Requirements
What running Levirge Brain inside your own network needs: hardware by deployment size, the services around it, and the questions that size a deployment.
Brain is a set of containerised services with a message bus, durable storage and model endpoints behind them. The surprising part is how little hardware it needs: the models are the demanding component, and only one of them wants a GPU.
Hardware
Guidance by what you have, not by tier. Which inference model runs where is on model options.
| Your hardware | Embeddings | Reranking | Ingest models |
|---|---|---|---|
| Laptop or small server, no GPU | local (CPU) | cloud | cloud |
| Integrated GPU (Vega, Iris, Apple Silicon) | local | cloud | cloud |
| Workstation with a discrete GPU | local | local | local or cloud |
Running every inference model locally wants roughly 16 GB or more of VRAM to hold the ingest models concurrently. Without a discrete GPU, reranking is the one that has to move to a cloud endpoint — it is the one part of the system that genuinely needs the hardware. Everything else runs on commodity kit.
Services
- A NATS server with JetStream. One process, one command — and not optional: it is where the knowledge lives.
- An embeddings endpoint. Ollama is the cheapest local path; a cloud API works if you would rather not run one.
- Durable storage. The knowledge base is the asset; it needs to survive a host failure like any other system of record.
- Somewhere to terminate TLS and route traffic to the MCP endpoint.
What sizes a deployment
- Corpus size and growth — how many documents you hold, and how many arrive per week. Ingest is model-bound, so this drives model capacity before it drives disk.
- Concurrent agents — how many clients query and capture at once, and whether they are interactive or batch.
- Search volume — query embedding is cheap and flat; reranking is the part that scales with it.
- Network posture — connected, restricted egress, or genuinely air-gapped. Air-gapped changes updates and support, not just firewall rules.
- Who operates it — your team, ours, or shared. This decides what access we need and where the support boundary sits.
What does not change
The MCP endpoint, the tools and the client setup are identical to the hosted product — the install guides work against your own URL. Agents neither know nor care where Brain runs.
Next
Model options covers the four inference models and where each can run. For figures against your own numbers, register below with a rough scale — that is faster than any table.
Check your inbox
Confirm the subscription from the email we just sent and you're on the list.