| Overview |
Scalable AI compute platform built on Ray for deploying and fine-tuning large language models in production. |
A platform for running applications close to users worldwide with lightweight VMs and global edge deployment. |
| Pricing |
Pay-per-use ($$-$$$$) |
Pay_per_use (Pay-as-you-go from $0) |
| Key Features |
- Ray-based
- Auto-scaling
- Fine-tuning
- Managed endpoints
- Multi-model
- GPU clusters
|
- Global edge deployment
- Fly Machines
- PostgreSQL
- Redis
- Private networking
- Auto-scaling
- Docker support
- CLI tools
|
| Pros |
- Built on Ray
- Excellent scaling
- Production-grade
- Fine-tuning support
|
- Global distribution
- Good performance
- Docker-native
- Fair pricing
|
| Cons |
- Complex setup
- Higher learning curve
- Enterprise-focused pricing
|
- Complexity for simple apps
- Documentation gaps
- Debugging can be hard
- Smaller community
|
