# Source: https://docs.fireworks.ai/fine-tuning/deploying-loras.md

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.fireworks.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Deploying Fine Tuned Models

> Deploy one or multiple LoRA models fine tuned on Fireworks

After fine-tuning your model on Fireworks, deploy it to make it available for inference.

<Note>
  You can also upload and deploy LoRA models fine-tuned outside of Fireworks. See [importing fine-tuned models](/models/uploading-custom-models#importing-fine-tuned-models) for details.
</Note>

## Single-LoRA deployment

Deploy your LoRA fine-tuned model with a single command that delivers performance matching the base model. This streamlined approach, called live merge, eliminates the previous two-step process and provides better performance compared to multi-LoRA deployments.

### Quick deployment

Deploy your LoRA fine-tuned model with one simple command:

```bash  theme={null}
firectl deployment create "accounts/fireworks/models/<MODEL_ID of lora model>"
```

<Check>
  Your deployment will be ready to use once it completes, with performance that matches the base model.
</Check>

## Multi-LoRA deployment

If you have multiple fine-tuned versions of the same base model (e.g., you've fine-tuned the same model for different use cases, applications, or prototyping), you can share a single base model deployment across these LoRA models to achieve higher utilization.

<Warning>
  Multi-LoRA deployment comes with performance tradeoffs. We recommend using it only if you need to serve multiple fine-tunes of the same base model and are willing to trade performance for higher deployment utilization.
</Warning>

### Deploy with CLI

<Steps>
  <Step title="Create base model deployment">
    Deploy the base model with addons enabled:

    ```bash  theme={null}
    firectl deployment create "accounts/fireworks/models/<MODEL_ID of base model>" --enable-addons
    ```
  </Step>

  <Step title="Load LoRA addons">
    Once the deployment is ready, load your LoRA models onto the deployment:

    ```bash  theme={null}
    firectl load-lora <FINE_TUNED_MODEL_ID> --deployment <DEPLOYMENT_ID>
    ```

    You can load multiple LoRA models onto the same deployment by repeating this command with different model IDs.
  </Step>
</Steps>

### When to use multi-LoRA deployment

Use multi-LoRA deployment when you:

* Need to serve multiple fine-tuned models based on the same base model
* Want to maximize deployment utilization
* Can accept some performance tradeoff compared to single-LoRA deployment
* Are managing multiple variants or experiments of the same model

## Next steps

<CardGroup cols={2}>
  <Card title="On-Demand Deployments" href="/guides/ondemand-deployments" icon="rocket">
    Learn about deployment configuration and optimization
  </Card>

  <Card title="Import Fine-Tuned Models" href="/models/uploading-custom-models#importing-fine-tuned-models" icon="upload">
    Upload LoRA models fine-tuned outside of Fireworks
  </Card>
</CardGroup>