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
Memory specifications dictate real-world viability for AI workloads: the H100's 80 to 94 GB HBM3 VRAM supports massive models and batch sizes, while the RTX 2070's 8 GB GDDR6 limits it to smaller datasets. Bandwidth amplifies this, as 3350 GB/s on the H100 enables rapid data movement for training large language models, compared to 448 GB/s on the RTX 2070 which bottlenecks high-throughput inference.
Floating-point performance reveals training and inference implications: H100's 1979 TFLOPS FP16 accelerates mixed-precision training by orders of magnitude over the RTX 2070's 7.5 TFLOPS, reducing epochs from days to hours for billion-parameter models. The H100's 67 TFLOPS FP32 suits precise scientific simulations, exceeding the RTX 2070's 7.5 TFLOPS, while FP8 at 3958 TFLOPS optimizes low-precision inference. Overall, the H100 handles enterprise-scale tasks; the RTX 2070 fits prototyping.
Power efficiency ties into deployment: the H100's 700W TDP demands robust cooling in multi-GPU clusters, yet yields 2.8x FP16 TFLOPS per watt over the RTX 2070's 175W setup.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
H100 SXM5
| 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 | ||
 Voltage Park | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 208 vCPU 928GB RAM 19200GB Storage | Dallas, Texas | $1.99/GPU/hr $15.92/hr total (8×) |
When to Choose the H100 SXM5
Select the H100 SXM5 for large-scale AI training and inference: its 80 to 94 GB VRAM accommodates models exceeding 70B parameters, and 3350 GB/s bandwidth supports batch sizes over 1000. Datacenter users benefit from 1979 TFLOPS FP16 for accelerating LLM fine-tuning in hours rather than weeks. Cloud deployments at $0.80 per hour justify costs for production pipelines.
When to Choose the RTX 2070
Opt for the RTX 2070 in budget-conscious prototyping: 8 GB VRAM suffices for models under 7B parameters, and 7.5 TFLOPS FP16 handles small-scale inference at $0.02 per hour. Its 175W TDP enables easy desktop or edge setups without datacenter infrastructure. Gamers and hobbyists leverage it for Stable Diffusion or light gaming alongside ML experiments.
Use Cases
The H100's 80 to 94 GB VRAM and 1979 TFLOPS FP16 handle billion-parameter models with large batch sizes via 3350 GB/s bandwidth. The RTX 2070's 8 GB VRAM cannot support such scales.
H100's 3958 TFLOPS FP8 and high bandwidth enable high-throughput serving for 70B+ models. RTX 2070's 7.5 TFLOPS limits it to sub-7B models at low concurrency.
H100 accelerates fine-tuning of large models with 67 TFLOPS FP32 precision. RTX 2070 works for small models but slows larger ones due to memory constraints.
RTX 2070's 8 GB VRAM generates 512x512 images efficiently at 7.5 TFLOPS FP16. H100's capacity exceeds needs for this consumer task, inflating costs.
H100's 67 TFLOPS FP32 and 3350 GB/s bandwidth speed simulations like molecular dynamics. RTX 2070's lower specs extend compute times significantly.
Frequently Asked Questions
What is the VRAM difference between H100 SXM5 and RTX 2070?▾
The H100 SXM5 offers 80 to 94 GB HBM3 VRAM, enabling large model handling. The RTX 2070 provides 8 GB GDDR6, suitable only for smaller workloads. This 10x plus gap impacts batch sizes in training.
How do FP16 performance numbers compare?▾
H100 SXM5 delivers 1979 TFLOPS FP16 for rapid AI training. RTX 2070 achieves 7.5 TFLOPS, over 260x slower. This favors H100 in deep learning acceleration.
What are the cloud rental prices?▾
H100 SXM5 rents from $0.80 per hour, averaging $3.56 per hour across 33 offers. RTX 2070 starts at $0.02 per hour, averaging $0.04 per hour over 2 offers. Budget tasks favor the latter.
Is H100 more power-hungry?▾
Yes, H100 SXM5 has 700W TDP for datacenter use. RTX 2070 draws 175W, ideal for consumer setups. Efficiency metrics show H100's superior TFLOPS per watt.
Which has higher memory bandwidth?▾
H100 SXM5 provides 3350 GB/s, supporting massive data flows. RTX 2070 offers 448 GB/s, limiting high-batch operations. Bandwidth drives H100's inference speed.
Can RTX 2070 handle LLM inference?▾
RTX 2070 manages small LLMs under 7B parameters with 8 GB VRAM. Larger models require H100's 80 to 94 GB. Quantization extends RTX 2070 viability modestly.
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.