AMD Instinct MI210 vs A100 SXM
Detailed comparison of specifications, performance, and pricing between AMD Instinct MI210 and A100 SXM
Difference Analysis
Full Specifications
| Specification | AMD Instinct MI210 | A100 SXM |
|---|---|---|
| Brand | AMD | NVIDIA |
| Series | Data Center | Data Center |
| Architecture | CDNA 2 | Ampere |
| VRAM | 64GB | 80GB |
| VRAM Type | HBM2E | HBM2e |
| Memory Bandwidth | 1.6 TB/s | 2.0 TB/s |
| FP16 TFLOPS | 181.0 | 78.0 |
| Tensor TFLOPS | 362.0 | 312.0 |
| TDP | 300W | 400W |
| Form Factor | - | SXM |
| Hardware Price | - | $$12k |
| Cloud Price (min) | - | $1.15/hr |
Which Should You Choose?
For AI Training
Large model training needs maximum VRAM and memory bandwidth.
For AI Inference
Inference prioritizes throughput and cost efficiency.
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AMD Instinct MI210 vs A100 SXM FAQ
It depends on your use case. The AMD Instinct MI210 offers 16% better performance (362.0 vs 312.0 TFLOPS). For raw performance, choose AMD Instinct MI210. For value, consider your budget and workload requirements.
The A100 SXM 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 A100 SXM 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 AMD Instinct MI210 would give you 16% more performance and similar VRAM. Consider if your workloads are bottlenecked by current GPU capabilities.
