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1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minuteShort answer: OVHcloud and RunPod Bare Metal are the clearest choices when you need a physical GPU server assigned to your business. RunPod Pods and Lambda are stronger self-service cloud options; Vast.ai is usually the lowest-cost marketplace but carries host and interruption risk; CoreWeave and reserved Lambda clusters target enterprise-scale deployments. This April 2026 comparison is date-locked. GPU prices, stock, regions, and terms change frequently, so confirm the live quote before ordering.
“Dedicated GPU” is not a single product category. A bare-metal server, dedicated virtual machine, container pod, marketplace rental, and multi-GPU cluster differ materially in isolation, control, reliability, and billing.
Quick comparison
| Provider | Product type | Best for | Physical dedicated server? | Price and availability note |
|---|---|---|---|---|
| RunPod Bare Metal | Physical bare metal | Custom drivers and long-running workloads | Yes | Quote or commitment pricing; confirm complete-server cost at official page |
| OVHcloud | GPU bare metal | Predictable monthly hosting | Yes | Some listed configurations started around $1,180–$1,216/month, with availability and installation fees varying by region; see GPU servers |
| RunPod Pods | Container-based GPU cloud | Fast self-service and experiments | No | Per-second billing; storage is separate; rates are live and volatile at pricing |
| Lambda | Dedicated GPU cloud instances and clusters | AI-focused teams | Usually no | Published per-GPU-hour rates and configurations at pricing |
| CoreWeave | GPU cloud, spot, and clusters | Enterprise multi-GPU production | Usually no | Large systems are commonly priced per node; compare complete configurations at pricing |
| Vast.ai | Marketplace | Lowest-cost, restartable jobs | Offer-dependent | Hosts set prices; storage and bandwidth are additional; see pricing documentation |
| Nebius | GPU cloud | European and international capacity | Product-dependent | Request a dated quote; exact April terms were not publicly established |
| Paperspace | Managed GPU cloud/workspaces | Convenient development environments | No | Verify current GPU, storage, and egress pricing directly |
| Vultr | Cloud GPU and bare-metal ecosystem | Existing Vultr customers | Product-dependent | GPU model and orderability vary by region |
| Hyperstack or Crusoe | Sales-led GPU cloud | H100/H200 production capacity | Product-dependent | Obtain complete-node pricing, SLA, and minimum-term details |
“Starting at” prices are not guaranteed quotes. Record the GPU model, region, billing mode, commitment, included CPU/RAM/storage, and whether the number is per GPU or per node.
What “dedicated GPU server” means
Traditional bare metal
A physical server is assigned to one customer. You normally receive administrator access, direct hardware visibility, and freedom to install an operating system, drivers, kernel modules, persistent services, and custom networking. Monthly billing or a commitment is common, and provisioning is slower than launching a cloud instance.
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Dedicated GPU cloud instance
A GPU or GPU-equipped virtual machine is allocated to your workload, but the host can remain virtualized. It is easier to resize and usually billed hourly or per second, while hypervisor and driver restrictions may limit system-level customization.
Container-based pod
A container receives GPU access with a ready-to-use developer workflow. Pods are excellent for training, inference, fine-tuning, and batch jobs, but they are not automatically physical dedicated servers.
Marketplace rental
Independent hosts supply capacity through a marketplace. Prices are often lowest, but uptime, network performance, software images, data handling, and interruption risk vary by host. Treat the individual offer—not the marketplace brand—as the unit you must evaluate.
Rank #2
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- Powered by GeForce RTX 5070 Ti
- Integrated with 16GB GDDR7 256bit memory interface
- PCIe 5.0
- WINDFORCE cooling system
How the providers were evaluated
The comparison prioritizes hardware fit (20%), availability (15%), price transparency (15%), performance consistency (15%), control and software (10%), storage and networking (10%), reliability and support (10%), and billing flexibility (5%). No provider is ranked on price alone, and no performance or uptime claim is made without comparable testing or a contractual SLA.
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1. RunPod Bare Metal — best true dedicated GPU direction
RunPod describes Bare Metal as physical GPU servers without virtualization, making it the strongest RunPod option for custom operating systems, kernel modules, driver control, and long-running training. It also advertises commitment-based discounts and examples for H200, H100, A100, and L40S hardware at its Bare Metal page.
- Choose it for: teams replacing on-premises hardware or running persistent services.
- Confirm: whether the quote is per GPU or the complete server, plus CPU, RAM, NVMe, network, region, setup time, and support.
- Avoid it for: a one-hour experiment where a self-service pod is cheaper and faster.
2. OVHcloud — best predictable monthly bare metal
OVHcloud offers conventional GPU dedicated servers and AI bare-metal systems with configurable memory, NVMe, and private/public networking. Some displayed configurations were approximately $1,180–$1,216 per month, but stock, region, and installation charges can materially change the first invoice. Check GPU dedicated servers and AI servers.
Rank #3
- Powered by the NVIDIA Blackwell architecture and DLSS 4. System Requirements: Minimum 850W PSU with 16-pin 12V-2x6 (12VHPWR) connector required. Verify before purchasing.
- Military-grade components deliver rock-solid power and longer lifespan for ultimate durability. Compatibility: 348mm (13.7") length, 3.6 slots, 4.3 lbs. Confirm case clearance and slot spacing. GPU bracket included.
- Protective PCB coating helps protect against short circuits caused by moisture, dust, or debris
- 3.6-slot design with massive fin array optimized for airflow from three Axial-tech fans
- Phase-change GPU thermal pad helps ensure optimal thermal performance and longevity, outlasting traditional thermal paste for graphics cards under heavy loads
- Choose it for: a fixed monthly server, European infrastructure, and private networking.
- Confirm: exact GPU, availability status, installation fee, bandwidth, and delivery time.
- Avoid it for: rapid autoscaling or short-lived jobs.
3. RunPod Pods — best self-service flexibility
RunPod advertises more than 30 GPU models, 31 global regions, and per-second billing for on-demand Pods at its cloud GPU page. Its catalog includes current-generation and consumer cards, but Pods are container-oriented cloud environments rather than automatic bare metal.
- Choose it for: experiments, fine-tuning, batch processing, and fast deployment.
- Budget for: container disk, volume disk, and network storage, which are billed separately according to the pricing page.
- Check: whether community or secure capacity meets your isolation and reliability requirements.
4. Lambda — best AI-focused instance catalog
Lambda publishes GPU memory, vCPU, RAM, storage, and price per GPU-hour for configurations including H100, A100, B200, GH200, A6000, and A10 at its pricing page. The page may show a per-GPU rate even when the practical purchase is a multi-GPU node.
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- Confirm: self-serve capacity, region, complete-node price, and whether a reserved cluster has different terms.
- Best use: production inference or training when the required GPU is orderable and the network topology fits.
5. CoreWeave — best enterprise GPU cloud
CoreWeave supports configurable on-demand, spot, inference, and multi-GPU systems. Its public catalog includes large HGX B200 and GB200 configurations at the pricing page, but those node prices are not comparable with a single inexpensive GPU.
Rank #4
- Powered by the NVIDIA Blackwell architecture and DLSS 4
- Powered by GeForce RTX 5060
- Integrated with 8GB GDDR7 128bit memory interface
- PCIe 5.0
- WINDFORCE cooling system
- Choose it for: multi-GPU production, cluster orchestration, and sales-assisted capacity.
- Confirm: node-versus-GPU billing, network fabric, storage, SLA, and spot termination behavior.
- Avoid it for: a small project that needs one GPU for a few hours.
6. Vast.ai — best marketplace value
Vast.ai lets hosts set prices, so supply, demand, GPU type, storage, and bandwidth determine the total. Its marketplace and pricing documentation explain the model.
- Choose it for: checkpointed training, rendering queues, and cost-sensitive experiments.
- Vet: host history, location, disk speed, network performance, persistence, and interruption terms.
- Avoid it for: sensitive data or a production API that cannot tolerate host loss unless the specific offer and controls are contractually suitable.
7. Nebius — European neocloud candidate
Nebius appears in 2026 market comparisons for H100/H200-class capacity and may suit teams seeking European or international regions. Exact April pricing, stock, minimums, and physical-isolation terms were not established in a public first-party rate card, so request a dated quote.
- Confirm: whether the offer is a VM, bare metal server, or cluster; data residency; networking; and reservation obligations.
- Best fit: organizations prepared to evaluate a newer, sales-assisted capacity option.
8. Paperspace — best managed development workflow
Paperspace is suited to users who value notebooks and managed development over the lowest GPU-hour price. Verify the current GPU, persistent-disk, egress, and product type directly; a notebook or VM should not be represented as a physical dedicated server.
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- Powered by the NVIDIA Blackwell architecture and DLSS 4 OC mode: 2640MHz/Default mode: 2610MHz (Boost Clock)
- Military-grade components deliver rock-solid power and longer lifespan for ultimate durability
- Protective PCB coating helps protect against short circuits caused by moisture, dust, or debris
- 3.125-slot design with massive fin array optimized for airflow from three Axial-tech fans
- Phase-change GPU thermal pad helps ensure optimal thermal performance and longevity, outlasting traditional thermal paste for graphics cards under heavy loads
- Choose it for: convenient model development and teams already using its workflow.
- Compare: the full storage and data-transfer bill against GPU-first alternatives.
9. Vultr — best general-infrastructure alternative
Vultr can be convenient for existing customers combining ordinary infrastructure with GPU capacity. Its documentation distinguishes bare-metal instances from cloud GPU virtual machines, but a bare-metal product does not automatically include a GPU. Verify model, region, minimum term, and orderability before comparing it with a dedicated GPU server.
10. Hyperstack or Crusoe — best sales-led production alternative
Both providers appear in 2026 H100/H200 capacity comparisons. Treat exact rates as quote-dependent. Request complete-node pricing, region, SLA, storage, networking, minimum term, cancellation rights, and hardware replacement commitments rather than accepting a headline GPU-hour number.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Choose a GPU by workload
| Workload | Relevant GPU classes | What matters most |
|---|---|---|
| Development and image generation | RTX 3090/4090, A5000, A6000, L4 | Price, VRAM, availability |
| Fine-tuning and medium inference | L40S, RTX 6000 Ada, A100 40/80GB | VRAM, bandwidth, software support |
| Large-model inference | A100 80GB, H100 80GB, H200 141GB, B200-class | VRAM, quantization, throughput, latency |
| Large training | H100, H200, B200, HGX systems | Interconnect, scaling, checkpoint storage |
| Rendering and video | RTX 4090/5090, L40S, RTX Pro 6000 | CUDA/OptiX, encoders, VRAM |
| Sensitive workloads | Controlled enterprise data-center GPUs | Isolation, logging, geography, contract terms |
VRAM is not system RAM. PCIe GPUs are not equivalent to SXM/HGX systems, and a GPU count says little about multi-GPU performance without the interconnect and NUMA layout. NVIDIA certification can help assess supported platforms, but a rented NVIDIA GPU does not automatically include NVIDIA AI Enterprise or guarantee every driver and CUDA combination; see NVIDIA’s certification documentation.
Bare metal, cloud GPU, or marketplace?
| Your requirement | Prefer |
|---|---|
| Full OS, kernel, and driver control | Bare metal |
| One-hour experiment | Cloud GPU or marketplace |
| Stable production API | On-demand dedicated cloud or bare metal |
| Restartable batch work | Spot or marketplace, with checkpoints |
| Multi-node training | Enterprise GPU cluster |
| Predictable monthly invoice | Dedicated bare metal |
| Lowest possible price | Marketplace, accepting host risk |
How to compare the real cost
Hourly versus monthly
For a continuously running 30.4-day month, multiply an hourly rate by about 730 hours. A $1.99 hourly equivalent is approximately $1,453 per month; $4.39 is approximately $3,205. These are mathematical equivalents, not promised monthly invoices.
Total cost of ownership
- GPU, CPU, and RAM
- Local NVMe and persistent volumes
- Object storage, snapshots, and backups
- Public bandwidth, egress, and inter-region transfer
- Setup, installation, taxes, and public IPs
- Minimum commitments, deposits, and support plans
- Idle-but-billed storage and migration at teardown
Availability, interruption, and support checks
Before ordering, record the region, exact GPU count, whether the rate is live or “from,” provisioning time, minimum term, and whether the listing is on-demand, spot, reserved, or marketplace. Spot and marketplace capacity can disappear; use them only when your job checkpoints and can restart. For production, confirm the SLA, hardware replacement process, support response target, refund policy, backup responsibility, acceptable-use rules, and data geography.
Quick Recap
Buying checklist
- Select the exact GPU and confirm VRAM, PCIe/SXM/HGX layout, CPU, and RAM.
- Choose the region and verify that the configuration is currently orderable.
- Identify the billing unit: GPU-hour, node-hour, server-hour, or monthly server.
- Add persistent storage, transfer, egress, setup, taxes, and support to the estimate.
- Confirm bare metal, VM, container, marketplace, or cluster classification.
- Check root access, OS choices, NVIDIA driver/CUDA policy, Docker, and kernel restrictions.
- Read cancellation, interruption, replacement, SLA, and refund terms.
- Timestamp the quote; if capacity is unavailable or sales-only, label it “not currently orderable” or “quote required.”
Recommendations by buyer
- Best true bare metal: RunPod Bare Metal for custom control; OVHcloud for a conventional monthly server.
- Best self-service: RunPod Pods.
- Best published AI instance catalog: Lambda.
- Best budget option: Vast.ai, when the workload is restartable and the host is vetted.
- Best enterprise cluster: CoreWeave or a reserved Lambda cluster.
- Best sensitive workload direction: controlled bare metal or an enterprise cloud with contractual isolation, logging, and data-residency terms.
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
