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 NVL's 1979 TFLOPS FP16 performance vastly outpaces the RTX 3070's 20.3 TFLOPS, enabling 97 times faster tensor core operations critical for deep learning training. FP32 throughput shows H100 at 67 TFLOPS versus 20.3 TFLOPS on RTX 3070, accelerating simulations and rendering by over three times. FP8 at 3958 TFLOPS on H100 NVL supports ultra-efficient inference for massive language models.
Memory differences define workload feasibility: H100 NVL's 80 to 94 GB HBM3 handles batch sizes up to 10 times larger than RTX 3070's 8 GB GDDR6 limit, reducing out-of-memory errors in training large models. The 3350 GB/s bandwidth on H100 NVL, compared to 448 GB/s, minimizes data bottlenecks, sustaining 7.5 times higher throughput in memory-intensive inference. These specs translate to hours-long jobs completing in minutes on H100 NVL versus days on RTX 3070.
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
Opt for the H100 NVL in large-scale LLM training or fine-tuning where 80 to 94 GB VRAM accommodates models exceeding 70B parameters without multi-GPU complexity. Its 3350 GB/s bandwidth and NVLink interconnect excel in distributed computing clusters, ideal for research labs processing petabyte datasets at $1.40 to $2.89 per hour.
Enterprise inference deployments benefit from 3958 TFLOPS FP8, serving thousands of queries per second unattainable on consumer hardware.
When to Choose the RTX 3070
The RTX 3070 suits budget prototyping of small models under 7B parameters, leveraging 8 GB VRAM at $0.04 per hour for rapid iteration. Hobbyists and indie developers favor its 220W efficiency in single-node Stable Diffusion or light inference, avoiding H100 NVL's high costs.
Gaming-integrated workflows or educational GPU programming thrive on RTX 3070's PCIe form factor and low 448 GB/s bandwidth needs.
Use Cases
H100 NVL's 80-94 GB VRAM and 1979 TFLOPS FP16 support training models over 70B parameters with large batches. RTX 3070's 8 GB limits it to tiny models.
3958 TFLOPS FP8 on H100 NVL enables high-throughput serving for production. RTX 3070's 20.3 TFLOPS FP16 handles only low-volume queries.
3350 GB/s bandwidth on H100 NVL accelerates parameter-efficient tuning on full datasets. RTX 3070 struggles with memory constraints beyond small adapters.
RTX 3070's 20.3 TFLOPS FP16 suffices for image generation at 512x512 resolutions cost-effectively at $0.04 per hour. H100 NVL overkill for single-user creative tasks.
67 TFLOPS FP32 on H100 NVL powers complex simulations like molecular dynamics. RTX 3070's matching 20.3 TFLOPS FP32 limits scale.
Frequently Asked Questions
What is the VRAM difference between H100 NVL and RTX 3070?▾
H100 NVL offers 80 to 94 GB HBM3 VRAM, enabling massive models. RTX 3070 provides 8 GB GDDR6, suitable for smaller workloads.
How do cloud prices compare for these GPUs?▾
H100 NVL starts at $1.40 per hour, averaging $2.89 across nine providers. RTX 3070 begins at $0.04 per hour, averaging $0.09 across four offers.
Which has higher FP16 performance?▾
H100 NVL achieves 1979 TFLOPS FP16, nearly 100 times the RTX 3070's 20.3 TFLOPS. This gap favors H100 for AI acceleration.
Can RTX 3070 handle LLM fine-tuning?▾
RTX 3070 manages fine-tuning on models under 7B parameters with its 8 GB VRAM. Larger tasks require H100 NVL's 80-94 GB capacity.
What is the memory bandwidth gap?▾
H100 NVL delivers 3350 GB/s, over seven times the RTX 3070's 448 GB/s. Higher bandwidth reduces bottlenecks in training.
Which GPU has lower power draw?▾
RTX 3070 consumes 220W TDP versus H100 NVL's 700W. This makes 3070 preferable for low-power edge deployments.
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.