---
title: Embedding models
---

## Overview

Mem0 offers support for various embedding models, allowing users to choose the one that best suits their needs.

<CardGroup cols={3}>
    <Card title="OpenAI" href="#openai"></Card>
    <Card title="Ollama" href="#ollama"></Card>
</CardGroup>

> When using `Qdrant` as a vector database, ensure you update the `embedding_model_dims` to match the dimensions of the embedding model you are using.

## OpenAI

To use OpenAI embedding models, set the `OPENAI_API_KEY` environment variable. You can obtain the OpenAI API key from the [OpenAI Platform](https://platform.openai.com/account/api-keys).

Example of how to select the desired embedding model:

```python
import os
from mem0 import Memory

os.environ["OPENAI_API_KEY"] = "your_api_key"

config = {
    "embedder": {
        "provider": "openai",
        "config": {
            "model": "text-embedding-3-large"
        }
    }
}

m = Memory.from_config(config)
m.add("I'm visiting Paris", user_id="john")
```

## Ollama

You can use embedding models from Ollama to run Mem0 locally.

Here's how to select it:

```python
import os
from mem0 import Memory

os.environ["OPENAI_API_KEY"] = "your_api_key"

config = {
    "embedder": {
        "provider": "ollama",
        "config": {
            "model": "mxbai-embed-large"
        }
    }
}

m = Memory.from_config(config)
m.add("I'm visiting Paris", user_id="john")
```