reasoning model for math problems. Slower but actually correct."
Reasoning models are AI systems trained to think step by step before answering, like OpenAI's o1 series and Anthropic's reasoning models. Tech jargon, not concerning. Your teen may be using them for school work; same conversations about academic integrity apply. If your kid uses it constantly, ask them where they first heard it, not to police their speech but to understand which online community they are in.
Reasoning model is an AI-industry term for a language model trained or prompted to produce explicit step-by-step reasoning before answering. Use in AI and tech contexts. Formal equivalent: "a model with chain-of-thought reasoning capabilities." Common non-native mistake: confusing with "reasoning" in everyday English; here it specifically refers to the model's training objective and behaviour. Read or listen to the word in context several times before trying it yourself; the right register is harder to learn than the dictionary meaning.
“Claude is a reasoning model. I'm explaining how it was designed to behave.”
— Bluesky· May 2026“MolmoAct 2 builds on MolmoAct, our first Action Reasoning Model (ARM). Like its predecessor, MolmoAct 2 reasons about the world in 3D before taking actions. It now runs up to 37x faster & handles two-armed tasks out of the box without per-task fine-tuning.”
— Bluesky· May 2026“A reasoning model, also known as a reasoning language model (RLM) or large reasoning model (LRM), is a type of large language model (LLM) that has been specifically trained to solve complex tasks requiring multiple steps of logical reasoning.”
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Why is this section here?
Slang is read by different audiences for very different reasons. The For parents view re-explains the term in plain, non-judgemental language so a caregiver can understand what their child means without needing the surrounding subculture. The For English learners view focuses on register (when it's safe to use), formal alternatives, and common mistakes — what a textbook won't teach you.
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Semantically related
- chain of thought80%
Prompting or training technique where an LLM produces intermediate reasoning steps before the final answer, dramatically improving accuracy on multi-step problems.
- chain of thought76%
A sequence of intermediate reasoning steps generated by a model to break down and solve a problem before producing its final answer or response.
- test-time compute72%
Using more compute at inference time — via longer chain-of-thought, sampling, or verification — to boost model quality without retraining. The OpenAI o1 + Claude extended-thinking paradigm. You pay seconds to gain accuracy.
- prompt engineering71%
The craft of writing inputs to LLMs to reliably produce the output you want. Includes role-setting, few-shot examples, chain-of-thought, and careful phrasing.
- tool use68%
The ability of an LLM to call external functions (search, code execution, databases) mid-conversation. The building block of agentic systems.