Chip comparison
AWS Trainium (Trn1) vs NVIDIA A100 Tensor Core GPU
Side-by-side specs
Straight from each vendor's datasheet. Winner in bold: higher throughput, memory, or transistor count; lower power draw or price. Sparse (2:4) throughput roughly doubles the FP8/INT8 numbers shown.
| Field | AWS Trainium (Trn1) | NVIDIA A100 Tensor Core GPU |
|---|---|---|
| Process node | TSMC N7 | TSMC N7 |
| Transistors (B) | — | 54 |
| Die size | — | 826 mm² |
| TDP | 500 W | 400 W |
| Memory | 32 GB HBM2e | 80 GB HBM2e |
| Memory bandwidth | 820 GB/s | 2,039 GB/s |
| FP16 (dense) | — | 312 TFLOPS |
| BF16 (dense) | 210 TFLOPS | 312 TFLOPS |
| INT8 (dense) | — | 624 TOPS |
| Launch price (list) | — | $10,000 |
| Form factor | Trn1 EC2 instance | SXM4 |
| Announced | 2020-12-01 | 2020-05-14 |
| Released | 2022-10-01 | 2020-05-14 |
Robots running AWS Trainium (Trn1)
No robots publicly running it yet.
Robots running NVIDIA A100 Tensor Core GPU
No robots publicly running it yet.
Data centers with AWS Trainium (Trn1)
No data centers publicly running it yet.
Data centers with NVIDIA A100 Tensor Core GPU
No data centers publicly running it yet.
Common questions
AWS Trainium (Trn1) vs NVIDIA A100 Tensor Core GPU: which is faster for training?
NVIDIA A100 Tensor Core GPU has 1.49x the dense FP16/BF16 throughput of the other (AWS Trainium (Trn1): 210 TFLOPS; NVIDIA A100 Tensor Core GPU: 312 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.
AWS Trainium (Trn1) vs NVIDIA A100 Tensor Core GPU: which has more memory?
NVIDIA A100 Tensor Core GPU carries more HBM (AWS Trainium (Trn1): 32 GB HBM2e; NVIDIA A100 Tensor Core GPU: 80 GB HBM2e). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.
AWS Trainium (Trn1) vs NVIDIA A100 Tensor Core GPU: which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: AWS Trainium (Trn1) 0.42 (210 ÷ 500 W); NVIDIA A100 Tensor Core GPU 0.78 (312 ÷ 400 W). NVIDIA A100 Tensor Core GPU wins at the die level; system-level efficiency also depends on cooling and interconnect.
See also: every chip comparison · AWS Trainium (Trn1) full page · NVIDIA A100 Tensor Core GPU full page.