Specifications Compared
| Spec | GTX-1070 | H100 |
|---|---|---|
| TDP | 150W | 700W |
| VRAM | 8 GB | 80-94 GB |
| CUDA Cores | 1,920 | 16,896 |
| Memory Type | GDDR5 | HBM3 |
| Architecture | Pascal | Hopper |
| Form Factors | PCIe | SXM5, PCIe, NVL |
| Interconnect | NVLink, PCIe 5.0, InfiniBand | |
| FP16 Performance | 6.5 TFLOPS | 1,979 TFLOPS |
| FP32 Performance | 6.5 TFLOPS | 67 TFLOPS |
| Memory Bandwidth | 256 GB/s | 3,350 GB/s |
Performance Analysis
The computational disparity is profound: the H100 SXM5 achieves 1979 TFLOPS in FP16, exceeding the GTX 1070 Ti's 8.9 TFLOPS by a factor of 222. This gap transforms AI training and inference realities, as FP16 dominates mixed-precision workflows; large language model training on the GTX 1070 Ti would require days for tasks the H100 completes in minutes. FP32 on the H100 at 67 TFLOPS still outpaces the GTX 1070 Ti's 8.9 TFLOPS by over 7.5 times, benefiting scientific simulations and general compute. Memory bandwidth presents another chasm: 3350 GB/s on the H100 versus 308 GB/s on the GTX 1070 Ti, a 10.9-fold increase. This enables the H100 to process massive batch sizes in deep learning, accommodating models with billions of parameters without swapping to host memory, while the GTX 1070 Ti limits users to small batches and frequent data transfers. Power efficiency follows suit, with the H100's 700 W TDP yielding far higher throughput per watt in AI tasks.
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 | ||
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 GTX 1070 Ti
The GTX 1070 Ti suits legacy gaming setups or light local workloads like basic video rendering and hobbyist machine learning experiments. Its 180 W TDP and PCIe form factor integrate easily into consumer desktops without high power demands. With no cloud availability, it appeals to users avoiding rental costs for infrequent, low-intensity tasks under 8 GB VRAM.
When to Choose the H100 SXM5
The H100 SXM5 excels in enterprise AI deployments, including large-scale model training and high-throughput inference. Its 80 GB HBM3 VRAM and 3350 GB/s bandwidth handle massive datasets, while NVLink interconnects scale across multi-GPU clusters. Cloud access from $0.80 per hour makes it ideal for bursty, production-grade compute.
Use Cases
The H100 SXM5's 1979 TFLOPS FP16 and 80 GB HBM3 VRAM enable efficient training of billion-parameter models. The GTX 1070 Ti's 8.9 TFLOPS and 8 GB VRAM cannot handle such scales without severe limitations.
H100 SXM5 supports high-throughput inference via 3958 TFLOPS FP8 and 3350 GB/s bandwidth for large batches. GTX 1070 Ti lacks the memory and speed for production deployment.
Fine-tuning demands the H100's 67 TFLOPS FP32 and vast VRAM for parameter-efficient methods on large models. GTX 1070 Ti restricts to tiny models due to 8 GB limit.
H100 SXM5 generates images rapidly with FP16 at 1979 TFLOPS, scaling to high resolutions. GTX 1070 Ti manages basic Stable Diffusion but slowly with small batches.
H100's 3350 GB/s bandwidth and multi-precision support accelerate simulations. GTX 1070 Ti suffices only for lightweight serial tasks.
Frequently Asked Questions
What is the performance difference between GTX 1070 Ti and H100 SXM5?▾
The H100 SXM5 delivers 1979 TFLOPS FP16 versus the GTX 1070 Ti's 8.9 TFLOPS, a 222-fold increase. FP32 is 67 TFLOPS on H100 compared to 8.9 TFLOPS on GTX 1070 Ti. This makes H100 vastly superior for AI workloads.
How much VRAM do these GPUs have?▾
GTX 1070 Ti offers 8 GB GDDR5X. H100 SXM5 provides 80 GB HBM3. The difference allows H100 to load much larger models without issues.
What is the memory bandwidth comparison?▾
GTX 1070 Ti has 308 GB/s bandwidth. H100 SXM5 reaches 3350 GB/s, over 10 times higher. This impacts batch sizes in training significantly.
Is there cloud pricing for H100 SXM5?▾
H100 SXM5 starts at $0.80 per hour, averaging $3.54 per hour across 32 offers. GTX 1070 Ti has no live cloud offers.
What are the power requirements?▾
GTX 1070 Ti consumes 180 W TDP. H100 SXM5 requires 700 W. H100 provides better performance per watt in compute tasks.
Can GTX 1070 Ti handle modern AI tasks?▾
GTX 1070 Ti manages small-scale AI with 8.9 TFLOPS FP32 but struggles with large models due to 8 GB VRAM. H100 SXM5 is designed for such demands.
Which is cheaper to rent, the GTX 1070 or the H100?▾
Cloud rental prices for both the GTX 1070 and H100 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 GTX 1070 have compared to the H100?▾
The GTX 1070 has 8 GB of GDDR5 memory. The H100 has 80 to 94 GB of HBM3 memory.
Can I find GTX 1070 and H100 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 GTX 1070 and the H100?▾
The GTX 1070 uses the Pascal architecture (2016) while the H100 uses Hopper (2022). The H100 delivers 304.5x the FP16 throughput and 13.1x the memory bandwidth of the GTX 1070.