TurboLLM

TurboLLM

  Run any local LLM engine, auto-tuned to your GPU — with a polished web UI
  and an OpenAI/Anthropic-compatible API.
  Bring your own llama.cpp fork. No compiling. No Electron. No Python. Point Claude Code at
  your own machine in one command — fully offline.

  = 22" />

  Source-available under FSL-1.1 — free for personal and
  internal business use; every release converts to Apache-2.0 two years after it ships.

That one command starts a local daemon, opens a browser UI, and serves your models over an
API any tool can talk to. TurboLLM is the performance & bleeding-edge layer for local
LLMs — built for people who today hand-compile forks and hunt forums for the right flags.
The speed is measured, not promised: 74.7 vs 61 t/s on the *same* official llama.cpp as
LM Studio — and 2.2× on forks it can't load (the numbers).

  📖 Full docs · what runs on your GPU · model picks → turbollm.dev

   one lightweight daemon -> any engine on your GPU" />

Contents

- Why TurboLLM
- Who this is for — and who it isn't
- Speed: TurboLLM vs LM Studio
- Features
- Live hardware monitoring
- Quick start
- ⭐ Bring any engine — the headline feature
- Run Claude Code on your own GPU
- Use it from any device on your network
- Command-line reference
- Configuration & data
- Requirements
- Privacy
- How TurboLLM compares
- Troubleshooting
- Develop from source
- Community
- License

Why TurboLLM

Local-LLM tools make two choices for you, and both cost you performance:

1. They pick the engine. LM Studio ships one blessed runtime; Ollama hides the engine
   entirely. The fastest community innovations — new quant formats, speculative decoding,
   low-bit KV cache — land in forks first, and you can't use them without compiling.
2. They don't tell you what speed to expect, and they…