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 SXM5 excels in compute-intensive tasks due to its FP16 performance of 1979 TFLOPS, dwarfing the RTX 4070 Ti SUPER's 29.1 TFLOPS: this gap accelerates machine learning training where mixed-precision FP16 or bfloat16 dominates. FP32 performance follows suit at 67 TFLOPS for H100 SXM5 versus 29.1 TFLOPS, benefiting simulations and graphics rendering. The H100 SXM5's FP8 capability of 3958 TFLOPS further optimizes large-scale inference.
Memory bandwidth defines workload feasibility: 3350 GB/s on H100 SXM5 supports massive batch sizes and models exceeding 12 GB VRAM on RTX 4070 Ti SUPER, preventing out-of-memory errors in transformer training. Lower 504 GB/s on RTX 4070 Ti SUPER limits it to smaller datasets. Power draw reflects scale, with H100 SXM5 at 700W TDP versus 200W, demanding robust cooling in datacenters but enabling sustained peak performance.
These specs translate to real-world speedups: H100 SXM5 handles enterprise-scale LLMs where RTX 4070 Ti SUPER suits prototyping.
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 | ||
 Voltage Park | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 208 vCPU 928GB RAM 19200GB Storage | Dallas, Texas | $1.99/GPU/hr $15.92/hr total (8×) |
RTX 4070 Ti 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 SXM5
The H100 SXM5 suits large-scale AI training and inference requiring over 12 GB VRAM. Its 80 to 94 GB HBM3 capacity fits billion-parameter models, while 3350 GB/s bandwidth enables high batch sizes. Users in research or production deploying FP16 workloads benefit from 1979 TFLOPS, justifying $0.80 to $3.51 per hour costs.
When to Choose the RTX 4070 Ti SUPER
The RTX 4070 Ti SUPER fits budget-conscious tasks like gaming, video editing, or small model fine-tuning. With 12 GB GDDR6X and 29.1 TFLOPS FP16 or FP32, it handles Stable Diffusion or lightweight inference efficiently at $0.09 to $0.17 per hour. Low 200W TDP suits edge or desktop clouds.
Use Cases
H100 SXM5's 80-94 GB HBM3 VRAM and 1979 TFLOPS FP16 support training massive LLMs that exceed RTX 4070 Ti SUPER's 12 GB limit.
3958 TFLOPS FP8 and 3350 GB/s bandwidth on H100 SXM5 enable high-throughput serving of large models, outperforming RTX 4070 Ti SUPER's 29.1 TFLOPS.
RTX 4070 Ti SUPER's 12 GB VRAM and 29.1 TFLOPS suffice for fine-tuning smaller models at low cost of $0.09 per hour.
RTX 4070 Ti SUPER handles image generation efficiently with 504 GB/s bandwidth and 200W TDP, ideal for creative workflows.
H100 SXM5's 67 TFLOPS FP32 and NVLink interconnect accelerate simulations requiring high precision and scalability.
Frequently Asked Questions
What is the VRAM capacity of H100 SXM5 versus RTX 4070 Ti SUPER?▾
H100 SXM5 provides 80 to 94 GB HBM3 VRAM. RTX 4070 Ti SUPER has 12 GB GDDR6X. This enables H100 SXM5 to load much larger models.
How do FP16 performances compare?▾
H100 SXM5 achieves 1979 TFLOPS FP16. RTX 4070 Ti SUPER reaches 29.1 TFLOPS. The difference speeds up AI training significantly on H100 SXM5.
What are the cloud pricing ranges?▾
H100 SXM5 starts at $0.80 per hour, averaging $3.51 per hour across 34 offers. RTX 4070 Ti SUPER begins at $0.09 per hour, averaging $0.17 per hour across 2 offers.
Which GPU has higher memory bandwidth?▾
H100 SXM5 delivers 3350 GB/s. RTX 4070 Ti SUPER offers 504 GB/s. Higher bandwidth on H100 SXM5 supports larger batch sizes.
What are the TDP ratings?▾
H100 SXM5 consumes 700W TDP. RTX 4070 Ti SUPER uses 200W. Lower TDP makes RTX 4070 Ti SUPER suitable for power-constrained setups.
What architectures do they use?▾
H100 SXM5 employs Hopper from 2022. RTX 4070 Ti SUPER uses Ada Lovelace from 2023. Hopper optimizes for datacenter AI tasks.
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.