Open-source LLM infrastructure management

Your hardware. Your models. One control plane.

LLM Systems Manager is a complete, self-hosted operations platform for LLM infrastructure: monitoring, remote control, tuning, routing, and alerting for llama.cpp, vLLM, and LM Studio, all in one place.

quick start
$ bash <(curl -fsSL https://raw.githubusercontent.com/llmsyscore/llm-systems-manager/main/tools/installer/install.sh)

One command installs the full stack. The installer is interactive. It handles prerequisites, InfluxDB, TLS, and agents, and never starts a service without you.

AGPL-3.0 open source Linux & macOS agents Script / .deb / .rpm / Docker / Homebrew
Integrates llama.cpp vLLM LM Studio stable-diffusion.cpp OpenClaw telemetry

Architecture

Three small services, one platform

A lightweight agent on every host, a manager as the control plane, and a standalone alarm engine, with TLS/mTLS on every connection.

agent · per host

One cross-platform binary for Linux and macOS. Auto-detects what each box runs and reports host, GPU, PSU, and inference-server metrics.

  • llama.cpp / vLLM / LM Studio
  • stable-diffusion.cpp
  • GPU · PSU · UPS · cooling

manager · control plane

The dashboard, the OpenAI-compatible gateway, model library and profiles, Autopilot routing, users and roles, backups.

  • web dashboard + admin console
  • /v1 inference gateway
  • Model Autopilot

alarm engine

Stores every sample, evaluates threshold and anomaly rules, and collapses bursts of related issues into single incidents.

  • InfluxDB history
  • email · toast · webhook · Discord
  • offline buffer + replay

What's inside

Everything self-hosted inference needs, in one place

From a single Mac to a rack of GPU hosts, with the same dashboard, gateway, and alerting.

Model Autopilot

Configure which models should be available. Autopilot places them on hardware that can run them, brings them back when a host drops, and automatically scales with the demand.

OpenAI-compatible gateway

One endpoint fronts every backend. A merged model catalog, per-model pinning, pooling, and failover to a live host when one goes down. Streaming included, and apps see one stable URL.

Telemetry & alerting

LLM-aware metrics down to slots, tokens/sec, and KV cache, plus a standalone alarm engine with threshold and anomaly rules that collapses bursts into single incidents.

Energy & cost intelligence

Measures what inference actually costs in $/Mtok against your electricity price, with savings versus hosted-API pricing and per-host performance profiles that reduce power draw and noise when a system is idle.

Benchmarking & autotuning

Run throughput benchmarks across your whole model library, and let the autotuner search out the best context and slot configuration for each model on its own hardware.

Model management

Pull models straight from Hugging Face, prune files to reclaim disk, and keep named config profiles per model; switching profiles reloads the model in one click.

Remote control

Start, stop, hot-swap models, edit configs, tail logs, or open an in-browser terminal for any host, from one page. A Discord bot exposes the same controls as slash commands.

GPU Report Card

A standardized benchmark that produces one shareable card: time-to-first-token, throughput, tokens/joule, and measured $/Mtok, comparable across providers and machines.

Screenshots

Inside the dashboard

Captured from a live deployment. Every view shown here is part of the product.

Installation

Install it your way

The script installer is the preferred path. The alternatives cover specific setups.

Script installer preferred

One interactive command covers everything: full stack, split installs, agents, offline installs, and updates.

Quickstart →

Native packages

.deb and .rpm packages for hosts standardized on apt or dnf package management.

Releases →

Docker Compose

A containerized control plane: manager, alarm engine, and InfluxDB, with agents installed on hosts.

Compose guide →

Homebrew

Agents on macOS install straight from the tap, with signed release binaries.

llmsyscore/homebrew-tap →

Local hardware. Private data. Full control.

Run models on hardware you own, keep every prompt and metric on your network, and manage it all from one dashboard. Free and open source under AGPL-3.0.