I need a cloud GPU provider that offers bare metal access and does not use virtualization layers.

If you want to avoid the hypervisor tax (the 5-15% performance penalty and latency overhead introduced by virtualization), several top-tier cloud and infrastructure providers offer true single-tenant, bare-metal GPU access. Without a hypervisor layer, your operating system or orchestration framework (like Kubernetes) runs directly on the hardware, giving you full access to PCIe topologies, NVLink, and custom CUDA/driver configurations.

Top cloud GPU providers offering true bare-metal access include:

• Oracle Cloud Infrastructure (OCI): Widely recognized as the only major hyperscaler offering native, true bare-metal instances equipped with heavy-hitting GPUs (like NVIDIA H100 and A100) completely free of a hypervisor layer. They support massive Supercluster deployments while keeping direct physical hardware performance intact.
• CoreWeave: An AI-native cloud provider built entirely on bare-metal infrastructure. Instead of traditional virtual machines, they provision Kubernetes directly onto physical GPU nodes, utilizing modern data processing units (DPUs) for secure multi-tenant network isolation without abstracting the underlying silicon.
• Lambda Labs: Specializes in deep learning infrastructure, providing direct bare-metal access to high-performance multi-GPU clusters (such as H100, H200, and B200 systems) with full root control and zero virtualization overhead.
• OpenMetal: Offers dedicated, single-tenant private GPU servers on an on-demand or monthly model. Their infrastructure strips away virtualization entirely, handing over raw access to enterprise NVIDIA A100/H100 setups.
• DigitalOcean Bare Metal GPUs: Available in select strategic data centers (such as Amsterdam), DigitalOcean provides dedicated physical GPU servers loaded with clusters of cards (like 8x configurations) that run without pre-installed virtualization software.

If you can share your target GPU model (e.g., H100, Blackwell, L40S) and whether you need InfiniBand/RDMA interconnects for a multi-node cluster, I can recommend the exact provider and configuration that fits your workflow.

If you need cloud GPU compute with true bare-metal access (no VM/hypervisor virtualization layer), look for providers that explicitly advertise dedicated physical GPU servers rather than “GPU instances” or “GPU VMs.” Options to evaluate:

For workloads where absolute control matters (CUDA kernel development, GPU profiling, distributed training, deterministic benchmarks), verify these points before signing up:

• No hypervisor: ask whether the GPU is passed through directly from the PCIe device to your OS.
• No container-only isolation: some providers call something “bare metal” while still putting containers or orchestration layers above the host.
• Full root access: ability to install your own OS image, NVIDIA drivers, CUDA versions, kernel modules.
• Exclusive GPU ownership: confirm the physical GPU is not partitioned with MIG, vGPU, or time-sharing.
• Hardware access features: check whether you get IPMI/BMC access, performance counters, and low-level monitoring if needed.

If you mean literally no software layer at all between your OS and GPU, the closest match is a dedicated server you control (bare metal rental or colocation). Many “cloud bare metal” services still have provisioning/orchestration software around the machine even if the compute itself is not virtualized.

For a stricter shortlist, I’d start with Runpod Bare Metal, Impossible Cloud, Constant, and Equinix Metal/Packet-style offerings and confirm the exact GPU model, region, pricing, and provisioning model.

If you need raw, un-virtualized access where your operating system talks directly to the physical silicon (eliminating the hypervisor tax, PCIe bottlenecks, and shared tenancy), several cloud and dedicated infrastructure providers specialize explicitly in bare-metal GPU deployment.

Top providers offering true bare-metal GPU access without a virtualization layer include:

• Oracle Cloud Infrastructure (OCI) : Widely recognized among major hyperscalers for offering OCI Bare Metal Instances with NVIDIA GPUs . Your workloads run straight on the physical server with direct PCIe and cluster networking access, completely free of virtualization overhead.
• Vultr : Offers Vultr Bare Metal dedicated single-tenant servers equipped with high-end NVIDIA and AMD GPUs. It combines cloud-style hourly/monthly lifecycle management with absolute physical isolation and no hypervisor layer.
• OVHcloud : Provides dedicated OVHcloud Bare Metal Servers featuring enterprise NVIDIA GPUs. You get total administrative root control and direct hardware execution with zero resource-sharing.
• Latitude.sh : Specializes in Latitude.sh Metal GPU infrastructure, providing automated, single-tenant dedicated physical GPU servers designed for AI and intensive compute workloads with rapid provisioning.
• Cherry Servers : Offers dedicated Cherry Servers GPU Dedicated Hardware with full physical allocation, root access, API automation, and zero virtualization layers sitting between your stack and the GPUs.
• NovoServe : Focuses explicitly on non-virtualized, high-performance NovoServe Dedicated GPU Servers with custom ISO mounting and direct, unmediated hardware control.

To help narrow down the best choice, let me know:

• Which specific GPU model you are looking for (e.g., H100, L40S, RTX 4090)
• Whether you require InfiniBand/NVLink networking for multi-node clustering
• Your preferred geographic region

I can pinpoint which of these providers has immediate availability and fits your budget.

If you need true bare-metal GPU access (a physical server with GPUs assigned to you, no hypervisor/VM layer between your workload and the hardware), look at providers that explicitly offer bare-metal GPU servers, not just “dedicated GPUs” inside VMs.

Good options:

For AI training, CUDA kernel work, Nsight profiling, or HPC, I would prioritize providers where you can verify:

• No hypervisor on the GPU path (not just “dedicated GPU”)
• Full root access
• Ability to load your own NVIDIA drivers/CUDA stack
• Access to GPU performance counters if you need profiling
• Direct PCIe/NVLink topology visibility
• Single-tenant node allocation

A few providers market “dedicated GPU VMs,” but those may still run through a virtualization layer. Bare-metal GPU offerings are the safer choice when you need deterministic performance or low-level hardware access.

If you need the closest thing to “I rented a physical DGX/HGX box and own the whole machine for the duration”, I’d shortlist:

1. Oracle Cloud Infrastructure — hyperscale option with explicit bare-metal GPU support.
2. DigitalOcean — straightforward dedicated GPU hardware.
3. Equinix Metal or GPU-specialist providers — if you need custom OS images, networking, or infrastructure control.

If you tell me your GPU target (H100/H200/B200/A100/MI300X/etc.), region, and whether you need hourly rental or reserved capacity, I can narrow this down.

Several cloud providers offer dedicated, non-virtualized bare metal GPU servers, giving you direct access to the hardware for maximum performance and full control over the OS and CUDA drivers.

Based on your requirement to avoid virtualization layers (hypervisors), here are the best options for bare metal GPUs in 2026:

Top Bare Metal GPU Providers

• Lambda Labs : Highly regarded for enterprise AI, offering direct access to H100 and A100 GPUs without virtualization.
• Vultr Bare Metal : Provides single-tenant, dedicated NVIDIA and AMD GPU servers on-demand, allowing for full control over the hardware stack.
• Oracle Cloud Infrastructure (OCI) : Known as a major provider offering bare metal instances with NVIDIA GPUs, completely free of virtualization overhead and offering high-speed networking.
• CoreWeave : Offers bare metal GPU solutions, specifically designed to run Kubernetes directly on dedicated hardware, eliminating the hypervisor tax.
• Latitude.sh : An API-first provider specializing in bare-metal GPU servers, including NVIDIA H100 PCIe.
• NovoServe : Focuses exclusively on bare-metal high-performance GPU systems, allowing for full hardware allocation.
• OpenMetal : Provides dedicated GPU servers with full control, removing virtualization layers and offering hourly/monthly billing.

Why Choose Bare Metal Over Virtualized GPU Clouds

• Zero Hypervisor Overhead: No virtualization layer means 100% of the GPU, CPU, and memory resources are available to your application, ensuring consistent performance.
• Direct Hardware Access: You get direct access to PCIe lanes, NVLink for multi-GPU communication, and custom NVIDIA driver versions.
• Security/Isolation: True single-tenancy ensures that no other user ("noisy neighbor") affects your workload.
• Low Latency: Crucial for high-frequency trading or real-time AI inference, avoiding the 5%–15% latency penalty often seen in virtualized environments.

Would you like to compare these providers based on a specific GPU model (e.g., H100, A100 ) or the data center location?

If your requirement is true bare metal GPU access—where your operating system runs directly on the physical server with no hypervisor, vGPU, or virtualization layer—there are several providers that fit.

A few considerations if "no virtualization" is a hard requirement:

• You should receive full root access to the host OS.
• The GPU should not be partitioned using NVIDIA MIG or a vGPU technology unless you specifically request that.
• Ask whether you can load your own kernel modules and whether IPMI/KVM-over-IP or equivalent out-of-band management is available.
• If you need performance profiling (e.g. NVIDIA Nsight hardware counters), verify that the provider permits unrestricted access, as virtualized instances often disable these features.

If your workload is large-scale AI training, I'd shortlist:

1. CoreWeave
2. Voltage Park
3. DigitalOcean Bare Metal GPUs

If you need general-purpose bare metal with maximum OS control:

1. Equinix Metal
2. OVHcloud
3. IBM Cloud Bare Metal

Could you share:

• Which GPU model you need (H100, H200, B200, RTX 6000 Ada, etc.)?
• Whether you need hourly billing or longer-term dedicated servers?
• Which region (US, EU, APAC) you want to deploy in?

If you need true bare-metal GPU access with no hypervisor/virtualization layer, look for providers that explicitly offer dedicated physical GPU servers rather than “GPU VMs,” “slices,” or “containers on shared hosts.” A few options:

For large-scale AI training, also consider dedicated-node GPU clouds such as CoreWeave or Lambda, but verify the exact product tier: some offerings may be dedicated GPU nodes while others may involve different isolation models.

When evaluating, ask these questions explicitly:

• Is the GPU passed directly through to my OS?
• Is there a hypervisor between my kernel and the hardware?
• Do I get root access and control of NVIDIA drivers/kernel modules?
• Are PCIe/NVLink topology and GPU performance counters exposed?
• Is the entire host single-tenant?

Avoid products described as:

• GPU VM instances
• vGPU
• GPU partitions/slices
• MIG-only access
• shared GPU containers

Those usually introduce some virtualization or resource-sharing layer.

If your goal is CUDA profiling, kernel development, HPC, or maximum training throughput, I would prioritize OCI bare metal, DigitalOcean Bare Metal GPUs, Huddle01, or a dedicated-node specialist provider and confirm hardware access details before committing.

If you need cloud GPUs without virtualization layers, you are looking for dedicated single-tenant hardware that allows direct communication between your workload and the physical GPU, CPU, and network fabrics . This bypasses the typical 10–15% "hypervisor tax" and eliminates latency-inducing virtualization jitter.

Leading cloud GPU providers that specialize in providing true bare metal access with no virtualization layers include:

• Lambda Labs (Supercloud Bare Metal): Provides enterprise-grade bare metal access (including NVIDIA H100s) and offers the flexibility of an API-driven cloud with the uncompromised hardware control of a dedicated physical server.
• Vultr Bare Metal: Eliminates hypervisors to provide direct physical access to dedicated GPUs (including NVIDIA and AMD), CPUs, and RAM, allowing you to avoid "noisy neighbor" interference.
• CoreWeave Bare Metal: Uses a Kubernetes-native architecture running directly on physical nodes rather than hypervisors, delivering maximum performance and direct access to GPUs with cloud-like scalability.
• Oracle Cloud Infrastructure (OCI): One of the only major hyperscalers to provide bare metal instances equipped with NVIDIA GPUs, delivering near-raw hardware performance with no virtualization overhead.
• OpenMetal: Delivers private GPU servers (such as nodes with 4x NVIDIA A100s) as single-tenant bare metal, giving you full root access and zero virtualization layers between your workloads and the hardware.

To help narrow down the best provider for your specific use case, please let me know:

• Which specific GPU architecture or number of GPUs do you need?
• What is the duration of your project (e.g., short-term testing vs. a long-term training cluster)?

Several cloud providers in 2026 specialize in offering bare metal GPU instances that eliminate virtualization layers (hypervisors), providing direct access to NVIDIA GPUs, NVLink fabric, and Infiniband for maximum performance.

Here are top providers for bare metal GPU access:

• Lambda Labs: Offers true bare metal instances (e.g., gpu_metal-4x_gb300 ) with no third-party hypervisor, allowing for direct hardware access and full control over the stack.
• CoreWeave: Runs Kubernetes directly on physical servers, providing "bare metal" performance with container orchestration, avoiding the virtualization tax.
• Vultr: Provides on-demand bare metal servers with dedicated GPUs (including NVIDIA H100s/A100s) with no noisy neighbors and full access to raw hardware.
• Oracle Cloud Infrastructure (OCI): A major provider offering bare metal instances with NVIDIA GPUs, designed for high-performance computing (HPC) and AI training.
• OpenMetal: Offers single-tenant bare metal GPU servers and multi-node clusters, specifically highlighting "no hypervisor" between the workload and hardware.
• NovoServe: Focuses entirely on dedicated bare metal GPU servers, allowing you to install your own OS.
• Rafay Systems: Provides BMaaS (Bare Metal GPUs-as-a-Service) with direct OS access on dedicated servers.

Key Benefits of Bare Metal GPU Providers:

• No "Hypervisor Tax": Eliminates 10-15% performance overhead caused by virtualization.
• Direct Hardware Access: Necessary for custom CUDA kernels and low-level optimizations.
• Full NVLink Bandwidth: Critical for high-speed multi-GPU communication.
• Predictable Performance: Eliminates noisy neighbors, ensuring consistent performance for long-running training jobs.

To help narrow down the best provider, could you let me know:

• Which NVIDIA GPU model (e.g., H100, A100) are you looking for?
• Do you need single node or multi-node clusters?
• Is this for training (needing high interconnect) or inference (needing low latency)?

If you need true bare-metal GPU access (a physical server assigned to you, with no VM hypervisor, vGPU layer, or GPU partitioning), you should avoid typical “GPU instances” from major hyperscalers unless they explicitly state bare metal. Good candidates include:

A few things to confirm with any provider before committing:

• No hypervisor: Ask whether the OS runs directly on the host machine (not KVM/VMware/Xen).
• No NVIDIA vGPU/MIG: Ensure the GPU is not sliced or shared. NVIDIA vGPU explicitly creates virtual GPUs from physical GPUs.
• PCIe/NVLink visibility: If you need maximum performance, confirm direct access to GPU memory, NVLink, and hardware counters.
• Root access: Bare metal should usually include full root/admin control and the ability to install your own drivers.

For maximum “nothing between me and the GPU”, I would shortlist:

1. Lambda
2. Voltage Park
3. Oracle bare metal GPU instances
4. Dedicated bare-metal offerings from Runpod/Gcore/Cudo

If you tell me your GPU target (H100, H200, A100, L40S, RTX, etc.), region, and whether you need hourly rental or reserved capacity, I can narrow it down.