# What is temperature in AI models? — QANATONE > Temperature sets how much risk a model takes when picking the next word. Low values give consistent answers, high values varied ones. Kaynak: https://www.qanatone.com/en/nedir/temperature-nedir/ --- [Explainers](https://www.qanatone.com/en/nedir/) # What is temperature in AI models? 15 Sep 2026 2 min read Model Settings · Temperature Temperature sets how much risk a model takes when picking the next word. Low values give consistent answers, high values varied ones. ## What is temperature? At every step a language model computes a list of candidates for the next [token](https://www.qanatone.com/en/nedir/token-nedir/) and a probability for each. Temperature adjusts how those probabilities are used. At low temperature the model almost always picks the most likely candidate. At high temperature it gives less likely candidates a chance too, so answers vary and sometimes surprise. Take the sentence "For breakfast most people eat ...". Low temperature picks "eggs" or a similar top choice nearly every time. High temperature sometimes says "pancakes", sometimes "porridge". ## Which value for which job? Most APIs accept values between 0 and 1 or 0 and 2. Jobs with one right answer, such as data extraction, coding and classification, use low values. Jobs that need variety, such as ad copy, name ideas or brainstorming, try higher values. Push the value too high and the text loses coherence. ## Does temperature 0 always give the same answer? Usually, but not guaranteed. Small numerical differences in hardware and software mean the same prompt can occasionally produce different output even at zero. If you need exact repeatability, store the output and reuse it. ## Temperature and hallucination Low temperature makes a model consistent, not correct. If the model believes a wrong fact is highly likely, it will repeat it at temperature zero as well. The way to reduce [hallucination](https://www.qanatone.com/en/nedir/halusinasyon-nedir/) is to give the model the right information, for example with [RAG](https://www.qanatone.com/en/nedir/rag-nedir/). A related setting is top-p: the model only chooses among the strongest candidates whose combined probability reaches a threshold. Usually only one of the two is adjusted. ## More articles [Core Concept · Token ### What is a token in AI and how is it counted? 15 Sep 2026 · 2 min](https://www.qanatone.com/en/nedir/token-nedir/)[Marketing · Turkey ### Digital marketing in Turkey: the market in numbers 15 Sep 2026 · 2 min](https://www.qanatone.com/en/nedir/turkiye-dijital-pazarlama/)[Guide · Free Tools ### Free AI tools: what is available and what are the limits? 15 Sep 2026 · 1 min](https://www.qanatone.com/en/nedir/ucretsiz-yapay-zeka/)[Architecture · Vector Database ### What is a vector database? 15 Sep 2026 · 2 min](https://www.qanatone.com/en/nedir/vektor-veritabani-nedir/)[Model Type · VLM ### What is a vision-language model (VLM)? 15 Sep 2026 · 2 min](https://www.qanatone.com/en/nedir/vlm-nedir/)[Prompting · Zero-shot ### What is zero-shot prompting? 15 Sep 2026 · 2 min](https://www.qanatone.com/en/nedir/zero-shot-nedir/)[Core Concept · LLM ### What are large language models (LLMs) and how do they work? 12 Sep 2026 · 6 min](https://www.qanatone.com/en/nedir/buyuk-dil-modelleri-nedir/)[Architecture · RAG ### What is RAG (retrieval-augmented generation)? 12 Sep 2026 · 2 min](https://www.qanatone.com/en/nedir/rag-nedir/)