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Inference

Industry Definition Set • Entity Resolution Path: /glossary/inference

Quick Answer / TL;DR

The process of running a trained ML model to generate predictions or outputs from input data, the primary operation of LLMs in production.

Key Takeaways

  • Running a trained model to generate outputs.
  • Autoregressive for LLMs: one token at a time.
  • Can be local (Ollama) or remote (API).
  • Primary cost and latency consideration in AI systems.
Definitive Statement: The process of running a trained ML model to generate predictions or outputs from input data, the primary operation of LLMs in production.

Technical Context & Protocol Usage

Detailed Explanation
Inference is the 'forward pass' of a neural network: given input tokens, the model predicts the next token (or sequence of tokens). For LLMs, this happens autoregressively, generating one token at a time. In MCP contexts, inference occurs when the LLM decides which tool to call, generates the tool arguments, or produces a final response. Inference can run locally (Ollama, LM Studio) or remotely (OpenAI, Anthropic APIs).

Format & Payload Metadata

Format: Input tokens -> model forward pass -> output tokens

Latency: First token: 200ms-2s; subsequent tokens: 10-100ms each

Real-World Implementation Use Case

An MCP client sends a user prompt to the LLM for inference, receives a tool call decision, executes the tool, and sends the result back for another inference round.

M
MCPserver.in Engineering

Platform Team

Published: 2026-07-20
Updated: 2026-07-20

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MLA Style:

MCPserver.in Engineering. "Inference." MCPserver.in Knowledge Hub, 20 July 2026, mcpserver.in/glossary/inference.