Ohm Studio
One Click.
Any AI Model.
Deploy AI across multiple GPU servers without writing a single command. Built for people who use AI, not people who configure infrastructure.
Deploy AI across multiple GPU servers without writing a single command. Built for people who use AI, not people who configure infrastructure.
You're a researcher. A data scientist. A design student. You need Stable Diffusion running, or a Llama model for your thesis, or Whisper to transcribe interviews. But today, that means SSH, Docker, CUDA drivers, port forwarding, YAML configs, and praying nothing breaks.
Most people give up, or pay for expensive cloud GPUs that send their data overseas. There has to be a better way.
Ohm Studio turns your GPU infrastructure into something anyone can use. No CLI. No config files. No terminal. Just a clean web interface where you pick what you need and it runs.
Don't know how to configure a model? Byte walks you through it. Pick a template, and the AI assistant handles GPU allocation, VRAM checks, and container setup for you.
From clicking "Deploy" to a working endpoint. No waiting for builds, no dependency hell, no troubleshooting.
GPU monitoring, container management, user access control, health dashboards, audit logs. The entire infrastructure toolkit in one place.
Most GPU orchestrators break when you scale beyond a single machine. Ohm Studio was built from day one for multi-server clusters. The Worker-Master-User architecture means adding a new GPU server is as simple as plugging it in.
Your users never think about which server their model is running on. The Master handles it. Need more capacity? Add another Worker. That's it.
Not everyone running AI models is a DevOps engineer. Ohm Studio is designed for the people who actually need AI in their work, not the people who manage servers for a living.
Your built-in AI assistant that handles the hard parts. Deploy models, check GPU health, troubleshoot errors, manage containers. Just type what you need in plain language.
"Deploy Stable Diffusion on the server with the most free VRAM." Done. No manual lookup, no guessing which node has capacity.
Most GPU cluster tools assume you know Docker, Kubernetes, or at least a terminal. We don't.
Everything through a web interface. Your users never touch a terminal, ever.
Byte handles deployment, monitoring, and troubleshooting in natural language. No expertise needed.
Worker-Master architecture scales from 1 GPU to 100 servers. Just plug in new nodes.
On-premise only. Air-gap ready. Your data never leaves your facility.
Admins, researchers, students — each with proper permissions, quotas, and audit trails.
GPU monitoring, container management, health dashboards, diagnostics — all in one platform.
No cloud. No lock-in. No data leaks. Just your hardware, your models, your control.
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