Specifications Compared
| Spec | H100 | RTX-5000-ADA |
|---|---|---|
| TDP | 700W | 250W |
| VRAM | 80-94 GB | 32 GB |
| CUDA Cores | 16,896 | 12,800 |
| Memory Type | HBM3 | GDDR6 |
| Architecture | Hopper | Ada Lovelace |
| Form Factors | SXM5, PCIe, 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 | 3,350 GB/s | 576 GB/s |
Performance Analysis
H100's FP16 throughput of 1979 TFLOPS vastly outpaces RTX 5000 Ada's 65.3 TFLOPS, accelerating deep learning training by enabling larger models and batches without precision loss. The FP32 performance gap, 67 TFLOPS for H100 versus 65.3 TFLOPS for RTX 5000 Ada, is minimal, but H100's memory bandwidth of 3350 GB/s versus 576 GB/s allows massive batch sizes in training, reducing iterations and time for LLMs exceeding 32 GB VRAM.
For inference, H100's FP8 at 3958 TFLOPS supports quantized models at scale, handling high concurrency that RTX 5000 Ada cannot match due to VRAM limits. Lower bandwidth on RTX constrains data movement, slowing workflows with large datasets, while H100's 700W TDP versus 250W reflects its datacenter focus versus workstation efficiency.
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 | |
|---|---|---|---|---|---|---|---|---|
 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 |
RTX 5000 Ada Generation
| 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 H100 PCIe
Choose the H100 PCIe for large-scale LLM training or inference where 80-94 GB HBM3 VRAM accommodates models like GPT variants, and 3350 GB/s bandwidth sustains high throughput at $1.25/hr starting price. It excels in multi-GPU clusters via NVLink, ideal for research labs processing terabyte-scale data.
When to Choose the RTX 5000 Ada Generation
Opt for RTX 5000 Ada Generation in budget-conscious setups for fine-tuning smaller models or Stable Diffusion, leveraging 32 GB GDDR6 at $0.25/hr. Its 250W TDP suits edge deployments or single-node workstations without extensive cooling.
Use Cases
H100's 1979 TFLOPS FP16 and 80-94 GB VRAM enable training of billion-parameter models with large batches, far beyond RTX 5000 Ada's 65.3 TFLOPS and 32 GB limits.
H100's 3958 TFLOPS FP8 and 3350 GB/s bandwidth support high-concurrency quantized inference for large LLMs, outperforming RTX 5000 Ada's capacity.
For models up to 94 GB, H100 accelerates fine-tuning via superior FP16; RTX 5000 Ada suffices only for sub-32 GB tasks.
RTX 5000 Ada's 32 GB VRAM and 65.3 TFLOPS FP16 handle image generation efficiently at low $0.25/hr cost, matching typical needs.
H100 dominates FP32-heavy simulations at 67 TFLOPS with high bandwidth; RTX 5000 Ada fits lighter tasks at 65.3 TFLOPS and lower power.
Frequently Asked Questions
Which GPU has more VRAM?▾
The H100 PCIe offers 80-94 GB HBM3 VRAM, compared to RTX 5000 Ada Generation's 32 GB GDDR6. This makes H100 suitable for larger models.
What is the performance difference in FP16?▾
H100 achieves 1979 TFLOPS in FP16, while RTX 5000 Ada reaches 65.3 TFLOPS. The gap favors H100 for AI training.
How do cloud prices compare?▾
H100 PCIe starts at $1.25/hr average $2.59/hr across 22 offers; RTX 5000 Ada at $0.25/hr average $0.51/hr across 5. RTX is far cheaper.
Which has higher memory bandwidth?▾
H100 provides 3350 GB/s, versus RTX 5000 Ada's 576 GB/s. Higher bandwidth on H100 boosts large-batch processing.
What are the TDP ratings?▾
H100 has 700W TDP for datacenter use; RTX 5000 Ada uses 250W, ideal for workstations.
Which is better for inference?▾
H100's 3958 TFLOPS FP8 excels in high-volume inference; RTX 5000 Ada works for smaller-scale needs.
Which is cheaper to rent, the H100 or the RTX 5000 Ada?▾
Cloud rental prices for both the H100 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 H100 have compared to the RTX 5000 Ada?▾
The H100 has 80 to 94 GB of HBM3 memory. The RTX 5000 Ada has 32 GB of GDDR6 memory.
Can I find H100 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 H100 and the RTX 5000 Ada?▾
The H100 uses the Hopper architecture (2022) while the RTX 5000 Ada uses Ada Lovelace (2023). The H100 delivers 30.3x the FP16 throughput and 5.8x the memory bandwidth of the RTX 5000 Ada.