CLI Flags & Environment Variables

CLI Flags

Flag	Short	Description
`--port <PORT>`	`-p`	Listen port
`--data-dir <PATH>`	`-d`	Data directory
`--config <PATH>`	`-c`	Config file path
`--model <PATH>`	`-m`	Path to a GGUF model file
`--gpu-layers <N>`		Layers to offload to GPU
`--bootstrap <ADDR>`		Bootstrap peer address (repeatable)
`--shards <RANGE>`		Shard range for split inference (e.g., `"0-4"`)
`--verbose`	`-v`	Increase log verbosity (`-v`, `-vv`, `-vvv`)

Subcommands

Command	Description
`run`	Start the daemon (default if no subcommand)
`status`	Query running daemon status
`chat`	Interactive CLI chat with streaming
`bench`	Benchmark inference (tokens/sec, TTFT)
`peers`	List connected peers
`pool`	Device pool management (link your machines)
`test-split`	Test split inference locally (diagnostic)
`version`	Print version

`chat` Options

Flag	Default	Description
`--model-name <NAME>`	auto-detect	Model to chat with
`--system <TEXT>`	none	System prompt
`--max-tokens <N>`	`2048`	Max tokens per response
`--temperature <F>`	`0.7`	Sampling temperature

`bench` Options

Flag	Default	Description
`--model-name <NAME>`	auto-detect	Model to benchmark
`--prompt <TEXT>`	"Write a short essay..."	Benchmark prompt
`--max-tokens <N>`	`128`	Tokens to generate
`--iterations <N>`	`1`	Number of benchmark runs

`pool` Subcommands

Link your personal devices so credits are combined on one main machine.

Command	Description
`pool create --name "My Devices"`	Create a device group (this machine becomes the main device)
`pool invite-code`	Generate an 8-character invite code to share
`pool join <CODE>`	Link this device using a code from your main machine
`pool status`	Show linked devices, credits, and online status
`pool leave`	Unlink this device from the group

Example flow:

# Main device:
swarmllm pool create --name "My Devices"
swarmllm pool invite-code   # → A3F7K2M9

# On each other device:
swarmllm pool join A3F7K2M9

Note: This links YOUR own devices. It's different from connecting to the SwarmLLM network (which uses swarm:// peer addresses).

Environment Variables

Every config option can be set via SWARMLLM_ prefix:

Config Path	Environment Variable
`node.listen_port`	`SWARMLLM_NODE_LISTEN_PORT`
`node.data_dir`	`SWARMLLM_NODE_DATA_DIR`
`logging.level`	`SWARMLLM_LOGGING_LEVEL`
`inference.model_path`	`SWARMLLM_INFERENCE_MODEL_PATH`
`inference.gpu_layers`	`SWARMLLM_INFERENCE_GPU_LAYERS`

Example:

SWARMLLM_NODE_LISTEN_PORT=9000 SWARMLLM_LOGGING_LEVEL=debug ./swarmllm run

Provider API Keys via Environment

Cloud provider API keys use standard environment variable names:

Provider	Environment Variable
OpenAI	`OPENAI_API_KEY`
Anthropic	`ANTHROPIC_API_KEY`
DeepSeek	`DEEPSEEK_API_KEY`
Mistral	`MISTRAL_API_KEY`
Groq	`GROQ_API_KEY`
NVIDIA NIM	`NVIDIA_NIM_API_KEY`
Cerebras	`CEREBRAS_API_KEY`
SambaNova	`SAMBANOVA_API_KEY`
Fireworks	`FIREWORKS_API_KEY`
Together	`TOGETHER_API_KEY`
DeepInfra	`DEEPINFRA_API_KEY`
Moonshot/Kimi	`MOONSHOT_API_KEY`

These can also be placed in a .env file in your data directory:

# ~/.local/share/swarmllm/.env
OPENAI_API_KEY=sk-proj-...
DEEPSEEK_API_KEY=sk-...
NVIDIA_NIM_API_KEY=nvapi-...

The .env file is loaded at startup. It does not override existing environment variables or keys already configured via the dashboard/database. The dashboard settings UI shows "From .env" for keys loaded this way.

SwarmLLM Documentation