Specifications Compared
| Spec | H200 | QUADRO-RTX-5000 |
|---|---|---|
| TDP | 700W | 230W |
| VRAM | 141 GB | 16 GB |
| CUDA Cores | 16,896 | 3,072 |
| Memory Type | HBM3e | GDDR6 |
| Architecture | Hopper | Turing |
| Form Factors | SXM, 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 | 4,800 GB/s | 448 GB/s |
Performance Analysis
The H200's FP16 performance of 1979 TFLOPS vastly outpaces the Quadro RTX 5000's 11.2 TFLOPS, enabling accelerated deep learning training where half-precision computations dominate: training times for large models shrink dramatically on the H200. Its FP32 throughput of 67 TFLOPS supports single-precision tasks 6 times faster than the Quadro's 11.2 TFLOPS, benefiting scientific simulations requiring precise floating-point operations.
Memory bandwidth defines practical limits: the H200's 4800 GB/s supports batch sizes up to 10 times larger than the Quadro RTX 5000's 448 GB/s, reducing overhead in inference pipelines and allowing models with billions of parameters to fit in 141 GB VRAM versus 16 GB. FP8 capability at 3958 TFLOPS on the H200 further optimizes inference for quantized LLMs, unavailable on the Turing-based Quadro. Higher TDP of 700W on the H200 demands robust cooling, unlike the 230W Quadro suited for compact setups.
These specs translate to real-world dominance in AI: the H200 handles enterprise-scale training infeasible on the Quadro, though the latter suffices for lighter visualization loads.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
H200
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vultr | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 72 vCPU 480GB RAM 960GB Storage | Atlanta | $1.99/GPU/hr | Available | ||
 Lambda Labs | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 64 vCPU 432GB RAM 4096GB Storage | Virginia | $2.29/GPU/hr | Available | ||
 Nebius | NVIDIA H200 SXM 141GB VRAM | 141GB | 16 vCPU 200GB RAM | 🌍Europe | $2.45/GPU/hr | |||
 CoreWeave | 8×NVIDIA H200 SXM 141GB VRAM | 141GB | 128 vCPU 0GB RAM 61440GB Storage | United States | $2.58/GPU/hr $20.64/hr total (8×) | |||
 Ori | 4×NVIDIA H200 SXM 141GB VRAM | 141GB | 96 vCPU 960GB RAM 12000GB Storage | London | $3.50/GPU/hr $14.00/hr total (4×) | 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 H200
The H200 excels in large-scale AI training and inference where 141 GB HBM3e VRAM accommodates massive models: users processing LLMs with over 100 billion parameters find the 4800 GB/s bandwidth essential for efficient data throughput. Cloud deployments leveraging NVLink and PCIe 5.0 interconnects benefit from its 1979 TFLOPS FP16 performance, ideal for hyperscale environments despite the 700W TDP.
High-performance computing clusters prioritize the H200 for FP8 inference at 3958 TFLOPS, enabling cost-effective scaling across 26 live cloud offers starting at $0.50 per hour.
When to Choose the Quadro RTX 5000
The Quadro RTX 5000 suits legacy workstation applications like CAD and 3D rendering, where 16 GB GDDR6 VRAM and 448 GB/s bandwidth meet moderate demands without overkill. Its PCIe form factor and 230W TDP integrate seamlessly into existing desktop or small-server setups, avoiding the H200's data center requirements.
Budget-conscious users favor its consistent $0.82 per hour cloud pricing across 2 offers for tasks not exceeding 11.2 TFLOPS in FP16 or FP32, ensuring compatibility with Turing-optimized software.
Use Cases
The H200's 141 GB VRAM and 1979 TFLOPS FP16 handle massive datasets and models infeasible on the Quadro RTX 5000's 16 GB and 11.2 TFLOPS.
FP8 performance of 3958 TFLOPS and 4800 GB/s bandwidth on the H200 enable high-throughput quantized inference, far surpassing the Quadro RTX 5000's capabilities.
Large batch sizes supported by 141 GB VRAM and 67 TFLOPS FP32 make the H200 ideal, while the Quadro RTX 5000's 16 GB limits model complexity.
The H200's superior FP16 at 1979 TFLOPS accelerates diffusion model generation; 141 GB VRAM supports high-resolution batches beyond the Quadro RTX 5000's 16 GB.
H200's 67 TFLOPS FP32 and 4800 GB/s bandwidth outperform the Quadro RTX 5000's 11.2 TFLOPS and 448 GB/s for memory-intensive simulations.
Frequently Asked Questions
What is the VRAM difference between H200 and Quadro RTX 5000?▾
The H200 offers 141 GB HBM3e VRAM, nearly 9 times more than the Quadro RTX 5000's 16 GB GDDR6. This enables larger models on the H200. Bandwidth follows suit at 4800 GB/s versus 448 GB/s.
Which has better FP16 performance: H200 or Quadro RTX 5000?▾
The H200 achieves 1979 TFLOPS in FP16, 176 times higher than the Quadro RTX 5000's 11.2 TFLOPS. This gap favors H200 for AI training. FP32 is 67 TFLOPS versus 11.2 TFLOPS.
How do cloud prices compare for H200 and Quadro RTX 5000?▾
H200 pricing starts at $0.50 per hour with an average of $3.62 per hour across 26 offers. Quadro RTX 5000 is $0.82 per hour average across 2 offers. H200 provides more options.
What are the TDP ratings of these GPUs?▾
The H200 has a 700W TDP suited for data centers. Quadro RTX 5000 uses 230W for workstations. Power needs reflect their architectures: Hopper versus Turing.
Is the H200 better for LLM inference than Quadro RTX 5000?▾
Yes, H200's FP8 at 3958 TFLOPS and 141 GB VRAM excel for LLM inference. Quadro RTX 5000 lacks FP8 and has only 16 GB VRAM. Bandwidth of 4800 GB/s aids H200 throughput.
What architectures power H200 and Quadro RTX 5000?▾
H200 uses Hopper from 2024. Quadro RTX 5000 employs Turing from 2018. This 6-year gap explains performance disparities like 1979 TFLOPS FP16 on H200.
Which is cheaper to rent, the H200 or the Quadro RTX 5000?▾
Cloud rental prices for both the H200 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 H200 have compared to the Quadro RTX 5000?▾
The H200 has 141 GB of HBM3e memory. The Quadro RTX 5000 has 16 GB of GDDR6 memory.
Can I find H200 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 H200 and the Quadro RTX 5000?▾
The H200 uses the Hopper architecture (2024) while the Quadro RTX 5000 uses Turing (2018). The H200 delivers 176.7x the FP16 throughput and 10.7x the memory bandwidth of the Quadro RTX 5000.