H100 PCIe vs A40
Detailed comparison of specifications, performance, and pricing between NVIDIA H100 PCIe and NVIDIA A40
Difference Analysis
Full Specifications
| Specification | H100 PCIe | A40 | AMD Instinct MI210 |
|---|---|---|---|
| Brand | NVIDIA | NVIDIA | AMD |
| Series | Data Center | Data Center | Data Center |
| Architecture | Hopper | Ampere | CDNA 2 |
| VRAM | 80GB | 48GB | 64GB |
| VRAM Type | HBM2e | GDDR6 | HBM2E |
| Memory Bandwidth | 2.0 TB/s | 696 GB/s | 1.6 TB/s |
| FP16 TFLOPS | 102.0 | 74.8 | 181.0 |
| Tensor TFLOPS | 1.5k | 150.0 | 362.0 |
| TDP | 350W | 300W | 300W |
| Form Factor | PCIe | PCIe | - |
| Hardware Price | $$28k | $$4.0k | - |
| Cloud Price (min) | $2.39/hr | $0.400/hr | - |
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H100 PCIe vs A40 FAQ
It depends on your use case. The H100 PCIe offers 909% better performance (1.5k vs 150.0 TFLOPS). However, the A40 is 600% cheaper. For raw performance, choose H100 PCIe. For value, consider your budget and workload requirements.
The H100 PCIe has more VRAM with 80GB compared to 48GB (67% 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 48GB, the cheaper option may be more cost-effective.
The A40 is 600% cheaper at $$4.0k vs $$28k. When considering performance per dollar, evaluate your specific workload requirements to determine the best value.
Upgrading to H100 PCIe would give you 909% more performance and 67% more VRAM. The upgrade cost difference is approximately $$24k. Consider if your workloads are bottlenecked by current GPU capabilities.