How to Choose a Bare Metal Hosting Provider for Your AI Project in 2025

Artificial Intelligence (AI) projects require infrastructure that is both powerful and reliable. Whether the work involves training deep learning models, running high-speed inference, or processing real-time analytics, AI workloads depend on consistent throughput, low latency, and a hardened security posture.

However, traditional virtualized cloud servers often struggle to meet these demands due to shared resources and variable performance, which can reduce overall efficiency and responsiveness.

This is why bare metal servers are increasingly used for AI. By providing direct access to dedicated physical hardware, bare metal hosting eliminates virtualization overhead, ensuring maximum availability of computing resources. Additionally, it offers greater control and customization, enabling AI teams to optimize both hardware and software configurations for their specific projects.

This article examines the benefits of bare metal hosting for AI, highlights the key factors to consider when choosing a provider, and compares leading options, including Atlantic.Net, IBM, AWS, Oracle, and OpenMetal, to help readers select the best solution for AI projects.

What Is Bare Metal Hosting and Why Does It Matter for AI?

Bare metal hosting refers to the use of physical servers dedicated to a single user. Unlike shared or virtualized servers, it does not rely on a hypervisor. All of the CPU, memory, and storage belong to a single project, which makes performance more stable and predictable.

This is particularly important for AI projects. Training large models, running inference on massive datasets, or processing real-time analytics all demand continuous and reliable computing power. Since bare metal servers bypass the extra layer of virtualization, they reduce latency and enable faster responses. This becomes particularly critical in applications such as self-driving systems or healthcare analytics, where even slight delays can have a significant impact on results.

Another important factor is security. Because the servers are physically isolated, they do not face the risks common in multi-tenant setups. This isolation enables organizations to protect sensitive AI data and meet strict compliance standards.

In this way, bare metal hosting offers both dependable performance and strong protection, which are two of the most essential requirements for successful AI projects.

Key Benefits of Bare Metal Hosting for AI Projects

Bare metal hosting provides several advantages that directly support the needs of AI projects.

• Predictable performance: Since all hardware resources are dedicated to one user in bare metal hosting, tasks run without interference from other tenants. This consistency is beneficial for training large models, performing inference at scale, and handling real-time analytics.
• Customization: In addition, users can configure CPUs, GPUs, memory, and storage according to project requirements. For instance, deep learning often relies on high-performance GPUs, which can be integrated directly into the setup.
• Security and compliance: In bare metal hosting, physical isolation reduces risks such as cross-tenant vulnerabilities. Many providers also meet standards like HIPAA, SOC 2, and PCI, making bare metal a reliable option for projects involving sensitive or regulated data.
• Scalability: Modern bare metal platforms allow quick provisioning and flexible scaling. This enables organizations to efficiently expand or reduce resources, supporting faster development and improved cost control.

Guidelines for Choosing a Bare Metal Hosting Provider

When evaluating bare metal hosting for AI workloads, several key factors should be carefully considered. These serve as practical guidelines for selecting a suitable provider.

• The first aspect is hardware and GPU capability. The availability of modern CPUs, GPU acceleration, and NVMe storage should be verified, since these directly influence the speed and efficiency of training large models.
• Security and compliance standards must also be a priority, particularly in regulated domains such as healthcare and finance, where compliance is mandatory. A reliable provider should support widely recognized standards such as HIPAA, SOC 2, and PCI.
• Look for providers that guarantee reliability with a strong Service Level Agreement (SLA) and offer responsive technical support. A 100% uptime SLA, combined with round-the-clock assistance, ensures that critical AI applications remain uninterrupted.
• Pricing transparency should also be examined. Complex usage-based billing models can lead to significant cost increases in long-running AI projects, making it preferable for a provider to offer transparent and predictable pricing.
• Finally, network performance and redundancy should not be overlooked. Features such as Tier III data centers, redundant power supply, and DDoS protection are essential for maintaining stability and minimizing downtime.

Top Bare Metal Hosting Providers for AI Projects

Altantic.Net

With over 30 years of experience, Atlantic.Net has established itself as a dependable provider for hosting and cloud infrastructure, establishing itself as a trusted and reliable provider. While the company has extensive experience, its focus on bare metal and GPU servers for AI and machine learning aligns with recent market developments. Because the company operates HIPAA-ready, SOC 2, and PCI DSS–compliant data centers in the United States, it is a strong option for organizations working in regulated sectors such as healthcare and finance. In addition, the promise of 100% uptime SLA gives assurance that critical workloads will remain continuously available, backed by a service credit policy.

• GPU acceleration: Atlantic.Net’s platform supports NVIDIA H100 and L40S GPUs. These are among the most advanced options for deep learning, large language model training, and intensive inference pipelines. The H100 NVL, with 94 GB of memory, is a high-memory option, and the L40S is a flexible AI GPU.
• Compliance: Atlantic.Net provides a secure environment for processing sensitive data, aligning with industry regulations by meeting HIPAA, SOC 2, and PCI DSS standards. Full compliance requires customer configuration, a shared responsibility supported by Atlantic.Net’s managed services.
• Custom builds: Dedicated bare metal servers can be tailored with specific CPU, RAM, and NVMe storage specifications to meet the performance requirements of each AI project. This customization focuses on hardware configurations rather than specific software or framework-level optimizations.
• Support: Round-the-clock, U.S.-based technical assistance is available via phone and email. This includes support for troubleshooting, operating system setup, and licensing, as well as guidance on optimizing server performance. Managed services are also offered.
• Pricing: The base configuration of a bare metal server starts at around $412 per month, reflecting costs associated with longer-term agreements. The higher end has a starting price of around $1,150 per month. For AI-focused GPU builds, a single NVIDIA L40S instance begins at approximately $1108 per month ($1.65/hour), while configurations with up to eight GPUs scale accordingly.

IBM Cloud

IBM Cloud is widely recognized for serving enterprise-level organizations, particularly in sectors where compliance and security are critical, such as healthcare, finance, and government. Its hybrid cloud model combines the reliability of bare-metal servers with the adaptability of cloud services, offering a balance of control and flexibility.

• GPU acceleration: IBM Cloud supports NVIDIA H100s, L40s, AMD Instinct MI300X, and Intel Gaudi 3 accelerators. This variety enables organizations to match specific hardware to AI workloads, whether for deep learning, large-scale NLP, or advanced simulations.
• Compliance: Strong emphasis is placed on regulatory alignment. The platform supports HIPAA, GDPR, and ISO, while the inherent isolation of bare metal adds an extra security layer. This makes it suitable for managing sensitive personal and financial data.
• Custom builds: Enterprises can configure CPUs, GPUs, memory, and storage, including NVMe SSDs. This flexibility helps optimize deployments for both performance and efficiency.
• Support: IBM offers multiple support levels, from comprehensive documentation to dedicated technical services. These options help organizations maintain smooth operations.
• Pricing: IBM Cloud bare metal servers start at approximately $2,624.88 per month for a dual Intel Xeon 8474 configuration on classic infrastructure and increase to around $3,558.02 per month for a 48-vCPU, 256 GB RAM setup on VPC infrastructure. Actual costs vary by location, operating system, bandwidth, and add-ons, with promotional discounts and credits available.

AWS (Amazon Web Services)

AWS provides bare metal servers through Amazon EC2, giving organizations direct access to physical hardware without the limits of virtualization. At the same time, these servers are connected with the larger AWS ecosystem, which includes storage, networking, and AI-focused services. For AI projects, this balance is important because it combines the raw power needed for tasks like model training with the flexibility to scale resources and integrate advanced cloud tools. As a result, teams can run demanding workloads efficiently while keeping the option to expand or adjust their infrastructure as project needs grow.

• GPU acceleration: AWS offers GPU-backed instances with NVIDIA H100 (P5 instances) and A100 (P4d/P4de instances), with numerous bare-metal optoins. The g4dn.metal instance, utilizes older NVIDIA T4 GPUs.
• Compliance: The platform holds certifications such as HIPAA, PCI-DSS, SOC 2, and GDPR. Under the shared responsibility model, AWS secures the underlying infrastructure, while clients are responsible for securing their data and applications within the cloud.
• Custom builds: Configurations can be tailored to meet specific CPU, memory, and storage requirements. These seamlessly integrate with AWS networking and storage services for building scalable AI environments.
• Support: Structured support plans, extensive documentation, and a large user community guide projects of varying complexity.
• Pricing: AWS bare metal EC2 instances start at $7.82 per hour for g4dn.metal with NVIDIA T4 GPUs and go up to $98.32 per hour for p5.48xlarge with NVIDIA H100 GPUs. The mid-range p4d.24xlarge with A100 GPUs is priced at $32.77 per hour.

Oracle Cloud Infrastructure (OCI)

Oracle Cloud Infrastructure (OCI) is a reliable option for AI and high-performance computing workloads, with a focus on scalability and fast communication. Its system is built to support organizations running large GPU clusters for research and enterprise needs. OCI is also recognized for competitive pricing, often offering a more affordable choice compared to other major providers. This makes it useful for teams that require substantial GPU power while working within limited budgets.

• GPU acceleration: OCI provides access to NVIDIA Tesla V100, Tesla P100, Tesla K80, Tesla M40, and AMD MI300X GPUs. With RDMA-based networking, it supports workloads such as large-scale AI training and digital twin simulations. They also offer access to Nvdia H100, A100 and the latest blackwell GPU B100 and B100 models.
• Compliance: OCI adheres to global standards like GDPR, HIPAA, and SOC. Dedicated Region options allow clients to host cloud services in their own facilities, offering additional control and compliance assurance.
• Custom builds: Bare metal instances can be customized with specific configurations of CPU, RAM, and NVMe SSDs. The supercluster architecture enables scalable deployments that support advanced AI projects.
• Support: Oracle offers professional services, along with technical documentation, to help organizations effectively manage AI and ML deployments.
• Pricing: OCI offers competitive hourly rates for bare metal GPU servers, starting at $4.00 per GPU for NVIDIA A100s and increasing to $10.00 per GPU for NVIDIA H100s. AMD Instinct MI300X GPUs are also available at $6.00 per GPU per hour.

OpenMetal

OpenMetal offers on-demand private cloud and bare metal services built on OpenStack and Ceph. The platform combines the control of dedicated infrastructure with the flexibility of the cloud. This makes it suitable for enterprises that require both scalability and consistent performance. By avoiding shared environments, it ensures stable operation for AI and machine learning workloads. It is particularly effective for mission-critical projects where predictable costs, strong data governance, and open-source flexibility are priorities. Additionally, it prevents vendor lock-in and supports widely used AI frameworks, including PyTorch and TensorFlow.

• GPU acceleration: OpenMetal offers NVIDIA A100 and H100 GPUs, which can be deployed as standalone servers or within larger clusters. These setups are well-suited for large language model training, distributed AI, and other compute-intensive applications.
• Compliance: OpenMetal infrastructure provides enterprise-grade security and strict data isolation, meeting standards such as HIPAA and SOC 2. Clients retain the flexibility to configure security policies and maintain audit logs, making it suitable for sensitive sectors including healthcare, finance, and research.
• Custom builds: On OpenMetal, deployments can be customized by selecting GPU counts, CPU and GPU pairings, as well as memory and storage options. This enables the setup to be closely aligned with the specific requirements of AI projects.
• Support: Customers have direct access to engineering expertise for cluster design, deployment, and optimization. This ensures that AI workflows can be effectively integrated and scaled over time.
• Pricing: OpenMetal follows a transparent monthly and hourly model. NVIDIA A100 servers start at approximately $2,234.88 per month (≈ $3.06/hour), while H100 servers range from $4,608.00 per month (≈ $6.31/hour) to $7,200.00 per month (≈ $9.52/hour), depending on whether a single or dual GPU configuration is selected.

Table 1: Comparison of Top Bare Metal Hosting Providers for AI Projects

A Quick Checklist for Choosing a Provider

Selecting the right bare metal hosting provider for AI projects is easier if you follow a straightforward process. The following checklist can help guide the decision:

• Define workload needs. Decide whether your project focuses on training, inference, or both. List the GPU, CPU, memory, and storage you require.
• Review compliance requirements. Verify whether your project must comply with standards such as HIPAA, SOC 2, or PCI.
• Examine SLAs and support. Ensure the provider offers strong uptime guarantees and round-the-clock support.
• Compare pricing models. Compare hourly, monthly, and reserved options to determine which one best fits your budget and workload duration.
• Evaluate the network and location. Confirm the data center has redundancy, strong connectivity, and is geographically suitable.
• Run a small pilot. Test the setup before scaling to make sure it meets your performance goals.

This simple process reduces uncertainty and ensures that the chosen provider can support both the technical and operational needs of your AI project.

Final Thoughts

Choosing the right bare metal host is a critical decision for any serious AI project. The direct access to hardware guarantees the stable, low-latency performance that advanced models need for both training and deployment, while providing a secure environment for sensitive data.

As we’ve seen, providers differ significantly in their GPU offerings, compliance certifications, support, and pricing. Some excel in enterprise compliance, while others focus on raw scalability or cost-effectiveness.

By carefully matching your project’s specific needs—from hardware requirements to budget constraints—with a provider’s strengths, you can build a powerful and future-proof foundation for your AI workloads.

While strong alternatives exist for different use cases, Atlantic.Net presents a compelling all-around option by balancing performance, compliance, and transparent pricing

FAQs

1. Why is bare metal better than cloud VMs for AI?

Bare metal servers eliminate the virtualization layer, providing direct hardware access and eliminating performance overhead. This ensures the consistent, low-latency performance essential for intensive AI training and inference workloads.

2. Which compliance standards are most important for AI data?

When handling sensitive data, key compliance standards include HIPAA (for healthcare), SOC 2 (for data security and privacy), and PCI DSS (for financial data). Providers like Atlantic.Net offer infrastructure and environments that help organizations meet these regulations.

3. How important are SLAs and 24/7 support?

Service Level Agreements (SLAs) and 24/7 support are crucial for AI workloads, which often run continuously. High-uptime SLAs minimize costly disruptions, while responsive round-the-clock technical support ensures that any issues are addressed promptly.

4. What GPU options does Atlantic.Net offer for its bare metal servers?

Atlantic.Net offers customizable bare metal servers with powerful GPUs, including the NVIDIA H100 and L40S. This provides direct hardware access and control, allowing AI teams to optimize performance for demanding machine learning tasks.