Specifications Compared
| Spec | H100 | QUADRO-RTX-4000 |
|---|---|---|
| TDP | 700W | 160W |
| VRAM | 80-94 GB | 8 GB |
| CUDA Cores | 16,896 | 2,304 |
| Memory Type | HBM3 | GDDR6 |
| Architecture | Hopper | Turing |
| Form Factors | SXM5, PCIe, NVL | PCIe |
| Interconnect | NVLink, PCIe 5.0, InfiniBand | |
| Tensor Cores | 528 | 288 |
| FP8 Performance | 3,958 TFLOPS | |
| FP16 Performance | 1,979 TFLOPS | 7.1 TFLOPS |
| FP32 Performance | 67 TFLOPS | 7.1 TFLOPS |
| FP64 Performance | 34 TFLOPS | |
| INT8 Performance | 3,958 TOPS | |
| Memory Bandwidth | 3,350 GB/s | 416 GB/s |
Performance Analysis
The H100 PCIe dominates in compute throughput: its 1979 TFLOPS FP16 vastly outpaces the Quadro RTX 4000's 7.1 TFLOPS, enabling faster AI model training where half-precision operations prevail. FP32 performance further highlights the gap at 67 TFLOPS versus 7.1 TFLOPS, benefiting single-precision tasks in scientific simulations. The FP16 to FP32 delta on H100 supports mixed-precision training workflows, reducing time for large-scale deep learning by leveraging hardware tensor cores.
Memory bandwidth defines practical limits: H100's 3350 GB/s allows massive batch sizes for training billion-parameter models, while Quadro's 416 GB/s restricts it to smaller datasets. This disparity affects inference too, with H100's 3958 TFLOPS FP8 throughput accelerating quantized deployments. Higher TDP of 700W on H100 versus 160W on Quadro reflects power demands for sustained peak performance in datacenter racks, influencing cloud suitability for intensive versus intermittent workloads.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
H100 PCIe
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 QuantaCloud Partner | H100 PCIe 32–1024+ GPUs · InfiniBand | ∞ | Custom configs | Multiple DCs | Reserved / cluster Get a quote in 24h | Available | ||
 Nebius | NVIDIA H100 SXM5 80GB VRAM | 80GB | 16 vCPU 200GB RAM | 🌍Europe | $2.15/GPU/hr | |||
 Vast.ai | NVIDIA H100 SXM5 80GB VRAM | 80GB | 128 vCPU 126GB RAM 1457GB Storage | Netherlands | $2.20/GPU/hr | Available | ||
 Denvr | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 208 vCPU 1024GB RAM 22800GB Storage | Virginia | $2.30/GPU/hr $18.40/hr total (8×) | |||
 CoreWeave | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 128 vCPU 0GB RAM 61440GB Storage | United States | $2.44/GPU/hr $19.51/hr total (8×) | |||
 Cirrascale | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 192 vCPU 2048GB RAM 39738GB Storage | United States | $2.49/GPU/hr $19.92/hr total (8×) |
Quadro RTX 4000
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Paperspace | NVIDIA Quadro RTX 4000 8GB VRAM | 8GB | 8 vCPU 30GB RAM 50GB Storage | Amsterdam | $0.56/GPU/hr | Available | ||
Paperspace | NVIDIA Quadro RTX 4000 8GB VRAM | 8GB | 8 vCPU 30GB RAM 50GB Storage | Canada | $0.56/GPU/hr | Available | ||
Paperspace | NVIDIA Quadro RTX 4000 8GB VRAM | 8GB | 8 vCPU 30GB RAM 50GB Storage | New York | $0.56/GPU/hr | Available | ||
Paperspace | 2×NVIDIA Quadro RTX 4000 8GB VRAM | 8GB | 16 vCPU 60GB RAM 50GB Storage | New York | $0.56/GPU/hr $1.12/hr total (2×) | Available | ||
Paperspace | 2×NVIDIA Quadro RTX 4000 8GB VRAM | 8GB | 16 vCPU 60GB RAM 50GB Storage | Canada | $0.56/GPU/hr $1.12/hr total (2×) | Available |
QuantaCloud
Comparing H-series providers? We broker across all of them.
Most Hopper capacity is sold out through Q3 2026. If you need 16+ GPUs reserved or a cluster in the next 90 days, we quote remaining H-series or B300 inventory at partner rates — one quote, 24h turnaround.
When to Choose the H100 PCIe
The H100 PCIe excels in AI training and large-scale inference: its 80 GB HBM3 VRAM handles models exceeding 8 GB GDDR6 limits on Quadro RTX 4000. Users processing FP16 workloads at 1979 TFLOPS benefit from rapid iterations, ideal for LLM development or scientific computing clusters. Cloud deployments at $1.25 per hour justify costs for high-throughput needs with NVLink interconnects.
When to Choose the Quadro RTX 4000
The Quadro RTX 4000 suits budget-conscious visualization tasks: its 160W TDP and $0.56 per hour pricing minimize operational costs for CAD or light rendering. Professionals running FP32 simulations at 7.1 TFLOPS find it adequate without H100's 700W demands. PCIe form factor ensures easy integration in workstation-like cloud instances for non-AI workflows.
Use Cases
H100's 80 GB HBM3 VRAM and 1979 TFLOPS FP16 support billion-parameter models with large batch sizes. Quadro RTX 4000's 8 GB GDDR6 limits scale severely.
3958 TFLOPS FP8 on H100 accelerates quantized serving at high throughput. Quadro lacks comparable efficiency for production inference.
67 TFLOPS FP32 and 3350 GB/s bandwidth enable efficient parameter updates on H100. Quadro's 7.1 TFLOPS proves inadequate for dataset-heavy fine-tuning.
H100's massive VRAM handles high-resolution generations without swapping. Quadro RTX 4000 restricts image sizes due to 8 GB limit.
H100's 67 TFLOPS FP32 outperforms Quadro's 7.1 TFLOPS for simulations. Bandwidth of 3350 GB/s supports complex datasets.
Frequently Asked Questions
How much faster is the H100 PCIe than Quadro RTX 4000 in FP16?▾
H100 PCIe achieves 1979 TFLOPS FP16 versus 7.1 TFLOPS on Quadro RTX 4000, roughly 279 times faster. This gap accelerates AI training significantly. Real-world gains depend on workload optimization.
What is the VRAM difference between H100 PCIe and Quadro RTX 4000?▾
H100 PCIe provides 80 GB HBM3, compared to 8 GB GDDR6 on Quadro RTX 4000. This enables larger models on H100. Bandwidth follows at 3350 GB/s versus 416 GB/s.
Which GPU has lower cloud pricing?▾
Quadro RTX 4000 averages $0.56 per hour across 5 offers, below H100 PCIe at $2.68 per hour average from 16 offers. H100 starts at $1.25 per hour. Choice depends on performance needs.
Can Quadro RTX 4000 handle AI training?▾
Quadro RTX 4000's 7.1 TFLOPS FP16 and 8 GB VRAM limit it to small models. H100's 1979 TFLOPS and 80 GB excel here. Use Quadro for prototyping only.
What are the power requirements?▾
H100 PCIe demands 700W TDP, far above Quadro RTX 4000's 160W. This affects datacenter cooling and costs. Quadro suits low-power cloud instances.
Is H100 PCIe backward compatible with Turing software?▾
H100 PCIe supports CUDA workloads from Turing era like Quadro RTX 4000. Hopper architecture enhances newer features. Verify drivers for optimal performance.
Which is cheaper to rent, the H100 or the Quadro RTX 4000?▾
Cloud rental prices for both the H100 and Quadro RTX 4000 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 4000?▾
The H100 has 80 to 94 GB of HBM3 memory. The Quadro RTX 4000 has 8 GB of GDDR6 memory.
Can I find H100 and Quadro RTX 4000 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 4000?▾
The H100 uses the Hopper architecture (2022) while the Quadro RTX 4000 uses Turing (2018). The H100 delivers 278.7x the FP16 throughput and 8.1x the memory bandwidth of the Quadro RTX 4000.