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AI Glossary

What is Inference (AI)?

The process of an AI model generating outputs from inputs (vs. training).

By Council Research TeamUpdated: Jan 27, 2026

Definition

Inference is when a trained AI model processes new inputs and generates outputs. It's what happens when you send a message to ChatGPT and get a response. Inference costs (per token) are what you typically pay for when using AI APIs.

Examples

1Sending a prompt to GPT-4
2Getting a response from Claude
3Running a local LLM

Why It Matters

Inference speed and cost determine how practical AI is for different applications.

Related Terms

Large Language Model (LLM)

An AI system trained on vast text data to understand and generate human-like text.

Token (AI)

A chunk of text (roughly 4 characters or 3/4 of a word) that AI models process.

Latency (AI)

The delay between sending a prompt and receiving the first response token.

Common Questions

What does Inference (AI) mean in simple terms?

The process of an AI model generating outputs from inputs (vs. training).

Why is Inference (AI) important for AI users?

Inference speed and cost determine how practical AI is for different applications.

How does Inference (AI) relate to AI chatbots like ChatGPT?

Inference (AI) is a fundamental concept in how AI assistants like ChatGPT, Claude, and Gemini work. For example: Sending a prompt to GPT-4 Understanding this helps you use AI tools more effectively.

Related Use Cases

Best AI for Coding

Best AI for Business

AI Models Using This Concept

ClaudeClaudeChatGPTChatGPTGeminiGemini

See Inference (AI) in Action

Council lets you compare responses from multiple AI models side-by-side. Experience different approaches to the same prompt instantly.

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