> ## Documentation Index
> Fetch the complete documentation index at: https://wiki.platelunchcollective.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Temperature

> Temperature is a parameter that controls the randomness of an AI model's outputs during inference.

*Technical implementation* · *AI Search Infrastructure*

## Definition

Temperature is a parameter that controls the randomness of an AI model's outputs during inference. A low temperature produces more deterministic, predictable responses; a high temperature produces more varied and creative outputs. Most AI search systems operate at low temperatures to prioritize factual accuracy over creative variation.

## Why It Matters for AI Search

Temperature helps explain why AI search responses are relatively consistent across repeated queries — the systems are tuned for reliability, not variety. For brands, this means that a negative or inaccurate AI representation of a brand is not random — it reflects what the system is consistently most confident about. Fixing a bad AI representation requires changing the underlying signals the system draws from, not hoping for a different random output.

## Related Terms

<CardGroup cols={2}>
  <Card title="Inference" href="/ai-search-glossary/inference" />

  <Card title="Foundation model" href="/ai-search-glossary/foundation-model" />

  <Card title="Grounding" href="/ai-search-glossary/grounding" />

  <Card title="Hallucination mitigation" href="/ai-search-glossary/hallucination-mitigation" />

  <Card title="RAG" href="/ai-search-glossary/rag" />
</CardGroup>

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[AI SEO](https://www.platelunchcollective.com/services/ai-seo)  [AI Search Visibility Assessment](https://www.platelunchcollective.com/services/context-map)  [Context Map](https://www.platelunchcollective.com/services/context-map)