H100 PCIe vs H100
Detailed comparison of specifications, performance, and pricing between H100 PCIe and H100
Difference Analysis
Full Specifications
| Specification | H100 PCIe | H100 | A100 SXM | B200 |
|---|---|---|---|---|
| Brand | NVIDIA | NVIDIA | NVIDIA | NVIDIA |
| Series | Data Center | Data Center | Data Center | Data Center |
| Architecture | Hopper | Hopper | Ampere | Blackwell |
| VRAM | 80GB | 80GB | 80GB | 192GB |
| VRAM Type | HBM2e | HBM3 | HBM2e | HBM3e |
| Memory Bandwidth | 2.0 TB/s | 3.4 TB/s | 2.0 TB/s | 8.0 TB/s |
| FP16 TFLOPS | 102.0 | 134.0 | 78.0 | - |
| Tensor TFLOPS | 1.5k | 2.0k | 312.0 | 4.5k |
| TDP | 350W | 700W | 400W | 1000W |
| Form Factor | PCIe | SXM | SXM | SXM |
| Hardware Price | $$28k | $$32k | $$12k | $$45k |
| Cloud Price (min) | $2.89/hr | $1.47/hr | $1.15/hr | $3.75/hr |
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H100 PCIe vs H100 FAQ
It depends on your use case. The H100 offers 31% better performance (2.0k vs 1.5k TFLOPS). However, the H100 PCIe is 14% cheaper. For raw performance, choose H100. For value, consider your budget and workload requirements.
The H100 PCIe has more VRAM with 80GB compared to 80GB (0% more). More VRAM is crucial for training large models and running inference on bigger batch sizes.
For AI training, the H100 PCIe is generally better due to its larger VRAM (80GB). Large language models and deep learning workloads benefit significantly from more memory. However, if your models fit in 80GB, the cheaper option may be more cost-effective.
The H100 PCIe is 14% cheaper at $$28k vs $$32k. When considering performance per dollar, evaluate your specific workload requirements to determine the best value.
The H100 actually offers 31% better performance. An "upgrade" to H100 PCIe would be a downgrade in raw performance, though it may offer other benefits like lower power consumption or cost.
