Infrastructure Stack Complexity
vLLM is typically deployed within Kubernetes or Ray infrastructure. For teams without existing K8s expertise, this adds significant complexity.
Comparison • SSH vs Kubernetesrbee vs vLLM:
rbee vs vLLM:
SSH vs Kubernetes
vLLM is an excellent high-performance inference engine, typically deployed within Kubernetes or Ray infrastructure. rbee is a multi-machine orchestration layer with SSH-based deployment. Choose based on your environment: existing K8s stack or simple SSH deployment.
- SSH deployment (5 minutes)
- No Kubernetes required
- Heterogeneous hardware
The Challenge
Infrastructure Complexity
vLLM is designed as a high-performance engine for infrastructure stacks, which can be complex for simpler deployments.
Feature Comparison
rbee vs vLLM: Side-by-Side
See how rbee and vLLM compare across key features.
✓Supported✗Not supported~Partial/ExperimentalvLLM offers slightly better raw performance but requires significant DevOps expertise. rbee prioritizes ease of deployment and heterogeneous hardware support.
| Feature | rbee | vLLM |
|---|---|---|
| Deployment method | SSH (5 minutes) | Kubernetes (weeks) |
| Multi-machine orchestration | Via K8s | |
| Heterogeneous hardware | NVIDIA only | |
| Apple Silicon support | ||
| AMD ROCm support | Experimental | |
| OpenAI-compatible API | ||
| Kubernetes required | ||
| User-scriptable routing | ||
| Setup complexity | Low (SSH only) | High (K8s + Helm) |
| Performance | High | Very High |
| GDPR compliance | ||
| License | GPL-3.0 + MIT | Apache 2.0 |
| Best for | Homelabs, startups, quick deployments | Large enterprises with K8s expertise |
The Solution
rbee: SSH-Based Multi-Machine Orchestration
Orchestration layer with SSH deployment and heterogeneous hardware support.
When to Choose
Which One is Right for You?
Choose based on your infrastructure and team.
FAQ
Common Questions
Everything you need to know about rbee vs vLLM.
Deployment
Technical
General
Ready for Multi-Machine Orchestration?
See how rbee handles SSH-based deployment across heterogeneous hardware.