orl 0.4: GPU pods, VM sizing, and spend in the OpenRelay CLI
Sep 26, 2026 · 3 min read
orl is the OpenRelay command-line tool. Version 0.4 runs your containers on whole GPUs, checks a VM's size against the fleet before launch, and shows what each VM costs while it runs.
Install and log in
brew install openrelayinc/tap/orl orl auth login
On Linux, install the .deb or .rpm from the release page. Already installed? Run orl upgrade.
Rent a GPU VM
orl ssh-keys create --name laptop --public-key "$(cat ~/.ssh/id_ed25519.pub)" orl ssh-keys list orl deploy trainer --ssh-key <key-id> --connect
orl deploy lists the GPU models with free capacity, asks for a model and count, and checks any --guest-mem-mb or --disk-gb you set against the fleet before it submits. --connect waits for the VM and opens an SSH session.
Run a container on a GPU
orl pods capacity list orl pods create --image pytorch/pytorch:2.5.1-cuda12.4-cudnn9-runtime \ --gpu-model-id <gpu-model-id> --ssh-key-ids <key-id> --volume-gb 100 orl vms metrics get <pod-id> --range 1h
A pod runs your image on whole GPUs, with SSH, an HTTP endpoint, and a /workspace volume that survives stop and start. Use a CUDA image on NVIDIA or a ROCm image such as rocm/pytorch on AMD, and read GPU utilization, memory, power, and temperature with vms metrics get.
Watch spend, stop billing
orl vms burn get <vm-id> orl usage daily get --days 7 orl vms stop <vm-id>
burn get shows a VM's hourly rate, the cost of its current session, and your runway. usage daily get splits daily spend into compute and inference, and vms stop stops the meter while keeping the disk.
Run batch inference
orl batches create --input-file requests.jsonl \ --endpoint /v1/chat/completions --priority expedited orl batches get <batch-id> orl files content get <output-file-id> -o results.jsonl
expedited gets a slot ahead of waiting standard batches and bills at the online rate. standard keeps the batch discount, and the Batch API is enabled per organization.
Give it to an agent
claude mcp add openrelay -- orl mcp serve
orl mcp serve exposes a core set of OpenRelay API calls as MCP tools. Widen it with --toolset vms, or add --read-only for an agent that can look but never change anything.
Rent a GPU from your terminal
Create an API key, then run orl auth login. The full reference is in the CLI docs.