Chip comparison
AWS Trainium (Trn1) vs NVIDIA GB200 Grace Blackwell Superchip
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 GB200 Grace Blackwell Superchip |
|---|---|---|
| Process node | TSMC N7 | TSMC 4NP |
| TDP | 500 W | 2700 W |
| Memory | 32 GB HBM2e | 384 GB HBM3e |
| Memory bandwidth | 820 GB/s | 16,000 GB/s |
| BF16 (dense) | 210 TFLOPS | — |
| FP8 (dense) | — | 9,000 TFLOPS |
| Form factor | Trn1 EC2 instance | Superchip (2xB200 + 1xGrace) |
| Announced | 2020-12-01 | 2024-03-18 |
| Released | 2022-10-01 | 2024-12-01 |
Robots running AWS Trainium (Trn1)
No robots publicly running it yet.
Robots running NVIDIA GB200 Grace Blackwell Superchip
No robots publicly running it yet.
Data centers with AWS Trainium (Trn1)
No data centers publicly running it yet.
Data centers with NVIDIA GB200 Grace Blackwell Superchip
Common questions
AWS Trainium (Trn1) vs NVIDIA GB200 Grace Blackwell Superchip: which is faster for training?
NVIDIA GB200 Grace Blackwell Superchip has 42.86x the dense FP16/BF16 throughput of the other (AWS Trainium (Trn1): 210 TFLOPS; NVIDIA GB200 Grace Blackwell Superchip: 9,000 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 GB200 Grace Blackwell Superchip: which has more memory?
NVIDIA GB200 Grace Blackwell Superchip carries more HBM (AWS Trainium (Trn1): 32 GB HBM2e; NVIDIA GB200 Grace Blackwell Superchip: 384 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 GB200 Grace Blackwell Superchip: which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: AWS Trainium (Trn1) 0.42 (210 ÷ 500 W); NVIDIA GB200 Grace Blackwell Superchip 3.33 (9,000 ÷ 2700 W). NVIDIA GB200 Grace Blackwell Superchip wins at the die level; system-level efficiency also depends on cooling and interconnect.
AWS Trainium (Trn1) vs NVIDIA GB200 Grace Blackwell Superchip: which is more widely used?
AWS Trainium (Trn1): 0 robots and 0 data centers publicly running it. NVIDIA GB200 Grace Blackwell Superchip: 0 robots and 11 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 GB200 Grace Blackwell Superchip full page.