H100 PCIe vs AMD Instinct MI210
Detailed comparison of specifications, performance, and pricing between NVIDIA H100 PCIe and AMD Instinct MI210
Difference Analysis
Full Specifications
| Specification | H100 PCIe | AMD Instinct MI210 | RTX PRO 6000 |
|---|---|---|---|
| Brand | NVIDIA | AMD | NVIDIA |
| Series | Data Center | Data Center | - |
| Architecture | Hopper | CDNA 2 | - |
| VRAM | 80GB | 64GB | 96GB |
| VRAM Type | HBM2e | HBM2E | - |
| Memory Bandwidth | 2.0 TB/s | 1.6 TB/s | - |
| FP16 TFLOPS | 102.0 | 181.0 | - |
| Tensor TFLOPS | 1.5k | 362.0 | - |
| TDP | 350W | 300W | - |
| Form Factor | PCIe | - | - |
| Hardware Price | $$28k | - | - |
| Cloud Price (min) | $2.39/hr | - | $1.84/hr |
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H100 PCIe vs AMD Instinct MI210 FAQ
It depends on your use case. The H100 PCIe offers 318% better performance (1.5k vs 362.0 TFLOPS). For raw performance, choose H100 PCIe. For value, consider your budget and workload requirements.
The H100 PCIe has more VRAM with 80GB compared to 64GB (25% 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 64GB, the cheaper option may be more cost-effective.
Price comparison requires both GPUs to have available pricing data. Check individual GPU pages for current market prices.
Upgrading to H100 PCIe would give you 318% more performance and 25% more VRAM. Consider if your workloads are bottlenecked by current GPU capabilities.