Every developer we know has the same complaint. The cloud coding assistants are fast, but they send your code to someone else's server. The local alternatives are private, but getting them running feels like a weekend project. We wanted something different: a local AI app that just works.
The problem we kept hitting
We tried Ollama, LM Studio, Jan, GPT4All, and everything in between. Each one had a piece of what we wanted, but none of them put it together. Some needed terminal commands. Some made us hunt through Hugging Face manually. Some had no idea whether our GPU could even load the model we picked. We kept bouncing between tools instead of getting work done.
The moment that broke us: downloading a 40 GB model only to realize our GPU did not have enough VRAM. There had to be a better way to match models to hardware.
What we set out to build
We wanted an app that felt like a modern desktop product, not a science experiment. It had to scan our hardware, recommend the right model, download it with one click, and run fully offline. Then it had to go further and actually help us code.
- One installer, no dependencies, no terminal.
- Hardware wizard that knows your GPU, VRAM, RAM, and CPU.
- One-click Hugging Face downloads.
- Autonomous coding agent that edits files across your project.
- Team and Enterprise features for real engineering workflows.
Local first, not cloud lite
We did not want a thin wrapper around an API. We wanted real local inference. Your prompts, your code, and your models stay on your machine. No telemetry. No token limits. No surprise bills. Even the document parser runs locally, so PDFs and DOCX files never leave your system.
“The best AI assistant is the one that never sees your code leave the building.”
OpenLLM Studio Team
What is in the app today
OpenLLM Studio is now a complete local AI workstation. It runs on Windows, macOS, and Linux. It auto-detects CUDA, Vulkan, and Metal backends. It ships with a model library, a hardware wizard, a chat interface, an autonomous coding agent, an integrated code editor, and a terminal. Team features include shared endpoints, Git bridge, RBAC, and usage metering.
What comes next
We are expanding model support, improving the coding agent's planning and verification, adding local RAG and document chat, and deepening team collaboration features. If you believe local AI should be powerful and simple, we built this for you.
Download OpenLLM Studio free and see what local AI can do when it is actually built for developers.