DEPLOYDatabase

Chip comparison

AWS Trainium 2 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.

FieldAWS Trainium 2NVIDIA A100 Tensor Core GPU
Process nodeTSMC N5TSMC N7
Transistors (B)54
Die size826 mm²
TDP500 W400 W
Memory96 GB HBM380 GB HBM2e
Memory bandwidth2,900 GB/s2,039 GB/s
FP16 (dense)312 TFLOPS
BF16 (dense)667 TFLOPS312 TFLOPS
FP8 (dense)1,300 TFLOPS
INT8 (dense)1,300 TOPS624 TOPS
Launch price (list)$10,000
Form factorAWS Neuron 2 (Trn2 UltraServer with 64 chips per unit)SXM4
Announced2024-12-032020-05-14
Released2025-01-012020-05-14

Robots running AWS Trainium 2

No robots publicly running it yet.

Robots running NVIDIA A100 Tensor Core GPU

No robots publicly running it yet.

Data centers with NVIDIA A100 Tensor Core GPU

No data centers publicly running it yet.

Common questions

AWS Trainium 2 vs NVIDIA A100 Tensor Core GPU: which is faster for training?

AWS Trainium 2 has 4.17x the dense FP16/BF16 throughput of the other (AWS Trainium 2: 1,300 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 2 vs NVIDIA A100 Tensor Core GPU: which has more memory?

AWS Trainium 2 carries more HBM (AWS Trainium 2: 96 GB HBM3; 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 2 vs NVIDIA A100 Tensor Core GPU: which is more power-efficient?

Dense FP16/BF16 TFLOPS per watt: AWS Trainium 2 2.60 (1,300 ÷ 500 W); NVIDIA A100 Tensor Core GPU 0.78 (312 ÷ 400 W). AWS Trainium 2 wins at the die level; system-level efficiency also depends on cooling and interconnect.

AWS Trainium 2 vs NVIDIA A100 Tensor Core GPU: which is more widely used?

AWS Trainium 2: 0 robots and 3 data centers publicly running it. NVIDIA A100 Tensor Core GPU: 0 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 2 full page · NVIDIA A100 Tensor Core GPU full page.