n8n’s built-in OpenRouter support is one node: the OpenRouter Chat Model, a sub-node that gives an AI Agent any chat model available through your OpenRouter account. There is no built-in OpenRouter app node for plain workflow steps and no built-in OpenRouter embeddings node, and those are the gaps most OpenRouter community nodes fill, along with prompt caching, reasoning and token reporting. This guide covers the built-in node (from n8n’s documentation) and the most used OpenRouter community packages (from our own npm data).
Quick comparison
| Built-in OpenRouter Chat Model | OpenRouter community nodes | |
|---|---|---|
| Type | Sub-node: the model for an AI Agent or other AI root node | Standalone nodes, chat model sub-nodes or embeddings sub-nodes, depending on the package |
| Embeddings | Not built in | Several embeddings packages |
| Credential | OpenRouter API key | Usually an OpenRouter API key (see each README) |
| Comes with n8n | Yes | No, installed as a community package |
Step 1: get an OpenRouter API key
- Log in to OpenRouter or create an account.
- Open your API keys page.
- Select Create new secret key and, if you like, name it.
- Copy the key into the n8n OpenRouter credential as the API Key.
The built-in OpenRouter Chat Model
Use it to give an AI Agent a model through OpenRouter. n8n loads the Model list from OpenRouter, so you only see the models your account can use. Options:
- Frequency Penalty: higher values make the model less likely to repeat itself.
- Maximum Number of Tokens: the completion length.
- Response Format: Text or JSON. JSON makes the model return valid JSON.
- Presence Penalty: higher values make the model more likely to talk about new topics.
- Sampling Temperature: higher values give more varied output, with a higher risk of hallucinations.
- Timeout (milliseconds) and Max Retries.
- Top P: lower values ignore less probable options.
n8n notes that OpenRouter’s API is compatible with OpenAI’s, and points to LangChain’s OpenAI documentation for more detail.
OpenRouter community nodes
Our OpenRouter hub lists 25 packages that pass our quality rule, with 2,300 npm downloads a week between them. The most downloaded, with the description each author gives on npm (weekly npm downloads as of 27 October 2026):
| Package | Weekly downloads | Author’s description |
|---|---|---|
| n8n-nodes-openrouter | 667 | A node for OpenRouter API integration |
| n8n-nodes-openrouter-official | 189 | A multimodal action node, embeddings, a reranker and a prompt cache chat model |
| n8n-nodes-openrouter-token-telemetry | 152 | Chat model that reports cached input, billable input, reasoning tokens and cache hit ratio |
| n8n-nodes-openrouter-cache | 96 | Chat model with prompt caching |
| @jayabraga/n8n-nodes-openrouter-reasoning | 91 | Chat model with silent reasoning output |
| n8n-nodes-openrouter-embeddings | 84 | Embeddings sub-node for models from several providers |
| n8n-nodes-openrouter-reasoning | 77 | Chat model with reasoning effort support |
| n8n-nodes-openrouter-embed | 75 | Embeddings sub-node for models from several providers |
| n8n-nodes-openrouter-selector | 74 | Picks an OpenRouter model by task, budget and benchmarks |
From the descriptions, the packages fall into four groups:
- Standalone OpenRouter nodes (n8n-nodes-openrouter, the multimodal action node in openrouter-official) for using OpenRouter as a normal workflow step, without an AI Agent.
- Embeddings sub-nodes (openrouter-embeddings, openrouter-embed, and openrouter-official) for vector stores, which the built-in nodes don’t cover for OpenRouter.
- Chat model variants with prompt caching, reasoning settings or full token usage reporting.
- Model selection: openrouter-selector picks a model for you based on task and budget.
Read each README for setup and supported settings, and check its node page here for the latest release and, where it has one, its GitHub repository for open issues.
How to choose
- An AI Agent that should use a model through OpenRouter: the built-in OpenRouter Chat Model.
- A plain OpenRouter call as a workflow step: a standalone community node such as n8n-nodes-openrouter.
- OpenRouter embeddings for a vector store: one of the embeddings packages.
- Prompt caching, reasoning control or cost tracking: compare the chat model variants’ READMEs.
To install a package on a self-hosted instance, an owner or admin enters its npm name in Settings > Community Nodes; full steps are in How to Install n8n Community Nodes. On n8n Cloud only verified community nodes can be installed, see Verified vs Unverified n8n Community Nodes. Related: OpenAI in n8n, Claude in n8n and DeepSeek in n8n.
FAQ
Does n8n support OpenRouter without community nodes?
Yes, through the built-in OpenRouter Chat Model, which gives an AI Agent any chat model your OpenRouter account can use.
Can I use OpenRouter in n8n without an AI Agent?
Not with the built-in node, which is a sub-node. Community packages such as n8n-nodes-openrouter add a standalone node. OpenRouter’s API is OpenAI-compatible, so n8n’s docs also point to OpenAI-style setup for details.
Does n8n have OpenRouter embeddings?
Not built in. Community packages such as n8n-nodes-openrouter-embeddings add an embeddings sub-node.
What is the most used OpenRouter community node?
n8n-nodes-openrouter, with 667 weekly npm downloads on 27 October 2026.
