by Amit Shekhar · 15 September 2026
How does Temperature control LLM output?
How Temperature controls LLM output, the single number that decides whether an AI model gives us a safe and predictable answer or a creative and surprising one. We will also see how an LLM picks one token at a time, how it gives a score to every possible next token, how those scores become probabilities, how Temperature quietly changes those probabilities before the pick happens, what happens at low, high, and zero Temperature, why it is called Temperature, and when to use which value based on our use case.
Before you read, guessHow does an LLM generate text?
Ten seconds, a guess, then read — a wrong guess still makes the answer stick.
What this article covers
- What is Temperature in LLMs?
- How does an LLM pick the next token?
- From scores to probabilities
- Where does Temperature come into the picture?
- Step-by-step example with numbers
- Low Temperature
- High Temperature
- Temperature = 1 and Temperature = 0
- Why is it called Temperature?
- When to use which Temperature?
- Common mistakes while using Temperature
The article lives on outcomeschool.com. Read it there, then come back: the tutor in the margin has read it and will answer questions, and the questions below check what stayed.