What is AI Temperature? Randomness in AI Explained (2026)
TLDR
Temperature is a setting that controls how random or creative an AI's responses are. A low temperature produces consistent, predictable outputs. A high temperature produces more varied and creative ones.
When an AI model generates text, it does not always pick the single most likely next word. Instead, it samples from a probability distribution of possible next words. Temperature controls how spread out that distribution is.
At temperature 0, the model always picks the highest-probability word. Responses are deterministic and consistent: ask the same question twice, get the same answer. This is useful for factual tasks, classification, and code generation.
At higher temperatures (typically 0.7 to 1.0), the model samples more broadly. This introduces variation and creativity, but also more risk of going off-topic or producing inaccurate content. Most chatbots use a temperature around 0.7 by default.
Temperature above 1.0 can produce highly unpredictable, sometimes incoherent outputs. It is rarely useful in practice. The sweet spot for most tasks is between 0.3 (precise, factual) and 0.8 (creative, varied).
In practice
Low temperature use case
When generating a JSON object, extracting data from text, or writing code, you want temperature near 0. Consistent, predictable outputs that match the expected format.
High temperature use case
When brainstorming product names, writing poetry, or generating diverse marketing angles, a higher temperature produces more variety and unexpected combinations.
API control
If you use OpenAI's API directly, you can set temperature explicitly: client.chat.completions.create(model="gpt-4o", temperature=0.2, ...)
Related terms
Frequently asked questions
Can I control temperature in ChatGPT?+
Not directly in the ChatGPT interface. Temperature is controlled by OpenAI and is not exposed to end users in the chat product. You can control it via the API.
What is top-p, and how does it relate to temperature?+
Top-p (nucleus sampling) is another way to control randomness. It limits sampling to the top portion of likely tokens. Many models use both temperature and top-p together. For most users, temperature is the more intuitive control.
Why does ChatGPT give different answers to the same question?+
Because it uses a non-zero temperature. Each response samples slightly differently from the probability distribution. This is intentional and makes conversations feel more natural.
Bottom line
Temperature is a setting that controls how random or creative an AI's responses are. A low temperature produces consistent, predictable outputs. A high temperature produces more varied and creative ones.