SilentSwarm or Exo?¶
Choose Exo if your machines are Macs on one network: it is built for them and it is far easier to start. SilentSwarm is for NVIDIA GPUs on Linux, machines in different places, or fine-tuning.
Checked against Exo's own documentation on 2026-11-05. Projects change, so check their current pages too. "Not documented" means we did not find it in what we read, not that it does not exist. We have not run either project against the other, so this page has no speed comparison.
| Exo | SilentSwarm | |
|---|---|---|
| Built for | Connecting your own devices into one AI cluster, mainly Macs | Serving and fine-tuning one model across mismatched machines you control |
| How a model is split | Pipeline or tensor sharding, with layers allocated by available memory | Contiguous layer stages, sized to each card's memory and speed |
| Hardware | Apple Silicon first. Its platform notes list Linux CUDA as planned | Linux with NVIDIA GPUs |
| Fine-tuning | Not documented | LoRA fine-tuning across the same split |
| API and interface | OpenAI, Claude and Ollama-style APIs, and a dashboard | OpenAI-compatible API and a web interface |
| Network | Same network or Thunderbolt, with automatic discovery. Across the internet is not documented | Workers connect out to your own coordinator: direct links where possible, its relay otherwise, across buildings and routers |
| Encryption between machines | Not stated in the pages we read | None of its own between machines. A WireGuard mesh encrypts traffic when it is up |
| Licence | Apache-2.0, open source | Source not public, terms agreed during the evaluation |
| Status | Actively developed; last GitHub release 2026-04-23 | In pre-evaluation |
Where Exo is the better choice¶
- Macs. Installing on Apple Silicon is a download, and we do not run on them at all.
- Tensor parallelism and RDMA over Thunderbolt 5, which can speed up one model across fast local links. SilentSwarm uses pipeline stages, which do not.
- Open source, under Apache-2.0.
- Size of the community, with far more users to learn from.
Where SilentSwarm fits¶
- Your GPUs are NVIDIA cards on Linux.
- The machines are not on one network.
- You want to fine-tune a model, not only chat with it.
SilentSwarm has gaps of its own: no sandbox, and no encryption of its own between machines or at rest. Data and security lists them, and our benchmarks show what it does on old cards.
Sources¶
SilentSwarm is in pre-evaluation. We are looking for companies, institutions and individuals who want to try it on their own machines: Apply for the evaluation.