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NVIDIA A100 vs AMD Instinct MI210 (64GB HBM2e PCIe HPC 训练): Spec Comparison & Buyer's Guide

In AI infrastructure selection, NVIDIA A100 and AMD Instinct MI210 (64GB HBM2e PCIe HPC 训练) are two accelerators frequently compared. This article contrasts them item by item — architecture, compute, memory, power, and release cadence — to help you quickly judge which fits training or inference workloads.

Spec Comparison Table​

VendorNVIDIA A100AMD Instinct MI210 (64GB HBM2e PCIe HPC 训练)
VendorNVIDIAAMD
ArchitectureAmpere GA100CDNA 2
ProcessTSMC 7nmTSMC 6nm FinFET
Release Date2020 6 GTC2022-03-22
FP8 Compute——
FP16 Compute——
FP32 Compute19.5 TFLOPS—
INT8 Compute——
Memory Type——
Memory Capacity80 GB HBM2e64 GB HBM2e
Memory Bandwidth1,935 GB/s1.6 TB/s
TDP Power300 W / 400 W300 W

Key Differences​

  • Power: AMD Instinct MI210 (64GB HBM2e PCIe HPC 训练) has a TDP of 300 W, lower than NVIDIA A100's 300 W / 400 W, friendlier to datacenter PUE and cooling.
  • Memory capacity: NVIDIA A100 packs 80 GB HBM2e, more than AMD Instinct MI210 (64GB HBM2e PCIe HPC 训练)'s 64 GB HBM2e, more comfortable for single-card hosting of very large models.

Selection Advice​

  • When chasing extreme single-card compute and a mature toolchain, prioritize NVIDIA A100; if budget, power wall, or local support are hard constraints, AMD Instinct MI210 (64GB HBM2e PCIe HPC 训练) often fits better. Use this site's AI Compute Card Comparison Tool to validate multiple chips side-by-side before deciding.

FAQ​

What are the main differences between NVIDIA A100 and AMD Instinct MI210 (64GB HBM2e PCIe HPC 训练)?​

The core difference is architecture and compute density: NVIDIA A100 uses Ampere GA100, FP8 ~No public FP8 data, memory 80 GB HBM2e; AMD Instinct MI210 (64GB HBM2e PCIe HPC 训练) uses CDNA 2, FP8 ~No public FP8 data, memory 64 GB HBM2e. See the comparison table above.

What is the TDP (power) of NVIDIA A100?​

NVIDIA A100 has a TDP of 300 W / 400 W; actual whole-system power also includes board, fans, and PUE.

Which is better for large-model training / inference?​

Training values memory capacity, bandwidth, and multi-card interconnect; inference values single-card throughput and power efficiency. Combine the "Key Differences" and "Selection Advice" above with your batch size, model size, and SLA.

How much do NVIDIA A100 and AMD Instinct MI210 (64GB HBM2e PCIe HPC 训练) differ in memory capacity?​

NVIDIA A100 is 80 GB HBM2e, AMD Instinct MI210 (64GB HBM2e PCIe HPC 训练) is 64 GB HBM2e; the gap directly affects loadable model size and context length.