DEPLOYDatabase

Chip comparison

AWS Trainium 2 vs Google TPU v5e

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 2Google TPU v5e
Process nodeTSMC N5
TDP500 W170 W
Memory96 GB HBM316 GB HBM2
Memory bandwidth2,900 GB/s819 GB/s
BF16 (dense)667 TFLOPS197 TFLOPS
FP8 (dense)1,300 TFLOPS
INT8 (dense)1,300 TOPS393 TOPS
Form factorAWS Neuron 2 (Trn2 UltraServer with 64 chips per unit)OAM (v5e pod, up to 256 chips)
Announced2024-12-032023-08-29
Released2025-01-012023-11-01

Robots running AWS Trainium 2

No robots publicly running it yet.

Robots running Google TPU v5e

No robots publicly running it yet.

Common questions

AWS Trainium 2 vs Google TPU v5e: which is faster for training?

AWS Trainium 2 has 6.60x the dense FP16/BF16 throughput of the other (AWS Trainium 2: 1,300 TFLOPS; Google TPU v5e: 197 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 Google TPU v5e: which has more memory?

AWS Trainium 2 carries more HBM (AWS Trainium 2: 96 GB HBM3; Google TPU v5e: 16 GB HBM2). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.

AWS Trainium 2 vs Google TPU v5e: which is more power-efficient?

Dense FP16/BF16 TFLOPS per watt: AWS Trainium 2 2.60 (1,300 ÷ 500 W); Google TPU v5e 1.16 (197 ÷ 170 W). AWS Trainium 2 wins at the die level; system-level efficiency also depends on cooling and interconnect.

AWS Trainium 2 vs Google TPU v5e: which is more widely used?

AWS Trainium 2: 0 robots and 3 data centers publicly running it. Google TPU v5e: 0 robots and 1 data center. Empty here means no operator has said publicly, not zero adoption in the market.

See also: every chip comparison · AWS Trainium 2 full page · Google TPU v5e full page.