AI Compute (AIC) – Dedicated GPU Server Hosting

Name: Dedicated GPU Server Hosting
Brand: servers.com
Rating: 5 (1114 reviews)

Overview

Optimize your AI workloads with custom GPUs

Bare metal optimized for AI

Our AI compute infrastructure provides enterprise bare metal hardware with custom GPU deployments. Designed to support major machine learning frameworks like PyTorch and Tensor and optimized to your specific requirements, AIC offers the enhanced compute power, memory and storage required to run data-intensive AI workloads.

Reduce costs for long-term GPU use

Businesses are hitting a critical point with AI, moving past testing phases and rolling out AI workloads long term. However, the costs to do this can be extreme.

That's where AIC comes in. By offering GPU dedicated servers over long term agreements, with no multi-tenant overhead or on-demand premium, we've created a solution that's making AI hosting more economical.

Keep workloads under one network

Most businesses hosting GPU deployments will also have CPU requirements. Often that means managing workloads across different hosting environments – adding an extra level of complexity and limiting operational efficiency.

This is why we designed AIC to work seamlessly alongside our Scalable Bare Metal (SBM) and Enterprise Bare Metal (EBM) servers - allowing you to host CPU and GPU deployments within one private network.

Features

Host AI applications without the premium

GPU dedicated servers

Match your compute demands with custom GPU-accelerated configurations on request.

Tailored performance

Choose optimal CPU, memory and storage configurations for your specific ML use case – from high throughput training to low-latency interface.

Full hardware control

Access iDRAC, configure RAID arrays and format disks exactly as your workload requires – no abstraction, full control.

Redundant, low-latency network

Support distributed training, clustered inference and large-scale AI pipelines with an enterprise-grade network architecture.

Automation-first approach

Automate your infrastructure provisioning via API, CLI or Terraform - ideal for CI/CD integration and large-scale experiments.

ML-native expertise

Consult our engineers on AI stack compatibility – whether you're deploying PyTorch, TensorFlow, ONNX models or hosting vector databases.

FAQs

Are these servers suitable for training LLM?

Yes. Our bare metal GPU servers are well-suited for training large language models. We can help you choose the right configuration (including CPU, RAM, and storage) based on your training pipeline, model size and data bandwidth needs.

Is AI compute infrastructure suitable for real-time inference?

Yes. Our low-level, redundant network architecture ensures minimal latency and high availability for clustered inference scenarios.

What GPU manufacturer(s) do you use?

We offer dedicated servers with NVIDIA GPUs, AMD, Intel or any other manufacturer. We can do this because AIC is a fully custom service which we build to your requirements.

Is AIC available on demand?

No. AIC is designed for long-term use and based on our Enterprise Bare Metal (EBM) hardware under long term agreements. If you want to test a new language model and spin up a GPU for a couple of hours, AIC won't be suitable for you. But once you've worked out what you need and want to cost optimize, then we're here to help you deploy.

What if I need a custom configuration?

We support custom builds and will design and provision a system tailored to your workload based on your specific CPU, RAM, GPU, storage and networking requirements.

Can I configure RAID for large dataset storage?

Yes. You have full control over your RAID setup allowing you to define RAID levels, format disks and access controllers and backplanes directly.

Can I install my own operating system?

Yes. You get direct access to your server via iDRAC (IPMI), allowing you to upload and install any custom OS or image, including specialized machine learning environments.

Which ML stacks are supported?

AIC servers support all major machine learning frameworks, including PyTorch, TensorFlow, JAX and ONNX. They are also well-suited for hosting vector databases such as Weaviate or Qdrant.

What automation tools are available?

You can deploy and manage your AI compute infrastructure using API, CLI or Terraform. This makes it easy to integrate bare metal into existing CI/CD pipelines or MLOps workflows.

Can I use AIC at the same time as EBM and SBM?

Absolutely. You can rent GPU dedicated servers via our AIC service and deploy them alongside standard CPU-based deployments hosted on our Scalable Bare Metal (SBM) and Enterprise Bare Metal (EBM) solutions.

Does a dedicated server need a GPU?

A dedicated server doesn't need a GPU for general tasks like web hosting, databases or file storage, as these rely on CPU, RAM and network performance. However, a dedicated server with a GPU is essential for workloads involving graphics, video rendering, machine learning or scientific computing, where parallel processing is required.

AI Compute