Chip comparison
AWS Inferentia 2 vs NVIDIA L40S
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 Inferentia 2 | NVIDIA L40S |
|---|---|---|
| Process node | TSMC N7 | TSMC 4N |
| Transistors (B) | — | 76.3 |
| TDP | 250 W | 350 W |
| Memory | 32 GB HBM3 | 48 GB GDDR6 |
| Memory bandwidth | 820 GB/s | 864 GB/s |
| FP16 (dense) | — | 362 TFLOPS |
| BF16 (dense) | 190 TFLOPS | 362 TFLOPS |
| FP8 (dense) | 380 TFLOPS | 733 TFLOPS |
| INT8 (dense) | — | 733 TOPS |
| Form factor | Inf2 EC2 instance | PCIe |
| Announced | 2022-12-01 | 2023-08-08 |
| Released | 2023-04-01 | — |
Robots running AWS Inferentia 2
No robots publicly running it yet.
Robots running NVIDIA L40S
No robots publicly running it yet.
Data centers with AWS Inferentia 2
No data centers publicly running it yet.
Data centers with NVIDIA L40S
No data centers publicly running it yet.
Common questions
AWS Inferentia 2 vs NVIDIA L40S: which is faster for training?
NVIDIA L40S has 1.93x the dense FP8 throughput of the other (AWS Inferentia 2: 380 TFLOPS; NVIDIA L40S: 733 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.
AWS Inferentia 2 vs NVIDIA L40S: which has more memory?
NVIDIA L40S carries more HBM (AWS Inferentia 2: 32 GB HBM3; NVIDIA L40S: 48 GB GDDR6). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.
AWS Inferentia 2 vs NVIDIA L40S: which is more power-efficient?
Dense FP8 TFLOPS per watt: AWS Inferentia 2 1.52 (380 ÷ 250 W); NVIDIA L40S 2.09 (733 ÷ 350 W). NVIDIA L40S wins at the die level; system-level efficiency also depends on cooling and interconnect.
See also: every chip comparison · AWS Inferentia 2 full page · NVIDIA L40S full page.