Specifications Compared
| Spec | H100 | RTX-4070 |
|---|---|---|
| TDP | 700W | 200W |
| VRAM | 80-94 GB | 12 GB |
| CUDA Cores | 16,896 | 5,888 |
| Memory Type | HBM3 | GDDR6X |
| Architecture | Hopper | Ada Lovelace |
| 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 | 29.1 TFLOPS |
| FP32 Performance | 67 TFLOPS | 29.1 TFLOPS |
| FP64 Performance | 34 TFLOPS | |
| INT8 Performance | 3,958 TOPS | 466 TOPS |
| Memory Bandwidth | 3,350 GB/s | 504 GB/s |
Performance Analysis
The H100 NVL vastly outperforms the RTX 4070 SUPER in AI-relevant metrics. Its FP16 performance reaches 1979 TFLOPS compared to 35 TFLOPS on the RTX 4070 SUPER, accelerating deep learning training by orders of magnitude. The FP32 performance of 67 TFLOPS on the H100 NVL exceeds the RTX 4070 SUPER's 35 TFLOPS, but the real gap lies in low-precision formats like FP8 at 3958 TFLOPS on the H100 NVL, ideal for modern LLM training and inference.
Memory bandwidth defines practical limits: the H100 NVL's 3350 GB/s supports massive batch sizes for models exceeding 12 GB VRAM capacity of the RTX 4070 SUPER. This enables training billion-parameter models on the H100 NVL without splitting, while the RTX 4070 SUPER's 504 GB/s restricts it to smaller batches or quantized inference. Power draw further differentiates them: 700W TDP for the H100 NVL suits datacenters, versus 220W for efficient desktop use on the RTX 4070 SUPER.
In real-world terms, the H100 NVL handles enterprise-scale AI pipelines, whereas the RTX 4070 SUPER suits prototyping or gaming with occasional ML tasks.
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 |
RTX 4070 SUPER
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA GeForce RTX 4070 Ti 12GB VRAM | 12GB | 6 vCPU 30GB RAM | 🌍global | $0.50/GPU/hr |
When to Choose the H100 NVL
Choose the NVIDIA H100 NVL for large-scale AI training and inference requiring over 80 GB VRAM. Its 94 GB HBM3 and 3350 GB/s bandwidth accommodate full-precision LLMs up to hundreds of billions of parameters without model parallelism. Datacenter users benefit from NVLink interconnects and FP8 performance of 3958 TFLOPS for rapid iterations.
Cloud deployments at $1.40 per hour make it viable for teams needing 1979 TFLOPS FP16 throughput unattainable on consumer hardware.
When to Choose the RTX 4070 SUPER
The NVIDIA GeForce RTX 4070 SUPER fits budget-conscious individuals or small projects with its 220W TDP and PCIe form factor for easy desktop integration. It delivers 35 TFLOPS FP16 for fine-tuning small models or running Stable Diffusion locally within 12 GB VRAM limits.
Without cloud pricing, it appeals for offline gaming or entry-level inference where 504 GB/s bandwidth suffices and acquisition costs far undercut H100 NVL hourly rates.
Use Cases
The H100 NVL's 94 GB HBM3 VRAM and 3958 TFLOPS FP8 performance handle massive LLMs with large batch sizes. The RTX 4070 SUPER's 12 GB limits it to tiny models.
H100 NVL supports high-throughput inference via 1979 TFLOPS FP16 and NVLink scaling. RTX 4070 SUPER manages small-scale inference but bottlenecks on memory.
94 GB VRAM on H100 NVL fits full datasets for fine-tuning large models at 3350 GB/s bandwidth. RTX 4070 SUPER requires heavy quantization.
RTX 4070 SUPER's 35 TFLOPS FP16 and 12 GB VRAM suffice for fast image generation locally. H100 NVL overkill for single-user creative tasks.
H100 NVL's 67 TFLOPS FP32 and InfiniBand support complex simulations. RTX 4070 SUPER lacks capacity for large-scale HPC workloads.
Frequently Asked Questions
How much VRAM does the H100 NVL have compared to RTX 4070 SUPER?▾
The H100 NVL provides 94 GB HBM3 VRAM, dwarfing the RTX 4070 SUPER's 12 GB GDDR6X. This allows the H100 NVL to load enormous AI models in one GPU.
What is the FP16 performance difference?▾
H100 NVL achieves 1979 TFLOPS in FP16, versus 35 TFLOPS on RTX 4070 SUPER. This gap translates to 56 times faster AI computations on the H100 NVL.
Which GPU has higher memory bandwidth?▾
The H100 NVL offers 3350 GB/s bandwidth, six times the RTX 4070 SUPER's 504 GB/s. Higher bandwidth on H100 NVL supports larger batch sizes in training.
What are the power requirements?▾
H100 NVL consumes 700W TDP for datacenter use, while RTX 4070 SUPER uses 220W for efficient consumer setups. Lower TDP makes RTX 4070 SUPER desktop-friendly.
Is there cloud pricing for these GPUs?▾
H100 NVL starts at $1.40 per hour averaging $2.89 across nine offers. RTX 4070 SUPER has no live cloud offers, suiting local purchases.
Which is better for AI training?▾
H100 NVL excels with 3958 TFLOPS FP8 and 94 GB VRAM for large LLMs. RTX 4070 SUPER limits training to small models due to 12 GB VRAM.
Which is cheaper to rent, the H100 or the RTX 4070?▾
Cloud rental prices for both the H100 and RTX 4070 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 4070?▾
The H100 has 80 to 94 GB of HBM3 memory. The RTX 4070 has 12 GB of GDDR6X memory.
Can I find H100 and RTX 4070 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 4070?▾
The H100 uses the Hopper architecture (2022) while the RTX 4070 uses Ada Lovelace (2023). The H100 delivers 68.0x the FP16 throughput and 6.6x the memory bandwidth of the RTX 4070.