Introducing Bare Metal: Dedicated GPU Servers with Maximum Control and Savings

AI teams and ML engineers need flexibility, performance, and cost efficiency—and RunPod's new Bare Metal offering delivers exactly that.

With Bare Metal, you can now reserve dedicated GPU servers for months or even years, ensuring consistent performance without the hassle of hourly or daily pricing. This means significant cost savings and a machine that’s entirely yours, with no virtualization layer getting in the way.

Why Choose RunPod’s Bare Metal?

✅ Full Hardware Control – Get direct access to the underlying server, run any software stack, install custom drivers, and configure the machine however you need.

✅ Deploy Without Limitations – Unlike containerized environments, Bare Metal lets you run Kubernetes, specialized AI frameworks, or any system-level tools that require full hardware access.

✅ No Resource Sharing – Your machine is 100% dedicated to your workloads, eliminating the unpredictability of shared environments.

✅ Built for Long-Term AI & ML Workloads – Whether you're transitioning from prototyping to production or running long-term training jobs, Bare Metal provides the stability and efficiency you need.

✅ Best Pricing on RunPod – The longer you commit, the steeper the discounts—offering the most cost-effective way to secure high-performance GPUs for your AI workloads.

Customize for Your ML Pipeline

Choose from a variety of GPU types to match your exact workload requirements, and fine-tune your setup to optimize performance for your specific AI models and frameworks.

Get Started with Bare Metal

Ready to lock in your own dedicated AI infrastructure? Fill out our interest form, and we’ll get back to you with next steps.