Early access · runs on your machine

Ask your GPU clusteranything.

DeepLM Ops is a local, read-only assistant for GPU and Slurm questions. See what's free, why a job is waiting, and what will fit, in plain English. Run it with Docker in minutes.

Try itOpen-source tools

Install on Windows · macOS · Ubuntu

127.0.0.1:8090
The DeepLM Ops chat interface: a workspace sidebar, a chat panel and a side panel showing the connected model and recent sessions.

Quick start

Running in minutes.

DeepLM Ops runs on your own machine through Docker. It is read-only, so it can answer questions about your cluster but never change it. The first start downloads the model once (2.55 GiB). If the model runs on the CPU inside Docker, give Docker at least 8 GB of memory.

Your system
  1. 01

    Install Docker on Windows

    Already have Docker? Skip to step 2.

    PowerShell (Admin), then restart
    wsl --install
    PowerShell
    winget install -e --id Docker.DockerDesktop

    Docker Desktop runs on WSL 2. Start Docker Desktop once after installing.

    Full Windows guide
  2. 02

    Get access

    Accept the DeepLM GitHub org invite, then create a classic token with only read:packages. Fine-grained tokens don't work with ghcr.io.

    Create the token
    Log in
    docker login ghcr.io -u <your-github-username>

    Paste the token at the Password prompt.

  3. 03

    Pull the image

    Docker picks the right build for your machine: amd64 for Intel and AMD, CPU-only arm64 for Apple silicon.

    Pull
    docker pull ghcr.io/deeplm/dlm-ops-dev:0.2.0-rc.4

    0.2.0-rc.4 is a release candidate for testing: the first image with the new platform UI.

  4. 04

    Run it

    Run
    docker run -d --name dlm-ops -p 127.0.0.1:8090:8090 -v dlm-ops:/var/lib/dlm-ops --read-only --tmpfs /tmp --tmpfs "/run/dlm:uid=1000,gid=1000,mode=0700" --cap-drop ALL --security-opt no-new-privileges --pids-limit 256 --restart unless-stopped ghcr.io/deeplm/dlm-ops-dev:0.2.0-rc.4 demo

    The demo cluster is a recorded sample campus cluster with made-up jobs; questions about this machine still use your real machine. Switch to “My machine” to use no demo cluster. Add an NVIDIA GPU with the checkbox above.

  5. 05

    Sign in and try it

    Run the command below and open the http://127.0.0.1:8090/#token=… link once it says “model ready”.

    Logs
    docker logs dlm-ops

    That link is a password and works until the container restarts. Don't paste it into chats, issues or screen shares. docker restart dlm-ops makes a new one.

    Then ask it:

    • Why is my job 5102 still pending?
    • Why did 5098 fail?
    • Is anyone wasting a GPU on gpu03?
    • Will Llama 3.1 8B fit on my GPU for inference with 8k context?
Step-by-step guides:WindowsmacOSUbuntuAll docs

Stop it with docker rm -f dlm-ops. Hit a bug or a wrong answer? Send us the question you asked and a screenshot (without the sign-in link).

Products

Built for people who run GPU clusters.

DeepLM Ops answers your questions. Insights and Baseline show you the numbers. All of them run on your own machines.

Release candidate

DeepLM Ops

A local, read-only assistant for GPU and Slurm questions. Ask why a job is pending, who is using a GPU, or whether a model fits. Runs on your own machine with Docker.

Read the docs
Free & open source

DeepLM Insights

Real-time Grafana dashboards and Prometheus metrics for HPC and Slurm GPU clusters. Track job performance, GPU utilization, power and checkpoint efficiency.

Insights docs
Free & open source

DeepLM Baseline

Benchmark your GPU cluster's real performance in one run: compute, interconnect and network scaling, checked against vendor specifications.

Baseline docs

More:Product overviewGPU cost calculatorAbout DeepLM