GPU Infrastructure Comparison 2026: What Cloud Providers Don’t Want You to Know
By GYGO Research Team. Published February 26, 2026. Pricing table rechecked and reset against published list rates on October 13, 2026.
The GPU market is less transparent than the stock market, and it’s costing teams real money. We rechecked every provider’s published on-demand rate on October 13, 2026, and found the same NVIDIA H100 80GB selling for $3.99 per GPU-hour at one provider and $12.29 at another. Run an 8-GPU node around the clock at the top of that range instead of the bottom and you hand over more than $48,000 a month for identical silicon.
This post breaks down where the spread lives, which providers win on which use cases, and how the rent-vs-buy-vs-colocation math works once you price cloud at its real list rate.
The 2026 GPU Landscape: Three Watershed Products
In eighteen months, three hardware releases reset the market:
NVIDIA H200
Doubled memory bandwidth over the H100 it succeeded. The H200’s 141 GB of HBM3e memory at 4.8 TB/s bandwidth is the reason inference providers are retiring A100 clusters faster than anyone predicted.
AMD MI300X
Arrived as the memory-capacity champion with 192 GB of unified HBM3 on a single die. MLPerf results from late 2025 showed the MI300X competitive with H100 on transformer inference. We can’t give you a per-hour comparison: none of the providers in this guide publishes an MI300X rental rate.
NVIDIA GB200 NVL72
Set a new performance ceiling for rack-scale deployments. The NVL72’s 36 GB200 Superchips connected via fifth-generation NVLink deliver throughput that did not exist in any cloud catalog 18 months ago. A single NVL72 rack replaces approximately 30 H100 nodes for large-scale training.
RTX 4090 (Still Relevant)
The RTX 4090 still refuses to retire — the cheapest FP8 compute per dollar for teams willing to tile workloads across consumer cards, at a published $0.34/hour on RunPod Community Cloud as of 13 October 2026.
H100 Pricing: Same GPU, 3.1x the Price
Every figure below is a published on-demand list rate for an NVIDIA H100 80GB SXM, quoted per GPU-hour, in a US region, read off the provider’s own pricing page on October 13, 2026. No committed-use discount, no reserved term, no spot or preemptible tier.
Three providers only sell the GPU as a full 8-GPU node. For those we divided the node rate by 8 and show the arithmetic, because a per-instance number compared against a per-GPU number is how these tables go wrong.
| Provider | Per GPU-hour | Pricing basis | Source |
|---|---|---|---|
| RunPod (Secure Cloud) | $3.99 | Quoted per GPU, H100 SXM. Community Cloud lists $2.69, on hosts without an enterprise SLA. | runpod.io/pricing |
| Lambda | $3.99 | Quoted per GPU on the 8x H100 SXM instance. Smaller 1x, 2x and 4x shapes list higher, up to $4.29. | lambda.ai/pricing |
| CoreWeave | $6.16 | $49.24/hr for an 8-GPU HGX H100 instance, divided by 8. | coreweave.com/pricing |
| AWS | $6.88 | $55.04/hr for p5.48xlarge (8 GPUs), us-east-1, divided by 8. Reflects the 44% P5 price cut AWS made in June 2025. | aws.amazon.com/ec2/pricing |
| Google Cloud | $11.06 | $88.49/hr for a3-highgpu-8g (8 GPUs), us-central1, divided by 8. The 1x, 2x and 4x A3 shapes are Spot or Flex-start only. | cloud.google.com/compute/gpus-pricing |
| Azure | $12.29 | $98.32/hr for ND96isr H100 v5 (8 GPUs), US East, Linux, divided by 8. There is no single-GPU ND SKU. | azure.microsoft.com/pricing |
Vast.ai is missing from the table on purpose. It runs a marketplace with no fixed list rate, so there is no published number to quote next to the six above. On September 12, 2026 its on-demand H100 SXM offers started around $1.80 per GPU-hour, sourced from independent hosts with no common SLA or InfiniBand fabric. vast.ai/pricing
Cheapest to most expensive: $8.30 per GPU-hour. Across a 730-hour month that is $6,059 per GPU. On the 8-GPU node every hyperscaler actually sells, the gap comes to $48,472 a month for the same chip.
Median of the six list rates: $6.52 per GPU-hour. Mean: $7.40. Both sit well above the $2 to $4 band that most 2025-vintage comparison tables still quote, because those tables mix spot and community-tier rates into an on-demand column.
Why the gap exists: AWS cut P5 on-demand by 44% in June 2025 and Azure and Google never followed, so the hyperscaler tier split in half. Underneath it, the GPU-specialist clouds price against each other rather than against AWS. You are paying for ecosystem depth, enterprise SLA, compliance certifications, and regional coverage. Whether any of that is worth 3.1x depends on your workload, and most teams never run the comparison.
When to Rent, When to Buy, When to Colocate
Rent: Variable workloads, prototyping, burst capacity
On-demand GPU rental is the right choice when:
- ✓Your workload runs fewer than 8 hours per day
- ✓You need to scale GPU count up or down week-to-week
- ✓You are evaluating multiple GPU types before committing
- ✓Your team needs different hardware for different projects
Median list rate (October 2026): $6.52 per GPU-hour for H100 80GB on-demand across the six providers above. Use GYGO’s rent comparison to find live pricing →
Buy: Sustained workloads, predictable utilization
Purchase becomes cheaper than cloud rental when:
- ✓Workload runs 6+ months at 70%+ utilization
- ✓You have in-house IT to manage hardware
- ✓You can place the hardware in a facility with adequate power and cooling
Named reseller listings, read 13 October 2026:
- NVIDIA H100 80GB SXM5: $289,000 for a complete 8-GPU HGX H100 server (Supermicro SYS-821GE-TNHR at Vipera), or $36,125 per GPU deployed
- NVIDIA H100 80GB PCIe: $32,000 per card at CDW in October 2023, as ServeTheHome recorded it; no named reseller shows a fetchable 2026 price
- NVIDIA A100 80GB PCIe: $16,535 SabrePC list price, shown out of stock; in-stock new cards listed higher
- NVIDIA RTX 4090: $4,399 per new card on Amazon as tracked by GPUDojo, against NVIDIA’s $1,599 launch price
No named reseller publishes an MI300X price — it is quote-only everywhere we checked, so we do not list one. NVIDIA and AMD publish no MSRP for datacentre parts, so none of these are list prices, and the SXM5 module is not sold on its own, so the per-GPU figure is the complete server divided by eight.
An H100 bought at $36,125 (one eighth of the server) and run at 80% utilization avoids $3,808 of rental a month at the $6.52 median, so the card pays for itself in about 9.5 months. Price it against Azure’s $12.29 and the payback drops to 5.0 months. Against RunPod’s $3.99 it stretches to 15.5 months. Those figures cover the card alone; power, cooling and rack space are the colocation line below. Browse GPU hardware for purchase →
Place (Colocation): Owned hardware, third-party facilities
GPU colocation — placing your owned hardware in a data center that provides power, cooling, and connectivity — is consistently the highest-ROI option for teams with 6+ months of sustained workload. Published 2026 rate guides put high-density air-cooled racks at $120–$350 per kW per month across the primary US markets, before cross-connects, remote hands and power billing.
The math on a 40 kW GPU rack:
- Holds roughly three to four DGX H100 systems, so 24 to 32 H100 GPUs at about 10.2 kW per system
- Colocation cost: $4,800–$14,000/month (facility fees at $120–$350/kW)
- Hardware depreciated over 3 years: varies by configuration
- Equivalent cloud spend for the same 24 to 32 GPUs at the $6.52 median list rate: $114,000–$152,000/month
Buying 24 to 32 H100s at $36,125 a GPU, one eighth of a complete 8-GPU server, costs $867,000 to $1,156,000. Set that against the cloud spend it replaces, net of the rack fee, and colocation pays the hardware back in roughly 8 months at the median list rate, or about 4 months if you are moving off Azure. Find colocation facilities via GYGO Place →
AMD MI300X vs NVIDIA H100: The Real 2026 Comparison
The AMD vs NVIDIA debate has become more legitimate than the GPU community expected.
MI300X Advantages
- +192 GB HBM3 unified memory enables large models that cannot fit on H100’s 80 GB
- +15–25% lower per-hour cost on most spot markets
- +Competitive inference throughput on transformer workloads per MLPerf 4.0
H100 Advantages
- +Mature CUDA ecosystem and software support
- +Wider provider availability: every provider in this comparison publishes an H100 rate; none of the six publishes an MI300X rate
- +Proven at scale for distributed training clusters
Our Recommendation
For inference on large models (70B+ parameters), MI300X is worth evaluating — the memory capacity advantage is real and the cost delta matters at scale. For training from scratch with complex model architectures, the CUDA ecosystem maturity still favors H100 unless your team has ROCm experience.
GB200 NVL72: Is It Worth It?
CoreWeave publishes the GB200 NVL72 at $42.00 per instance-hour for four Blackwell GPUs, which is $10.50 per GPU-hour (coreweave.com/pricing, October 13, 2026). A full NVL72 rack is 36 Superchips carrying 72 Blackwell GPUs, so about $756 an hour at that rate. Most other providers quote GB200 on request rather than publishing a list price.
When GB200 Makes Sense
- →Training runs longer than 30 days on models with 100B+ parameters
- →Inference for frontier-scale models at production traffic levels
- →Organizations willing to sign 12-month commitments for best pricing
For most teams reading this post: the H100 or H200 remains the right choice. GB200 economics require sustained high utilization at a scale that most organizations have not yet reached.
Frequently Asked Questions
Is GYGO a cloud provider itself, or just a comparison tool?
GYGO is a marketplace aggregator. We compare pricing, availability, and specifications from GPU cloud providers, hardware resellers, and colocation facilities. We do not operate our own GPU clusters. Our revenue model is based on provider partnerships, not charging users for comparisons.
How often is GYGO’s pricing data updated?
On-demand instance prices are refreshed hourly from provider APIs. Spot market prices are updated every 15 minutes. Hardware purchase prices are updated weekly from reseller data feeds.
Can GYGO help me negotiate bulk GPU cloud pricing?
GYGO surfaces public pricing data. For bulk commitments and enterprise negotiations, contact individual providers directly. We recommend using GYGO’s comparison data as a baseline before entering negotiations — most providers will match or beat documented competitor pricing for 6–12 month commitments.
What regions does GYGO cover?
GYGO covers GPU providers in North America, Europe, and Asia-Pacific. Colocation demand concentrates in a small set of metros: Synergy Research counted 20 metros holding about 60% of the global colocation market in August 2024, 8 of them in the US, 7 in Asia-Pacific, and 4 in Europe. GYGO works the US markets in its pricing table against your rack spec.
Does GYGO cover AI-specific cloud platforms like CoreWeave or SambaNova?
Yes. GYGO includes GPU-specialized providers that do not appear in general cloud marketplaces: Lambda Labs, CoreWeave, RunPod, Vast.ai, Fluidstack, and others. We also include hyperscaler GPU instances from AWS, Azure, and Google Cloud for complete comparison.
Start Your GPU Infrastructure Comparison
The same H100 sells for $3.99 and $12.29 an hour depending on whose invoice you are on. Comparing published rates before you sign a provider contract, a hardware order, or a colocation lease is the cheapest hour of work available to an infrastructure team this year.