Specifications Compared
| Spec | H100 | RTX-5070 |
|---|---|---|
| TDP | 700W | 250W |
| VRAM | 80-94 GB | 12 GB |
| CUDA Cores | 16,896 | 6,144 |
| Memory Type | HBM3 | GDDR7 |
| Architecture | Hopper | Blackwell |
| Form Factors | SXM5, PCIe, NVL | PCIe |
| Interconnect | NVLink, PCIe 5.0, InfiniBand | |
| Tensor Cores | 528 | 192 |
| FP8 Performance | 3,958 TFLOPS | |
| FP16 Performance | 1,979 TFLOPS | 40.6 TFLOPS |
| FP32 Performance | 67 TFLOPS | 40.6 TFLOPS |
| FP64 Performance | 34 TFLOPS | |
| INT8 Performance | 3,958 TOPS | 650 TOPS |
| Memory Bandwidth | 3,350 GB/s | 448 GB/s |
Performance Analysis
The H100 PCIe dominates in compute throughput: its 1979 TFLOPS FP16 vastly exceeds the RTX 5070's 40.6 TFLOPS, enabling faster AI training where half-precision dominates. FP32 performance shows 67 TFLOPS on H100 versus 40.6 TFLOPS on RTX 5070, benefiting general simulation tasks. The FP16 to FP32 delta on H100 accelerates mixed-precision training pipelines, reducing epochs by orders of magnitude for large models.
Memory bandwidth reveals key limits: 3350 GB/s on H100 supports batch sizes up to 10 times larger than the RTX 5070's 448 GB/s, critical for inference on billion-parameter LLMs without swapping. H100's 80 to 94 GB VRAM handles models exceeding 70B parameters in full precision, while 12 GB on RTX 5070 restricts to smaller batches or quantization. These specs translate to H100 completing training runs in hours versus days on RTX 5070 for equivalent workloads.
Power efficiency differs sharply: H100's 700W TDP demands robust cooling, yet yields 3958 TFLOPS FP8 for inference, outpacing RTX 5070 in high-volume deployments.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
H100 PCIe
| 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×) |
When to Choose the H100 PCIe
Choose the H100 PCIe for large-scale AI training or inference on models with over 70 billion parameters. Its 80 to 94 GB HBM3 VRAM and 3350 GB/s bandwidth enable full-model loading without quantization, ideal for enterprise data centers. NVLink and PCIe 5.0 interconnects scale multi-GPU clusters efficiently, justifying $1.25 to $2.65 per hour pricing for production workloads.
When to Choose the RTX 5070
Opt for the RTX 5070 in cost-sensitive scenarios like prototyping or gaming-integrated compute. At $0.08 to $0.16 per hour, its 12 GB GDDR7 and 250W TDP fit small-scale inference or fine-tuning under 7B parameters. Single PCIe form factor simplifies deployment for individual developers or edge applications.
Use Cases
H100's 1979 TFLOPS FP16 and 80 to 94 GB VRAM handle massive datasets and models without memory constraints. RTX 5070's 12 GB limits scale severely.
3958 TFLOPS FP8 and 3350 GB/s bandwidth on H100 support high-batch production serving. RTX 5070 suits only quantized small models.
67 TFLOPS FP32 and vast VRAM enable efficient parameter-efficient tuning on large LLMs. RTX 5070 restricts to tiny models.
RTX 5070's 40.6 TFLOPS FP16 and low $0.08 per hour cost suffice for image generation at consumer scales. H100 overkill for single-user tasks.
H100's 67 TFLOPS FP32 and InfiniBand scaling accelerate simulations like molecular dynamics. RTX 5070 lacks bandwidth for complex grids.
Frequently Asked Questions
What is the VRAM capacity of H100 PCIe versus RTX 5070?▾
The H100 PCIe provides 80 to 94 GB HBM3 VRAM, suitable for large AI models. The RTX 5070 offers 12 GB GDDR7, limiting it to smaller workloads. This gap affects model size handling directly.
How do cloud prices compare for these GPUs?▾
H100 PCIe rentals start at $1.25 per hour, averaging $2.65 across 21 offers. RTX 5070 begins at $0.08 per hour, averaging $0.16 across 2 offers. Pricing reflects performance disparity.
Which has higher FP16 performance?▾
H100 PCIe achieves 1979 TFLOPS FP16, dwarfing RTX 5070's 40.6 TFLOPS. This boosts AI training speed significantly on H100. Inference also favors H100 for volume.
What are the power requirements?▾
H100 PCIe has a 700W TDP, requiring enterprise cooling. RTX 5070 uses 250W TDP, ideal for standard setups. Efficiency varies by workload scale.
Is RTX 5070 viable for LLM fine-tuning?▾
RTX 5070 works for models under 7B parameters with its 12 GB VRAM and 40.6 TFLOPS FP16. Larger tasks demand H100's 80 to 94 GB capacity. Quantization extends RTX 5070 usability.
What architectures power these GPUs?▾
H100 PCIe uses Hopper from 2022 with NVLink support. RTX 5070 employs Blackwell from 2025 for consumer tasks. Architectural advances favor H100 in datacenter compute.
Which is cheaper to rent, the H100 or the RTX 5070?▾
Cloud rental prices for both the H100 and RTX 5070 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 5070?▾
The H100 has 80 to 94 GB of HBM3 memory. The RTX 5070 has 12 GB of GDDR7 memory.
Can I find H100 and RTX 5070 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 5070?▾
The H100 uses the Hopper architecture (2022) while the RTX 5070 uses Blackwell (2025). The H100 delivers 48.7x the FP16 throughput and 7.5x the memory bandwidth of the RTX 5070.