llmman

Run any agent on any model.

Claude Code, Codex, OpenCode and friends, pointed at a model running on your own machine, or at any hosted provider, in one command.

llmman launch claude --model qwen3.8

That starts a local inference server, downloads a `llama.cpp` build matching your GPU, loads the model, and execs an agent against it.

Models are OCI images, so moving one takes no tooling you don't already have:

llmman transfer hf.co/unsloth/Qwen3.5-0.8B-GGUF docker.io/owner/model:latest

That copies from Hugging Face into your own registry directly, without a copy landing in your local store.

Why llmman?

• Provider agnostic. The same launch, run and list commands work against a local model or any hosted provider (--provider baseten, --provider groq, ...). One endpoint, one agent config, local or hosted.
• Registry agnostic. llmman run qwen3.8 pulls straight from Docker Hub; llmman run hf.co/org/model pulls straight from Hugging Face. Or package a model as a plain OCI artifact and push it to GHCR, quay, Harbor or a self-hosted mirror, then llmman run it from there. No curated library, no account with llmman, no gatekeeper.
• Vanilla everything. Upstream llama.cpp releases (or the llama-server already on your PATH), vllm and mlx-lm as-is, serving unmodified GGUF and safetensors files. No fork to wait on, no import step, no private blob format: the store is a standard OCI Image Layout that all can read.
• One-step transfer. Any source pull understands paired with any OCI registry