LlamaForge
LlamaForge is a graphical control panel for llama.cpp. It builds llama.cpp for your machine, keeps it current with upstream, discovers models that fit your hardware, tunes every server parameter per model, and runs it — all from a browser instead of hand-editing models.ini and long llama-server command lines.
LlamaForge contains no llama.cpp source code. The backend (backend/server.py, pure Python standard library) proxies llama.cpp's own router API, edits models.ini, and shells out to git, cmake, nvidia-smi, and the platform package manager. It also drives vLLM as a second, optional backend for full-precision and safetensors models.
Who it is for
LlamaForge is built for people who want llama.cpp's speed and control but would rather not memorize flags, edit config files by hand, or babysit build commands. It assumes you are comfortable running a setup script once and building llama.cpp for your machine — both are guided from the dashboard.
Windows with an NVIDIA GPU is the primary target (CPU-only also works). Linux (NVIDIA/CPU) and macOS (Apple Silicon, Metal) are supported as an early preview — the same dashboard, launched with bootstrap.sh instead of bootstrap.ps1.
If you want a zero-config, double-click installer with no compile step, LM Studio, Ollama, or Jan will get you running faster. LlamaForge trades that convenience for direct, per-model control over the real llama.cpp server.
Architecture
LlamaForge runs two local HTTP services:
| Component | Default address | Role |
|---|---|---|
| Dashboard (panel) | http://127.0.0.1:8090 | The LlamaForge backend and web UI — Models, Stats, Discover, Build, Setup tabs. Always binds to 127.0.0.1 only. |
| Router | http://127.0.0.1:8080 | llama.cpp's own server process, started by LlamaForge with --models-preset models.ini. Serves the OpenAI-compatible API and llama.cpp's chat UI. |
Both ports, along with the bind address, are configured by the panel_port, router_port, and router_host keys in config.json (defaults 8090, 8080, and 127.0.0.1). The router's bind address can be widened to 0.0.0.0 from the Setup tab's Network Access panel to reach it from other devices on your LAN; the dashboard itself never leaves 127.0.0.1.
Clients — curl, an OpenAI SDK, or any OpenAI-compatible chat client — talk to the router, not the dashboard. The dashboard's job is configuration: it writes model presets into models.ini, starts and stops the router, and reads back the router's own metrics endpoint for the Stats tab.
When vLLM is enabled (Windows only, via WSL2), it runs as a third process inside WSL and is bridged back to a Windows localhost port (vllm_port in config.json); it shares the same Models list, Discover tab, and stats as llama.cpp.
Where to go next
Start with Installation to get the bootstrap script running on your platform, then First Run for the onboarding wizard and auto-tune.