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 throughput reaches 1979 TFLOPS, far exceeding the RTX 3070's 20.3 TFLOPS, which accelerates mixed-precision training in deep learning models. For FP32 operations, the H100 delivers 67 TFLOPS against the RTX 3070's 20.3 TFLOPS, benefiting single-precision scientific simulations. This delta means training large neural networks completes orders of magnitude faster on the H100: a task taking hours on the RTX 3070 might finish in minutes.
Memory capacity defines feasibility: the H100's 80 to 94 GB HBM3 supports massive batch sizes for models like large language models, whereas the RTX 3070's 8 GB GDDR6 limits batches and requires gradient accumulation, slowing effective throughput. Bandwidth reinforces this: 3350 GB/s on the H100 versus 448 GB/s on the RTX 3070 reduces data bottlenecks, enabling higher utilization in inference pipelines. In real-world terms, the H100 handles enterprise inference at scale, while the RTX 3070 suits prototyping where speed is secondary to cost.
Power draw highlights efficiency trade-offs: the H100's 700W TDP demands robust cooling and infrastructure, contrasting the RTX 3070's 220W for easier deployment. Interconnects like NVLink on the H100 enable multi-GPU scaling unavailable on the PCIe-only RTX 3070.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
H100
| 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
Opt for the H100 in scenarios demanding extreme compute: training billion-parameter LLMs where its 1979 TFLOPS FP16 and 80 to 94 GB VRAM enable full-model loading without sharding. Datacenter workflows benefit from 3350 GB/s bandwidth for large-batch training, reducing epochs from days to hours compared to consumer GPUs.
Multi-node clusters leverage NVLink and InfiniBand for distributed training, ideal for research labs or AI firms processing petabyte-scale datasets.
When to Choose the RTX 3070
Choose the RTX 3070 for cost-sensitive, low-volume tasks: hobbyist fine-tuning of small models under 8 GB VRAM or Stable Diffusion image generation at $0.04 per hour minimum. Its 20.3 TFLOPS FP16 suffices for inference on lightweight networks, avoiding the H100's $0.80 per hour entry cost.
Gaming, video editing, or entry-level ML prototyping fit its 220W TDP and PCIe form factor, offering quick setup without datacenter overhead.
Use Cases
The H100's 1979 TFLOPS FP16 and 80 to 94 GB VRAM handle billion-parameter models with large batches. The RTX 3070's 8 GB limits scale.
H100's 3958 TFLOPS FP8 and high bandwidth support high-throughput serving. RTX 3070 manages small models but bottlenecks on demand.
H100 accelerates with 67 TFLOPS FP32 for precise updates on large datasets. RTX 3070 works for tiny models under 8 GB.
RTX 3070's 20.3 TFLOPS FP16 generates images quickly at low cost. H100 overkill for single-user creative tasks.
H100's 3350 GB/s bandwidth and NVLink excel in simulations. RTX 3070 adequate for modest HPC but lacks scale.
Frequently Asked Questions
How much faster is the H100 than RTX 3070 in FP16?▾
The H100 achieves 1979 TFLOPS in FP16 compared to the RTX 3070's 20.3 TFLOPS, yielding nearly 100 times the performance. This gap accelerates AI training significantly. Real-world speedups depend on memory-bound tasks.
What is the VRAM difference between H100 and RTX 3070?▾
H100 provides 80 to 94 GB HBM3 versus RTX 3070's 8 GB GDDR6. This allows H100 to load massive models fully. RTX 3070 requires model parallelism for larger ones.
Which has higher cloud rental cost?▾
H100 averages $3.14 per hour across 57 offers, starting at $0.80 per hour. RTX 3070 averages $0.08 per hour from $0.04 per hour over 6 offers. Cost reflects performance disparity.
Can RTX 3070 handle LLM inference?▾
RTX 3070 supports inference for models under 8 GB VRAM at 20.3 TFLOPS FP16. Larger LLMs need quantization or offloading. H100 excels without compromises.
What is the TDP comparison?▾
H100 draws 700W, requiring datacenter power. RTX 3070 uses 220W, suitable for desktops. Efficiency favors H100 per TFLOP.
Does H100 support multi-GPU better?▾
H100 uses NVLink, PCIe 5.0, and InfiniBand for scaling. RTX 3070 relies on PCIe alone. This enables H100 clusters for distributed training.
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.