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TOPIC OVERVIEW

langchain/Models

Connect LangChain to the language models that power your application's reasoning and responses.

15 QuestionsBeginnerHigh Priority ~10 min read

Models are the part of a LangChain application that generate text, understand instructions, decide what to do, or produce structured outputs. LangChain provides a common interface so applications can work with different model providers without rewriting the entire application around one API.

Choosing a model is not only about how smart it is. Cost, latency, context window, tool-calling support, structured output, reliability, and the type of task you are solving all affect which model makes sense.

What you'll walk away knowing

How models fit into a LangChain application
How chat models process messages
How model capabilities affect agent and tool workflows
How to choose models based on quality, cost, and latency
1How to initialise a model in langchain?Intermediate2List parameters we can use while creating a model instance.Intermediate3What are models?Intermediate4How can we use tools with model instances in langchain?Intermediate
All Topics
1
Basics
Models
Messages
2
Agents
Tools
Middleware
Memory
3
MCP
Multi Agents
Human in the loop
4
RAG
Context Engineering
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