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

# Modal Integration

> Use Modal serverless GPUs with Hubify Labs for on-demand compute.

# Modal Integration

<Note>
  Modal integration is currently in development. This page describes the planned functionality. RunPod is the recommended compute provider today.
</Note>

[Modal](https://modal.com) provides serverless GPU functions that run on-demand and bill per second. When available, Modal will complement RunPod by handling short-lived, bursty workloads.

## Planned Features

### Serverless GPU Functions

Instead of managing pods, deploy Python functions that run on GPU infrastructure:

```python theme={null}
# hubify_functions.py
import modal

app = modal.App("hubify-lab")

@app.function(gpu="H100", timeout=600)
def run_analysis(experiment_config: dict):
    """Runs on an H100 GPU, billed per second of execution."""
    import cobaya
    # Your analysis code here
    return results
```

### When to Use Modal vs RunPod

| Use Case                   | Recommended | Why                                     |
| -------------------------- | ----------- | --------------------------------------- |
| Long MCMC chains (hours)   | RunPod      | Persistent pod is cheaper for long runs |
| Quick analysis (\< 10 min) | Modal       | Per-second billing, no pod overhead     |
| Figure generation          | Modal       | Short task, instant cold start          |
| Batch inferences           | Modal       | Auto-scales across multiple GPUs        |
| Interactive debugging      | RunPod      | SSH access, persistent environment      |
| Training runs              | RunPod      | Stable long-running environment         |

### Auto-Routing

When Modal is available, the orchestrator will automatically route experiments to the most cost-effective provider:

```
Short task (< 10 min) → Modal (per-second billing)
Long task (> 10 min) → RunPod (per-minute billing, cheaper at scale)
Bursty parallel tasks → Modal (auto-scaling)
```

## Planned Setup

```bash theme={null}
# Install Modal
pip install modal

# Authenticate
modal token new

# Connect to Hubify
hubify pod provider add modal --token $MODAL_TOKEN

# Deploy functions
hubify deploy functions --provider modal --file hubify_functions.py
```

## Planned Configuration

```bash theme={null}
# Set Modal as the default for short tasks
hubify pod config --short-task-provider modal

# Set the routing threshold
hubify pod config --modal-threshold 10m  # Tasks under 10 min → Modal

# View provider routing
hubify pod config --show-routing
```

## Current Status

Modal integration is planned for Q3 2026. In the meantime:

* Use **RunPod** for all GPU compute
* The transition will be seamless when Modal support ships
* Existing experiments will continue to work on RunPod
* The orchestrator will automatically start routing to Modal when configured

## Sign Up for Updates

To be notified when Modal integration is available:

```bash theme={null}
hubify notifications subscribe --feature modal-integration
```