Specifications Compared
| Spec | H100 | QUADRO-RTX-5000 |
|---|---|---|
| TDP | 700W | 230W |
| VRAM | 80-94 GB | 16 GB |
| CUDA Cores | 16,896 | 3,072 |
| Memory Type | HBM3 | GDDR6 |
| Architecture | Hopper | Turing |
| Form Factors | SXM5, PCIe, NVL | PCIe |
| Interconnect | NVLink, PCIe 5.0, InfiniBand | NVLink |
| Tensor Cores | 528 | 384 |
| FP8 Performance | 3,958 TFLOPS | |
| FP16 Performance | 1,979 TFLOPS | 11.2 TFLOPS |
| FP32 Performance | 67 TFLOPS | 11.2 TFLOPS |
| FP64 Performance | 34 TFLOPS | |
| INT8 Performance | 3,958 TOPS | |
| Memory Bandwidth | 3,350 GB/s | 448 GB/s |
Performance Analysis
The H100's FP16 performance of 1979 TFLOPS vastly outpaces the Quadro RTX 5000's 11.2 TFLOPS, accelerating machine learning training by handling mixed-precision computations at scales unattainable on Turing hardware. For inference, H100's FP8 capability at 3958 TFLOPS further widens the gap, enabling real-time deployment of large language models with minimal latency. FP32 at 67 TFLOPS on H100 supports scientific simulations, compared to 11.2 TFLOPS on Quadro RTX 5000.
Memory differences prove critical: H100's 80 to 94 GB HBM3 allows batch sizes for models exceeding 70 billion parameters, while Quadro RTX 5000's 16 GB GDDR6 limits to smaller batches around 1 to 7 billion. Bandwidth of 3350 GB/s on H100 minimizes data bottlenecks in training loops, versus 448 GB/s on Quadro RTX 5000, which causes stalls in memory-intensive tasks. Power draw reflects this: H100 at 700W suits datacenters, Quadro RTX 5000 at 230W fits workstations.
These specs translate to H100 completing AI training epochs in minutes where Quadro RTX 5000 requires hours, reshaping workflows for modern deep learning.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
H100
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Hyperstack | 4×NVIDIA H100 PCIe 80GB VRAM | 80GB | 124 vCPU 720GB RAM 3300GB Storage | Canada | $1.90/GPU/hr $7.60/hr total (4×) | Available | ||
Hyperstack | 2×NVIDIA H100 PCIe 80GB VRAM | 80GB | 60 vCPU 360GB RAM 1600GB Storage | Canada | $1.90/GPU/hr $3.80/hr total (2×) | Available | ||
Hyperstack | 8×NVIDIA H100 PCIe 80GB VRAM | 80GB | 252 vCPU 1440GB RAM 6600GB Storage | Canada | $1.90/GPU/hr $15.20/hr total (8×) | Available | ||
Hyperstack | NVIDIA H100 PCIe 80GB VRAM | 80GB | 28 vCPU 180GB RAM 850GB Storage | Canada | $1.90/GPU/hr | Available | ||
Hyperstack | 8×NVIDIA H100 PCIe 80GB VRAM | 80GB | 252 vCPU 1440GB RAM 6600GB Storage | Canada | $1.95/GPU/hr $15.60/hr total (8×) | Available |
Quadro RTX 5000
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Paperspace | NVIDIA Quadro RTX 5000 16GB VRAM | 16GB | 8 vCPU 30GB RAM 50GB Storage | New York | $0.82/GPU/hr | Available | ||
Paperspace | 2×NVIDIA Quadro RTX 5000 16GB VRAM | 16GB | 16 vCPU 60GB RAM 50GB Storage | New York | $0.82/GPU/hr $1.64/hr total (2×) | Available |
When to Choose the H100
Opt for the H100 in large-scale AI training and inference scenarios: its 1979 TFLOPS FP16 and 80 to 94 GB VRAM handle models like GPT-scale transformers without splitting. Datacenter users benefit from 3350 GB/s bandwidth for high-throughput batch processing across NVLink or PCIe 5.0 interconnects.
Scientific computing demanding 67 TFLOPS FP32 or FP8 at 3958 TFLOPS favors H100, especially in cloud at $0.80 per hour starting rates for short bursts.
When to Choose the Quadro RTX 5000
Select the Quadro RTX 5000 for budget-conscious professional visualization and CAD: its 16 GB GDDR6 suffices for rendering complex scenes at 11.2 TFLOPS FP32. Lower 230W TDP and PCIe form factor suit on-premises workstations without datacenter cooling.
Light inference or legacy software incompatible with Hopper excels here, with cloud pricing at a steady $0.82 per hour across available offers.
Use Cases
H100's 1979 TFLOPS FP16 and 80 to 94 GB HBM3 enable training billion-parameter models in feasible timeframes. Quadro RTX 5000's 11.2 TFLOPS and 16 GB VRAM cannot handle required batch sizes.
H100's 3958 TFLOPS FP8 supports high-throughput serving of large models. Quadro RTX 5000 lacks the memory bandwidth of 3350 GB/s for efficient real-time queries.
H100's 67 TFLOPS FP32 and vast VRAM accelerate parameter-efficient fine-tuning on datasets exceeding 16 GB. Quadro RTX 5000 struggles with memory constraints.
H100 generates images rapidly via 1979 TFLOPS FP16 for diffusion steps. Quadro RTX 5000's lower 11.2 TFLOPS limits to slower, smaller-scale generation.
H100's 3350 GB/s bandwidth and 700W TDP optimize simulations at 67 TFLOPS FP32. Quadro RTX 5000's 448 GB/s proves inadequate for large-scale computations.
Frequently Asked Questions
Which has more VRAM: H100 or Quadro RTX 5000?▾
The H100 offers 80 to 94 GB HBM3 VRAM, far exceeding the Quadro RTX 5000's 16 GB GDDR6. This enables H100 to process larger models without offloading. Quadro RTX 5000 suits smaller datasets only.
How does H100 compare to Quadro RTX 5000 in FP16 performance?▾
H100 delivers 1979 TFLOPS FP16, over 176 times the Quadro RTX 5000's 11.2 TFLOPS. This gap accelerates AI training significantly on H100. Workstation tasks see less disparity.
What is the memory bandwidth difference?▾
H100 provides 3350 GB/s, about 7.5 times the Quadro RTX 5000's 448 GB/s. Higher bandwidth on H100 reduces training bottlenecks. Quadro RTX 5000 handles lighter loads adequately.
Which GPU is cheaper in the cloud?▾
Both start near $0.80 to $0.82 per hour, but H100 averages $3.21 across 56 offers while Quadro RTX 5000 stays at $0.82 across 2. Short tasks favor H100's availability. Budget runs prefer Quadro RTX 5000.
What are the power requirements?▾
H100 demands 700W TDP for datacenter use, versus Quadro RTX 5000's 230W for workstations. H100 requires robust cooling infrastructure. Quadro RTX 5000 fits standard PCIe slots easily.
Can Quadro RTX 5000 do AI training?▾
Quadro RTX 5000 manages small-scale training at 11.2 TFLOPS FP16 with 16 GB VRAM. It falters on models needing over 16 GB or high throughput. H100 excels universally.
Which is cheaper to rent, the H100 or the Quadro RTX 5000?▾
Cloud rental prices for both the H100 and Quadro RTX 5000 vary by provider, configuration, and availability. This page shows live pricing from 25+ providers updated every 60 seconds. Scroll to the Live Cloud Pricing section to compare current rates.
How much VRAM does the H100 have compared to the Quadro RTX 5000?▾
The H100 has 80 to 94 GB of HBM3 memory. The Quadro RTX 5000 has 16 GB of GDDR6 memory.
Can I find H100 and Quadro RTX 5000 GPUs available to rent right now?▾
Yes. This page shows real-time availability across 25+ cloud GPU providers. The Live Cloud Pricing section displays only in-stock offers with current pricing.
What is the main difference between the H100 and the Quadro RTX 5000?▾
The H100 uses the Hopper architecture (2022) while the Quadro RTX 5000 uses Turing (2018). The H100 delivers 176.7x the FP16 throughput and 7.5x the memory bandwidth of the Quadro RTX 5000.