Chip comparison
AWS Trainium (Trn1) vs NVIDIA Jetson AGX Thor
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 Jetson AGX Thor |
|---|---|---|
| Process node | TSMC N7 | TSMC 4NP |
| TDP | 500 W | 130 W |
| Memory | 32 GB HBM2e | 128 GB LPDDR5X |
| Memory bandwidth | 820 GB/s | 273 GB/s |
| BF16 (dense) | 210 TFLOPS | — |
| FP8 (dense) | — | 2,070 TFLOPS |
| INT8 (dense) | — | 2,070 TOPS |
| Form factor | Trn1 EC2 instance | Module (AGX Thor) |
| Announced | 2020-12-01 | 2024-03-18 |
| Released | 2022-10-01 | 2025-08-01 |
Robots running AWS Trainium (Trn1)
No robots publicly running it yet.
Data centers with AWS Trainium (Trn1)
No data centers publicly running it yet.
Data centers with NVIDIA Jetson AGX Thor
No data centers publicly running it yet.
Common questions
AWS Trainium (Trn1) vs NVIDIA Jetson AGX Thor: which is faster for training?
NVIDIA Jetson AGX Thor has 9.86x the dense FP16/BF16 throughput of the other (AWS Trainium (Trn1): 210 TFLOPS; NVIDIA Jetson AGX Thor: 2,070 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 Jetson AGX Thor: which has more memory?
NVIDIA Jetson AGX Thor carries more HBM (AWS Trainium (Trn1): 32 GB HBM2e; NVIDIA Jetson AGX Thor: 128 GB LPDDR5X). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.
AWS Trainium (Trn1) vs NVIDIA Jetson AGX Thor: which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: AWS Trainium (Trn1) 0.42 (210 ÷ 500 W); NVIDIA Jetson AGX Thor 15.92 (2,070 ÷ 130 W). NVIDIA Jetson AGX Thor wins at the die level; system-level efficiency also depends on cooling and interconnect.
AWS Trainium (Trn1) vs NVIDIA Jetson AGX Thor: which is more widely used?
AWS Trainium (Trn1): 0 robots and 0 data centers publicly running it. NVIDIA Jetson AGX Thor: 11 robots and 0 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 Jetson AGX Thor full page.