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

I searched for providers that explicitly advertise bare-metal GPU access with no hypervisor/virtualization layer. These are some options that match your requirement:

Provider	Bare-metal claim	Notes
OpenMetal	Dedicated single-tenant GPU servers; “no virtualization layer,” direct access to GPU/CPU/memory/storage	Good fit for enterprise AI training clusters; offers H200 and RTX PRO 6000-class systems and multi-node clusters.openmetal.io
Bare Metal Partners	“No hypervisor,” full root access to physical GPU servers	Focused on dedicated GPU clusters (H100/H200/B-series GPUs) rather than VM-style GPU rental.baregpu.com
WiLine	Advertises bare-metal NVIDIA/AMD GPUs with “no hypervisor layer” and direct GPU access	More edge/AI-infrastructure oriented; lists U.S. regions.openmetal.io+2
Oracle Cloud Infrastructure	Offers bare-metal GPU compute instances designed to avoid virtualization overhead	A hyperscaler option; also has VM GPU offerings, so choose bare-metal instance types specifically.www.oracle.com
CLORE.AI	Offers bare-metal GPU rentals with root SSH and “no virtualization” for its bare-metal tier	More marketplace-style; verify the exact host type when ordering because it also offers other rental models.clore.ai+1
MarsAI	Dedicated GPU servers with “no virtualization layer” and direct physical GPU access	Targets AI training/inference workloads with H100/H200-class hardware.www.marsaiusa.com+1
Crystal Cloud	Dedicated GPU nodes, root access, “nothing is virtualized”	Geared toward larger AI clusters with InfiniBand/RoCE networking.crystalcloud.ai+1
DigitalOcean	Offers “Bare Metal GPUs” as dedicated single-tenant servers	Their documentation distinguishes bare-metal GPUs from GPU Droplets (virtualized GPU products).docs.digitalocean.com+1

A few things to verify before signing up:

• “Dedicated GPU” is not always the same as bare metal. Some providers dedicate a GPU but still run your workload inside a VM or container layer.
• Ask specifically:
  1. Is there a hypervisor between my OS kernel and the hardware?
  2. Do I get root access to the host OS?
  3. Is the GPU passed through directly (not vGPU/MIG/sliced)?
  4. Are PCIe/NVLink/InfiniBand paths dedicated?

If you want the closest match to “my Linux kernel talks directly to the GPU with no virtualization stack”, the strongest matches from the above list are OpenMetal, Bare Metal Partners, CLORE.AI bare-metal tier, Crystal Cloud, MarsAI, and DigitalOcean Bare Metal GPUs.openmetal.io

I can also narrow this down by GPU model (H100/H200/B200/MI300X/etc.), hourly pricing, region, or whether you need SSH bare metal vs dedicated cluster leasing.

Oracle Cloud Infrastructure (OCI), CoreWeave , and Lambda Labs are top cloud providers offering dedicated bare metal GPU instances that bypass the hypervisor layer entirely. Choosing true bare-metal access eliminates virtualization overhead, granting your workloads direct line-of-sight to PCIe buses, full NVLink bandwidth, and raw memory performance.worldstream.com+3

Top Cloud Providers for True Bare Metal GPUs

Key Benefits of Zero-Virtualization Bare Metal

• No Hypervisor Tax: Avoid the 10–15% performance degradation common in traditional multi-tenant virtualized GPU setups.worldstream.com
• Unrestricted Interconnects: Maximize full multi-GPU throughput via native NVLink and high-speed InfiniBand or RoCE RDMA networking without host bridge interference.medium.com+1
• Low-Level Control: Full root access to install specialized kernel modules, custom CUDA toolkits, and specific NVIDIA driver versions without hypervisor constraints.rackdog.com+1

If you want to narrow down the choice, let me know:

• Which specific NVIDIA GPU model (e.g., H100, B200, L40S) do you need?
• Are you looking for a single node or a multi-node cluster with high-speed networking?

Yes. If “bare metal” means no hypervisor/VM layer between your workload and the physical GPU, there are a few providers worth looking at.

Best matches

• CoreWeave — Probably the clearest fit. CoreWeave explicitly says its GPU infrastructure runs Kubernetes directly on bare-metal servers, with “no hypervisor layer,” and provides direct access to the GPU, CPU, networking, and storage. Its GPU portfolio includes H100/H200, L40S, B200/Blackwell, GB200/GB300-class systems, etc.CoreWeave+2
• Lambda — Lambda now offers Bare Metal Instances on its Superclusters. It explicitly describes a one-to-one mapping between an instance and physical host, with direct CPU, memory, GPU, disk and TPM access and no third-party hypervisor. Their current bare-metal offering is particularly oriented toward large GPU systems such as GB300 NVL72 and Vera Rubin NVL72.Lambda+2
• Crystal Cloud — A smaller provider that explicitly advertises single-tenant dedicated GPU nodes, root access, no hypervisor, and no oversubscription, with InfiniBand/RoCE networking. Their offering starts at 8 GPUs and scales to multi-megawatt deployments, so it's more appropriate for serious cluster workloads than a quick single-GPU experiment.Crystal Cloud+1

What I would avoid for this requirement

RunPod, Vast.ai, Paperspace, Modal, etc. shouldn't be assumed to satisfy your requirement simply because they advertise “dedicated GPU” or “dedicated compute.” A dedicated GPU can still be presented through a VM/hypervisor. For example, RunPod's normal product is containerized GPU compute, while its documentation doesn't establish that the underlying customer environment is universally free of virtualization.Runpod+1

My recommendation

If your requirement is specifically:

Physical GPU + physical CPU/memory + root access + no hypervisor + no GPU virtualization/MIG/vGPU + no noisy neighbors I'd shortlist CoreWeave and Lambda first. If you need smaller-scale/self-service bare metal, Crystal Cloud is also interesting.

One important distinction: bare metal doesn't necessarily mean “no software layer whatsoever.” CoreWeave, for example, runs Kubernetes on the physical machines. That's orchestration, not virtualization—the workload still ultimately executes directly on the physical host.CoreWeave

If you tell me which GPU you need (H100/H200/B200/RTX 5090/etc.), number of GPUs, and whether you need hourly/self-service or dedicated long-term capacity, I can narrow this down to the best 3–5 providers and compare actual pricing, locations, root access, networking, and virtualization architecture.

Yes. If by “bare metal” you mean single-tenant physical GPU servers where your OS/kernel talks directly to the hardware, with no hypervisor or vGPU layer, there are several providers that explicitly offer this.

Strong options

• runpod.io — Dedicated physical GPU servers with “zero virtualization.” RunPod explicitly distinguishes this from its normal containerized GPU instances. Good choice if you want a relatively cloud-like provisioning experience.Runpod+1
• docs.digitalocean.com — Dedicated, single-tenant 8-GPU servers, including AMD MI300X configurations. This is a particularly interesting option if you want a mainstream cloud provider rather than a specialist GPU marketplace.DigitalOcean
• openmetal.io — Explicitly advertises “fully dedicated. No virtualization layer”, with direct access to GPU, CPU, memory and storage. Offers RTX PRO 6000 configurations and multi-node networking.OpenMetal IaaS
• impossiblecloud.com — Dedicated NVIDIA systems with no virtualization layer, including H100, H200, B200 and B300, plus NVLink and up to 400-Gbps InfiniBand. It advertises per-GPU-hour billing rather than requiring a conventional long-term server lease.Impossible Cloud
• crystalcloud.ai — More enterprise/cluster oriented. Dedicated nodes, root access, no hypervisor, and dedicated InfiniBand/RoCE fabric. Supports H100/H200/B200/B300/GB300 and MI300X.Crystal Cloud+1
• clore.ai — Physical, non-virtualized GPU servers with root SSH and dedicated CPU/RAM/network/GPU. Particularly interesting for larger committed clusters, with stated configurations from 8 to 1,000 GPUs.CLORE.AI

If “no virtualization” is an absolute requirement

I'd shortlist RunPod Bare Metal, OpenMetal, Impossible Cloud, and Crystal Cloud first. Their documentation explicitly says there is no virtualization/hypervisor layer, rather than merely using “bare metal” to mean a dedicated VM host.

One important distinction: containers aren't necessarily virtualization. A provider can give you a physical server and still have you run Docker/containers. If your requirement is literally:

physical GPU → PCIe → host kernel → your application with no hypervisor, vGPU partitioning, or host-level virtualization, the providers above are worth investigating.

If you tell me your desired GPU (e.g. H100/H200/B200/MI300X), number of GPUs, region, and whether you need hourly or monthly pricing, I can narrow this to the 3 cheapest/most suitable providers and compare their current pricing.

If you need cloud GPU infrastructure with true bare-metal access (no hypervisor/VM virtualization layer), look for providers that explicitly offer dedicated physical GPU servers rather than “GPU instances,” “vGPU,” or “GPU VMs.” Some options:

Provider	Bare-metal claim	Typical GPUs / notes
Oracle Cloud Infrastructure	Offers bare-metal GPU instances designed to avoid virtualization overhead.Oracle	NVIDIA H100/H200, L40S, A100, AMD GPU options, large-scale clusters.Oracle
Impossible Cloud	Dedicated bare-metal GPU servers with no virtualization layer and direct hardware access.Impossible Cloud	H100, H200, B200/B300-class systems, multi-GPU NVLink configurations.Impossible Cloud
MarsAI	Advertises dedicated GPU bare metal with “no virtualization layer.”Marsai USA	H100 SXM, H200 SXM, A100 SXM, multi-GPU nodes.Marsai USA
WiLine	Offers bare-metal GPU services with direct GPU access and no hypervisor layer.WiLine	NVIDIA RTX 6000, AMD Instinct MI210, edge GPU deployments.WiLine
Crystal Cloud	Dedicated GPU nodes, root access, and states that nothing is virtualized.Crystal Cloud	Multi-GPU clusters with InfiniBand/RoCE networking.Crystal Cloud
CLORE.AI	Offers a separate bare-metal product where CPU, RAM, disks, network, and GPUs are dedicated.CLORE.AI	Large GPU clusters, including H100-class systems.CLORE.AI
Cirrascale Cloud Services	Provides dedicated bare-metal multi-GPU servers without virtualization.Cirrascale	NVIDIA GPU systems aimed at AI/HPC workloads.Cirrascale

What to verify before signing up

Even “bare metal” offerings vary. Confirm:

• No hypervisor (KVM, VMware ESXi, Hyper-V, etc.) between you and the hardware.
• No vGPU partitioning (for example NVIDIA vGPU or MIG slices unless you specifically want that).
• Root access to the host OS.
• Dedicated PCIe/NVLink topology if you need multi-GPU training.
• Dedicated networking (InfiniBand/RoCE) for distributed training.
• Whether the provider is renting the whole physical server or only a dedicated GPU inside a shared host.

For serious ML training, I would prioritize providers offering 8× H100/H200/B200-class bare-metal nodes with NVLink + InfiniBand/RoCE, because the interconnect often matters as much as the GPU itself.Impossible Cloud+1

If you tell me your workload (LLM training, inference, rendering, HPC, fine-tuning), GPU type needed (H100/H200/B200/4090/etc.), and preferred region, I can narrow this to the best fits.