Chip comparison
AWS Trainium (Trn1) vs NVIDIA H200 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 H200 Tensor Core GPU |
|---|---|---|
| Process node | TSMC N7 | TSMC 4N |
| Transistors (B) | — | 80 |
| Die size | — | 814 mm² |
| TDP | 500 W | 700 W |
| Memory | 32 GB HBM2e | 141 GB HBM3e |
| Memory bandwidth | 820 GB/s | 4,800 GB/s |
| FP16 (dense) | — | 989 TFLOPS |
| BF16 (dense) | 210 TFLOPS | 989 TFLOPS |
| FP8 (dense) | — | 1,979 TFLOPS |
| INT8 (dense) | — | 1,979 TOPS |
| Form factor | Trn1 EC2 instance | SXM5 |
| Announced | 2020-12-01 | 2023-11-13 |
| Released | 2022-10-01 | 2024-03-01 |
Robots running AWS Trainium (Trn1)
No robots publicly running it yet.
Robots running NVIDIA H200 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 H200 Tensor Core GPU
Common questions
AWS Trainium (Trn1) vs NVIDIA H200 Tensor Core GPU: which is faster for training?
NVIDIA H200 Tensor Core GPU has 9.42x the dense FP16/BF16 throughput of the other (AWS Trainium (Trn1): 210 TFLOPS; NVIDIA H200 Tensor Core GPU: 1,979 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 H200 Tensor Core GPU: which has more memory?
NVIDIA H200 Tensor Core GPU carries more HBM (AWS Trainium (Trn1): 32 GB HBM2e; NVIDIA H200 Tensor Core GPU: 141 GB HBM3e). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.
AWS Trainium (Trn1) vs NVIDIA H200 Tensor Core GPU: which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: AWS Trainium (Trn1) 0.42 (210 ÷ 500 W); NVIDIA H200 Tensor Core GPU 2.83 (1,979 ÷ 700 W). NVIDIA H200 Tensor Core GPU wins at the die level; system-level efficiency also depends on cooling and interconnect.
AWS Trainium (Trn1) vs NVIDIA H200 Tensor Core GPU: which is more widely used?
AWS Trainium (Trn1): 0 robots and 0 data centers publicly running it. NVIDIA H200 Tensor Core GPU: 0 robots and 4 data centers. Empty here means no operator has said publicly, not zero adoption in the market.
See also: every chip comparison · AWS Trainium (Trn1) full page · NVIDIA H200 Tensor Core GPU full page.