Installation

Download

Download the right file for your system from the GitHub Releases page:

Not sure which Mac? Apple menu > "About This Mac." If it says "Apple M1" (or M2/M3/etc.), pick Apple Silicon. If it says "Intel," pick Intel.

Which NVIDIA cards get GPU acceleration? RTX 30-series and newer (also RTX 40, RTX 50, and the A/H data-centre cards). The RTX 20-series, GTX 16-series and anything older are below the requirement of the FlashAttention kernels SwarmLLM ships, which is what makes attention fast.

An older card is not a problem — nothing breaks and there is nothing to configure. SwarmLLM checks the card when it starts, tells you in the log and on the dashboard that it is using the processor instead, and carries on. On Windows, running a model locally goes through Vulkan and works on any GPU regardless; the CUDA requirement applies to inference split across several machines.

To check your card: nvidia-smi --query-gpu=name,compute_cap --format=csv. A number of 8.0 or higher gets GPU acceleration.

Install & Run

Windows

Recommended — installer: double-click SwarmLLM-Setup.exe. It detects your GPU (NVIDIA / AMD / Intel) and installs the matching binary. If SmartScreen warns you, click More info > Run anyway.

Raw binary alternative: download swarmllm-windows-x86_64-gpu.zip (Vulkan + CUDA static) or swarmllm-windows-x86_64-cpu.zip (CPU-only fallback), extract, and run swarmllm.exe.

From PowerShell on a raw binary:

cd Downloads\swarmllm-windows-x86_64-gpu
.\swarmllm.exe run

macOS

cd ~/Downloads
tar xzf swarmllm-macos-aarch64.tar.gz
cd swarmllm-macos-aarch64
chmod +x swarmllm
./swarmllm run

Note: macOS aarch64 binaries are compile-validated and exercised in CI (test + clippy on macos-15); integration tests stay Linux-only for now. Intel Mac users should build from source.

Where you put it matters on a Mac. Keep SwarmLLM in a folder you own — anywhere under your home folder, as in the commands above. Folders like /Applications need administrator rights, and SwarmLLM cannot then replace its own binary, so it will tell you an update is available and decline to install it. Nothing else about it changes; move the file and updates work by themselves.

First launch: "cannot be opened because it is from an unidentified developer." The binaries are not yet signed with an Apple developer certificate, so Gatekeeper stops the first run of anything downloaded in a browser. Either open System Settings > Privacy & Security and click Open Anyway, or remove the quarantine flag the browser added:

xattr -d com.apple.quarantine swarmllm

Downloading with curl avoids it entirely — the quarantine flag is set by the browser, not by macOS in general — and it is a one-time thing per download, not something that recurs on every update (confirmed on a Mac mini M4, 2026-09-03).

Linux

cd ~/Downloads
tar xzf swarmllm-linux-x86_64.tar.gz
cd swarmllm-linux-x86_64
chmod +x swarmllm
./swarmllm run

Docker

The fastest way to get running on any Linux server:

# 1. Get the compose file and example env
curl -LO https://raw.githubusercontent.com/enapt/SwarmLLM/main/docker-compose.yml
curl -LO https://raw.githubusercontent.com/enapt/SwarmLLM/main/.env.example

# 2. Configure (add API keys, change ports, etc.)
cp .env.example .env
nano .env

# 3. Start
docker compose up -d

For NVIDIA GPU support (requires NVIDIA Container Toolkit):

docker compose --profile gpu up -d

Pre-built images on GHCR:

Data is persisted in Docker volumes. Model shards are stored in the swarmllm-models volume (or bind-mount a host directory via SWARMLLM_MODELS_DIR in .env).

View logs with docker compose logs -f. The API key is printed on first startup.

Cargo Install

Requires Rust 1.90+:

cargo install --git https://github.com/enapt/SwarmLLM.git --tag v0.3.14-alpha
swarmllm run

Building from Source

git clone https://github.com/enapt/SwarmLLM.git
cd SwarmLLM
cargo build --release
./target/release/swarmllm run

For CUDA GPU support:

cargo build --release --features candle-cuda

For Apple Silicon: the default build runs on CPU. A Metal-accelerated build is on the roadmap but not yet implemented (no metal Cargo feature exists yet); until then, use the default cargo build --release.

Open the Dashboard

Once running, open http://localhost:8800 in your browser. The setup wizard will walk you through initial configuration.