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
Modal integration is currently in development. This page describes the planned functionality. RunPod is the recommended compute provider today.
Planned Features
Serverless GPU Functions
Instead of managing pods, deploy Python functions that run on GPU infrastructure: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:Planned Setup
Planned Configuration
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