Specifications Compared
| Spec | H100 | RTX-2070 |
|---|---|---|
| TDP | 700W | 175W |
| 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 | NVLink |
| Tensor Cores | 528 | 288 |
| FP8 Performance | 3,958 TFLOPS | |
| FP16 Performance | 1,979 TFLOPS | 7.5 TFLOPS |
| FP32 Performance | 67 TFLOPS | 7.5 TFLOPS |
| FP64 Performance | 34 TFLOPS | |
| INT8 Performance | 3,958 TOPS | |
| Memory Bandwidth | 3,350 GB/s | 448 GB/s |
Performance Analysis
Compute specifications reveal profound differences in real-world utility. The H100 NVL's 1979 TFLOPS FP16 accelerates AI training and inference using mixed precision, while its 67 TFLOPS FP32 handles traditional HPC tasks; the RTX 2070 SUPER's equal 9 TFLOPS in FP16 and FP32 limits it to smaller-scale operations like gaming or basic ML. The H100 NVL's FP8 at 3958 TFLOPS further optimizes low-precision inference for massive models. Memory bandwidth dictates batch size feasibility: 3350 GB/s on the H100 NVL supports enormous batches for efficient training convergence, whereas 496 GB/s on the RTX 2070 SUPER constrains datasets and prolongs runtimes. VRAM capacity mirrors this: 80 to 94 GB enables full-model loading on the H100 NVL, but 8 GB on the RTX 2070 SUPER requires heavy optimization or model sharding. Power draw underscores deployment contexts, with the H100 NVL at 700 W TDP for data centers versus the RTX 2070 SUPER's 215 W for desktops.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
H100 NVL
| 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 |
When to Choose the H100 NVL
Select the H100 NVL for demanding AI and HPC workloads. Its 80 to 94 GB VRAM and 3350 GB/s bandwidth handle large batch training of LLMs or scientific simulations infeasible on consumer hardware. Cloud availability from $1.40 per hour suits scalable, intermittent projects without capital expenditure.
When to Choose the RTX 2070 SUPER
The RTX 2070 SUPER fits gaming, content creation, or hobbyist ML on local machines. With 9 TFLOPS FP32 and 8 GB VRAM, it performs 1440p gaming or Stable Diffusion at 215 W TDP. Absence of cloud offers favors one-time purchases for persistent, low-intensity desktop use.
Use Cases
H100 NVL's 80-94 GB HBM3 VRAM and 1979 TFLOPS FP16 support full-scale training of billion-parameter models. RTX 2070 SUPER's 8 GB VRAM cannot accommodate such sizes.
3958 TFLOPS FP8 on H100 NVL speeds high-throughput inference for large models. RTX 2070 SUPER lacks FP8 and sufficient 496 GB/s bandwidth.
3350 GB/s bandwidth on H100 NVL enables large-batch fine-tuning for faster iterations. 496 GB/s on RTX 2070 SUPER bottlenecks efficiency.
RTX 2070 SUPER's 8 GB VRAM and 9 TFLOPS FP32 suffice for image generation at consumer scale. H100 NVL's 700 W TDP is unnecessary.
H100 NVL's 67 TFLOPS FP32 and NVLink interconnect scale complex simulations. RTX 2070 SUPER lacks multi-GPU bandwidth.
Frequently Asked Questions
What is the VRAM capacity of H100 NVL versus RTX 2070 SUPER?▾
H100 NVL provides 80-94 GB HBM3 VRAM, dwarfing the RTX 2070 SUPER's 8 GB GDDR6. This allows H100 NVL to load entire large models. Bandwidth reaches 3350 GB/s on H100 NVL versus 496 GB/s.
How do FP16 performances compare?▾
H100 NVL achieves 1979 TFLOPS FP16 for AI acceleration, versus 9 TFLOPS on RTX 2070 SUPER. FP32 is 67 TFLOPS on H100 NVL and 9 TFLOPS on RTX 2070 SUPER. These metrics highlight datacenter versus consumer focus.
What are the TDPs of these GPUs?▾
H100 NVL has a 700 W TDP requiring datacenter infrastructure. RTX 2070 SUPER uses 215 W suitable for desktops. Power differences affect deployment choices.
What cloud pricing exists for H100 NVL and RTX 2070 SUPER?▾
H100 NVL pricing starts at $1.40 per hour, averaging $2.89 per hour over nine offers. No live cloud offers appear for RTX 2070 SUPER. Local purchase applies for the latter.
Does RTX 2070 SUPER support FP8 compute?▾
RTX 2070 SUPER lacks FP8 capability, unlike H100 NVL's 3958 TFLOPS. It relies on FP16/FP32 at 9 TFLOPS each. This limits quantized inference efficiency.
Which GPU has better interconnects?▾
H100 NVL features NVLink, PCIe 5.0, and InfiniBand for multi-GPU scaling. RTX 2070 SUPER uses PCIe only. Interconnects enable H100 NVL for clusters.
Which is cheaper to rent, the H100 or the RTX 2070?▾
Cloud rental prices for both the H100 and RTX 2070 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 2070?▾
The H100 has 80 to 94 GB of HBM3 memory. The RTX 2070 has 8 GB of GDDR6 memory.
Can I find H100 and RTX 2070 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 2070?▾
The H100 uses the Hopper architecture (2022) while the RTX 2070 uses Turing (2018). The H100 delivers 263.9x the FP16 throughput and 7.5x the memory bandwidth of the RTX 2070.