> For the complete documentation index, see [llms.txt](https://docs.n8n.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatanthropic.md).

# Anthropic Chat Model

{% hint style="info" %}
On n8n Cloud, you can use the Anthropic Chat Model node with [Gateway credits](https://app.gitbook.com/s/jm0ZYRpZIPWge2ZSiDYO/use-n8n-cloud/gateway-credits) instead of your own Anthropic API key. Select **Use Gateway credits** in the node's credential field to run the node without an Anthropic account.
{% endhint %}

Use the Anthropic Chat Model node to use Anthropic's Claude family of chat models with conversational agents[^1].

On this page, you'll find the node parameters for the Anthropic Chat Model node, and links to more resources.

{% hint style="info" %}
**Credentials**

You can find authentication information for this node [here](/integrations/builtin/credentials/anthropic.md).
{% endhint %}

{% hint style="info" %}
**Parameter resolution in sub-nodes**

Sub-nodes behave differently to other nodes when processing multiple items using an expression.

Most nodes, including root nodes, take any number of items as input, process these items, and output the results. You can use expressions to refer to input items, and the node resolves the expression for each item in turn. For example, given an input of five `name` values, the expression `{{ $json.name }}` resolves to each name in turn.

In sub-nodes, the expression always resolves to the first item. For example, given an input of five `name` values, the expression `{{ $json.name }}` always resolves to the first name.
{% endhint %}

## Node parameters <a href="#node-parameters" id="node-parameters"></a>

* **Model**: Select the model that generates the completion. Choose from:
  * **Claude**
  * **Claude Instant**

## Node options <a href="#node-options" id="node-options"></a>

* **Maximum Number of Tokens**: Enter the maximum number of tokens used, which sets the completion length.
* **Sampling Temperature**: Use this option to control the randomness of the sampling process. A higher temperature creates more diverse sampling, but increases the risk of hallucinations.
* **Top K**: Enter the number of token choices the model uses to generate the next token.
* **Top P**: Use this option to set the probability the completion should use. Use a lower value to ignore less probable options.
* **Prompt Caching**: Cache the system prompt, tool definitions, and conversation history between requests using [Anthropic prompt caching](https://docs.anthropic.com/en/docs/build-with-claude/prompt-caching). Choose **Disabled** (the default), **5 Minutes**, or **1 Hour**. The value sets how long cached content stays valid before it has to be written again.

## Templates and examples <a href="#templates-and-examples" id="templates-and-examples"></a>

[Browse Anthropic Chat Model node documentation integration templates](https://n8n.io/integrations/anthropic-chat-model) or [search all templates](https://n8n.io/workflows/)

## Related resources <a href="#related-resources" id="related-resources"></a>

Refer to [LangChains's Anthropic documentation](https://js.langchain.com/docs/integrations/chat/anthropic/) for more information about the service.

View n8n's [Advanced AI](/build/integrate-ai.md) documentation.

[^1]: AI agents are artificial intelligence systems capable of responding to requests, making decisions, and performing real-world tasks for users. They use large language models (LLMs) to interpret user input and make decisions about how to best process requests using the information and resources they have available.