Single Machine Design
Ollama is designed for single-machine use. If you have a gaming PC, Mac, and server, they can't work together.
Both make local LLM inference easy. The key difference: Ollama is designed for single-machine use, rbee orchestrates across multiple machines. Choose based on your hardware setup.
When you have multiple machines with GPUs, single-machine tools can only use one at a time.
See how rbee and Ollama compare across key features.
| Feature | rbee | Ollama |
|---|---|---|
| Multi-machine support | ||
| Heterogeneous hardware (NVIDIA + Apple + AMD) | Partial | |
| SSH-based deployment | ||
| OpenAI-compatible API | ||
| User-scriptable routing (Rhai) | ||
| Automatic load balancing | ||
| No single point of failure | ||
| GDPR compliance features | ||
| Setup time | 5 minutes | 2 minutes |
| Model marketplace | ||
| License | GPL-3.0 + MIT | MIT |
| Best for | Multi-GPU setups, homelabs, enterprises | Single machine, quick demos |
See the difference in multi-machine orchestration.
Limited to one machine at a time
Orchestrates across ALL your machines
| Metric | Before rbee | After rbee |
|---|---|---|
| GPU Utilization | Low | High |
| Machines Used | 1 | All |
| Setup Time | ~2 min | ~5 min |
Orchestrate across all your machines with heterogeneous hardware support.
Choose based on your hardware and needs.
Everything you need to know about rbee vs Ollama.
See how rbee handles multi-machine GPU orchestration with SSH-based deployment.