Specifications Compared
| Spec | H200 | RTX-5000-ADA |
|---|---|---|
| TDP | 700W | 250W |
| VRAM | 141 GB | 32 GB |
| CUDA Cores | 16,896 | 12,800 |
| Memory Type | HBM3e | GDDR6 |
| Architecture | Hopper | Ada Lovelace |
| Form Factors | SXM, NVL | PCIe |
| Interconnect | NVLink, PCIe 5.0, InfiniBand | |
| Tensor Cores | 528 | 400 |
| FP8 Performance | 3,958 TFLOPS | |
| FP16 Performance | 1,979 TFLOPS | 65.3 TFLOPS |
| FP32 Performance | 67 TFLOPS | 65.3 TFLOPS |
| FP64 Performance | 34 TFLOPS | |
| INT8 Performance | 3,958 TOPS | 1,044 TOPS |
| Memory Bandwidth | 4,800 GB/s | 576 GB/s |
Performance Analysis
Compute disparities favor the H200 profoundly for AI tasks. Its 1979 TFLOPS FP16 performance enables rapid matrix multiplications in training, far exceeding the RTX 5000 Ada's 65.3 TFLOPS; FP8 at 3958 TFLOPS on H200 accelerates quantized inference models. FP32 parity at 67 TFLOPS versus 65.3 TFLOPS means similar scalar compute, but H200's tensor cores amplify deep learning gains.
VRAM capacity dictates model scale: 141 GB HBM3e on H200 supports billion-parameter LLMs without splitting, unlike 32 GB GDDR6 on RTX 5000 Ada limiting to smaller models. Bandwidth of 4800 GB/s versus 576 GB/s allows H200 larger batch sizes, reducing training epochs by minimizing data stalls; RTX 5000 Ada suits smaller batches in inference.
Power draw underscores deployment: H200's 700W TDP demands rack-scale cooling, while RTX 5000 Ada's 250W fits desktops. Interconnects like NVLink on H200 enable multi-GPU scaling absent on PCIe-only RTX 5000 Ada.
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 |
RTX 5000 Ada
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA RTX 5000 Ada Generation 32GB VRAM | 32GB | 0 vCPU 0GB RAM | Chubbuck, Idaho | $0.55/GPU/hr | Available | ||
 RunPod | NVIDIA RTX 5000 Ada Generation 32GB VRAM | 32GB | 10 vCPU 83GB RAM | 🌍global | $0.83/GPU/hr |
When to Choose the H200
The H200 excels in large-scale LLM training and inference. Its 141 GB VRAM and 4800 GB/s bandwidth handle models exceeding 100B parameters with batch sizes impossible on 32 GB RTX 5000 Ada. NVLink interconnect supports multi-GPU clusters for distributed training at 1979 TFLOPS FP16.
Enterprise HPC favors H200's 3958 TFLOPS FP8 for quantized inference serving high throughput.
When to Choose the RTX 5000 Ada
The RTX 5000 Ada suits budget-conscious workstations for fine-tuning or visualization. At $0.25/hr average $0.51/hr, it undercuts H200's $3.62/hr by 86 percent, with 250W TDP enabling single-node setups. 65.3 TFLOPS FP16/FP32 handles Stable Diffusion or small-model inference without datacenter overhead.
Use Cases
H200's 141 GB VRAM and 1979 TFLOPS FP16 support massive models and large batches. RTX 5000 Ada's 32 GB limits scale.
141 GB HBM3e and 3958 TFLOPS FP8 enable high-throughput serving of large LLMs. RTX 5000 Ada's 32 GB GDDR6 restricts model size.
H200's 4800 GB/s bandwidth accelerates gradient updates on datasets fitting 141 GB. RTX 5000 Ada suffices only for small models.
RTX 5000 Ada's 65.3 TFLOPS FP16 and lower $0.51/hr cost handle image generation efficiently. H200 overkill for 32 GB needs.
H200's 67 TFLOPS FP32 and NVLink scaling boost simulations. RTX 5000 Ada's PCIe limits multi-node work.
Frequently Asked Questions
Which GPU has more VRAM?▾
The H200 offers 141 GB HBM3e VRAM. RTX 5000 Ada provides 32 GB GDDR6. This enables H200 to load larger models without partitioning.
How do prices compare?▾
H200 starts at $0.50/hr averaging $3.62/hr across 26 offers. RTX 5000 Ada begins at $0.25/hr averaging $0.51/hr over 5 offers. RTX saves costs for light use.
What is the FP16 performance difference?▾
H200 delivers 1979 TFLOPS FP16. RTX 5000 Ada achieves 65.3 TFLOPS. H200 accelerates AI training by over 30 times.
Which has higher memory bandwidth?▾
H200 provides 4800 GB/s. RTX 5000 Ada has 576 GB/s. Higher bandwidth on H200 supports bigger batches.
What are the TDP ratings?▾
H200 requires 700W TDP for datacenter use. RTX 5000 Ada uses 250W fitting workstations. Lower TDP eases RTX deployment.
Best for multi-GPU setups?▾
H200 supports NVLink and PCIe 5.0 for scaling. RTX 5000 Ada uses PCIe only. H200 excels in clusters.
Which is cheaper to rent, the H200 or the RTX 5000 Ada?▾
Cloud rental prices for both the H200 and RTX 5000 Ada 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 RTX 5000 Ada?▾
The H200 has 141 GB of HBM3e memory. The RTX 5000 Ada has 32 GB of GDDR6 memory.
Can I find H200 and RTX 5000 Ada 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 RTX 5000 Ada?▾
The H200 uses the Hopper architecture (2024) while the RTX 5000 Ada uses Ada Lovelace (2023). The H200 delivers 30.3x the FP16 throughput and 8.3x the memory bandwidth of the RTX 5000 Ada.