Specifications Compared
| Spec | H100 | RTX-3070 |
|---|---|---|
| TDP | 700W | 220W |
| VRAM | 80-94 GB | 8 GB |
| CUDA Cores | 16,896 | 5,888 |
| Memory Type | HBM3 | GDDR6 |
| Architecture | Hopper | Ampere |
| Form Factors | SXM5, PCIe, NVL | PCIe |
| Interconnect | NVLink, PCIe 5.0, InfiniBand | |
| Tensor Cores | 528 | 184 |
| FP8 Performance | 3,958 TFLOPS | |
| FP16 Performance | 1,979 TFLOPS | 20.3 TFLOPS |
| FP32 Performance | 67 TFLOPS | 20.3 TFLOPS |
| FP64 Performance | 34 TFLOPS | |
| INT8 Performance | 3,958 TOPS | |
| Memory Bandwidth | 3,350 GB/s | 448 GB/s |
Performance Analysis
The H100's FP16 performance of 1979 TFLOPS vastly exceeds the RTX 3070's 20.3 TFLOPS, making it ideal for machine learning training where half-precision computations accelerate gradient updates in deep neural networks. Its FP32 capability of 67 TFLOPS also surpasses the RTX 3070's 20.3 TFLOPS, supporting precise simulations, though the consumer card's balanced FP16 and FP32 suits graphics rendering equally well. This delta means the H100 processes training epochs far faster for large-scale models.
Memory bandwidth differences prove critical: the H100's 3350 GB/s allows massive batch sizes without bottlenecks, fitting models up to 80 to 94 GB VRAM, whereas the RTX 3070's 448 GB/s and 8 GB limit it to smaller batches and datasets. In inference scenarios, higher bandwidth on the H100 reduces latency for real-time serving of complex models. Power draw of 700W for the H100 versus 220W for the RTX 3070 influences deployment in dense clusters versus single-node setups.
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 |
When to Choose the H100 PCIe
Choose the H100 PCIe for enterprise-scale AI workloads requiring high throughput. Its 80 to 94 GB HBM3 VRAM and 3350 GB/s bandwidth handle large language models during training or inference, where the RTX 3070's 8 GB GDDR6 falls short. At $1.25 per hour starting price, it justifies the cost for teams needing 1979 TFLOPS FP16 performance across multi-GPU NVLink setups.
When to Choose the RTX 3070
Opt for the RTX 3070 in budget-conscious or lightweight applications. Its 20.3 TFLOPS FP16 and FP32 performance suffices for prototyping, gaming, or small-scale inference at $0.04 per hour. The 220W TDP and PCIe form factor enable easy integration in personal or edge computing without the H100's 700W demands.
Use Cases
The H100's 1979 TFLOPS FP16 and 80 to 94 GB HBM3 VRAM support training massive language models with large batch sizes. The RTX 3070's 8 GB VRAM and 20.3 TFLOPS cannot accommodate such scales.
High memory bandwidth of 3350 GB/s on the H100 enables low-latency serving of large models. The RTX 3070's 448 GB/s limits it to smaller models.
Fine-tuning medium models fits the RTX 3070's 8 GB VRAM and 20.3 TFLOPS for cost savings at $0.04 per hour. Larger fine-tunes benefit from H100's capacity.
The RTX 3070 handles image generation efficiently with 20.3 TFLOPS and 8 GB VRAM at low $0.09 per hour average. H100 overkill for consumer-scale diffusion tasks.
H100's 67 TFLOPS FP32 and 3350 GB/s bandwidth accelerate simulations with large datasets. RTX 3070 suits simpler computations only.
Frequently Asked Questions
What is the VRAM difference between H100 PCIe and RTX 3070?▾
The H100 PCIe provides 80 to 94 GB HBM3 VRAM, while the RTX 3070 has 8 GB GDDR6. This allows the H100 to load significantly larger models. Memory bandwidth follows suit at 3350 GB/s versus 448 GB/s.
How do their FP16 performances compare?▾
H100 achieves 1979 TFLOPS in FP16, compared to RTX 3070's 20.3 TFLOPS. This gap accelerates AI training on the H100. FP32 is 67 TFLOPS for H100 versus 20.3 TFLOPS for RTX 3070.
What are the cloud rental prices?▾
H100 PCIe starts at $1.25 per hour, averaging $2.75 per hour across 17 offers. RTX 3070 begins at $0.04 per hour, averaging $0.09 per hour over 4 offers. Prices reflect performance disparities.
Which has higher power consumption?▾
The H100 draws 700W TDP, far above the RTX 3070's 220W. This suits datacenter cooling for H100. Lower TDP makes RTX 3070 viable for consumer setups.
What architectures do they use?▾
H100 employs Hopper from 2022 with FP8 at 3958 TFLOPS. RTX 3070 uses Ampere from 2020. Hopper advances enable superior AI compute.
Can RTX 3070 handle large model training?▾
RTX 3070's 8 GB VRAM limits it to small models, unlike H100's 80 to 94 GB. Its 20.3 TFLOPS FP16 pales against 1979 TFLOPS. Use RTX 3070 for prototyping only.
Which is cheaper to rent, the H100 or the RTX 3070?▾
Cloud rental prices for both the H100 and RTX 3070 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 3070?▾
The H100 has 80 to 94 GB of HBM3 memory. The RTX 3070 has 8 GB of GDDR6 memory.
Can I find H100 and RTX 3070 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 3070?▾
The H100 uses the Hopper architecture (2022) while the RTX 3070 uses Ampere (2020). The H100 delivers 97.5x the FP16 throughput and 7.5x the memory bandwidth of the RTX 3070.