K-Culture GlossaryㅊWords you meet while using AI
Reasoning Model
A model that takes "time to think" on its own before answering. Slower, but much stronger on hard problems like math and coding.
In plain words
A typical language model starts writing an answer the moment it gets a question. A reasoning model works differently — it takes "time to think" before answering. It breaks the problem down, tries out multiple approaches, checks its own answer, and only then gives a final response.
Think of a quiz show: a regular model is the contestant who buzzes in right away, while a reasoning model is the one who works it out on scratch paper before raising a hand. This is naturally slower and uses more cost (tokens), but it significantly improves accuracy on problems that require step-by-step thinking, like math, science, and coding.
Starting with OpenAI's o1 in 2024, the whole industry moved in this direction. The "thinking mode" or "reasoning mode" toggle you see in chatbots today is exactly this, and when an article says "giving it more thinking time improves performance," it's talking about reasoning models.
How it shows up in the news
"The reasoning model solved an International Mathematical Olympiad problem" — this is the classic way articles in this genre put it, implying that the longer it thinks, the harder the problems it can solve.
Try it yourself
- In your chatbot's model selector, pick a mode labeled "thinking" or "reasoning."
- Ask it something like: "Which is bigger, 9.11 or 9.9? Show me your reasoning as you answer."
- Compare how the time and process differ from the regular mode before you get an answer.
"Reasoning" is used to mean two different things
Is it about thinking before answering?, Is it about actually running the model?
This is the most dangerous overlap in Korean AI reporting. English has two distinct words, reasoning and inference, but both have often been rendered with the same Korean term. A sentence like "inference costs have spiked" is usually about the cost of running the model, while "reasoning ability has improved" is about the model's capacity to think. Same word, different event.
| Aspect | Reasoning Model | Training & Inference |
|---|---|---|
| Original term | reasoning — thinking things through logically | inference — running a trained model to produce an answer |
| Opposite | answering immediately without thinking it through | training — the time spent learning |
| When it improves | it solves hard problems like math or coding | answers come out faster and cheaper |
| In articles | "reasoning ability," "spent more time thinking" | "inference cost," "inference-only chip," "inference demand" |
| How they relate | the longer it thinks, the longer it takes to run | so this cost rises — this is behind today's chip shortage |
Rule of thumbIf it's preceded by "cost," "chip," or "demand," it's about running the model (inference); if it's preceded by "ability" or "process," it's about thinking (reasoning).
See also
Stories using this term
No story has used this term yet. New ones attach here automatically.