NVIDIA H100 PCIe VS NVIDIA A100 80GB
Choosing between **H100 PCIe** and **A100 80GB** depends on your specific AI workload requirements. Currently, you can rent these GPUs starting from **$0.00/h** and **$0.40/h** respectively across 41 providers.
H100 PCIe
A100 80GB
📊 Detailed Specifications Comparison
| Specification | H100 PCIe | A100 80GB | Difference |
|---|---|---|---|
| Architecture & Design | |||
| Architecture | Hopper | Ampere | - |
| Process Node | 4nm | 7nm | - |
| Target Market | datacenter | datacenter | - |
| Form Factor | Dual-slot PCIe | SXM4 / PCIe | - |
| Memory & Bandwidth | |||
| VRAM Capacity | 80GB | 80GB | |
| Memory Type | HBM3 | HBM2e | - |
| Memory Bandwidth | 2.0 TB/s | 2.0 TB/s | -2% |
| Memory Bus Width | 5120-bit | 5120-bit | - |
| Compute Infrastructure | |||
| CUDA Cores | 14,592 | 6,912 | +111% |
| Tensor Cores (AI) | 456 | 432 | +6% |
| AI & Compute Performance (TFLOPS) | |||
| FP32 (Single Precision) | 51 TFLOPS | 19.5 TFLOPS | +162% |
| FP16 (Half Precision) | 1,513 TFLOPS | 312 TFLOPS | +385% |
| TF32 (Tensor Float) | N/A | 156 TFLOPS | |
| FP64 (Double Precision) | N/A | 9.7 TFLOPS | |
| INT8 (Integer Precision) | N/A | 624 TOPS | |
| Power & Efficiency | |||
| TDP (Thermal Design Power) | 350W | 400W | -13% |
| PCIe Interface | PCIe 5.0 x16 | PCIe 4.0 x16 | - |
| Multi-GPU Interconnect | None | NVLink 3.0 (600 GB/s) | - |
🎯 Use Case Recommendations
LLM & Large Model Training
NVIDIA H100 PCIe
Higher VRAM capacity and memory bandwidth are critical for training large language models. The A100 80GB offers 80GB compared to 80GB.
AI Inference
NVIDIA H100 PCIe
For inference workloads, performance per watt matters most. Consider the balance between FP16/INT8 throughput and power consumption.
Budget-Conscious Choice
NVIDIA A100 80GB
Compare live pricing to find the best value for your specific workload.
Technical Deep Dive: H100 PCIe vs A100 80GB
This is a generational comparison within the NVIDIA ecosystem, pitting Hopper against Ampere.
NVIDIA H100 PCIe is Best For:
- AI inference
- Enterprise AI
- Highest-end training
NVIDIA A100 80GB is Best For:
- AI model training
- Scientific computing
- Newest FP8 precision workloads
Frequently Asked Questions
Which GPU is better for AI training: H100 PCIe or A100 80GB?
For AI training, the key factors are VRAM size, memory bandwidth, and tensor core performance. The H100 PCIe offers 80GB of HBM3 memory with 2.0 TB/s bandwidth, while the A100 80GB provides 80GB of HBM2e with 2.0 TB/s bandwidth. Both GPUs have similar VRAM capacity, so performance characteristics become the deciding factor.
What is the price difference between H100 PCIe and A100 80GB in the cloud?
Cloud GPU rental prices vary by provider and region. Check our price tracker for the latest rates from 50+ cloud providers.
Can I use A100 80GB instead of H100 PCIe for my workload?
It depends on your specific requirements. If your model fits within 80GB of VRAM and you don't need the additional throughput of the H100 PCIe, the A100 80GB can be a cost-effective alternative. However, for workloads requiring maximum memory capacity or multi-GPU scaling, the H100 PCIe's architecture may be essential.
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