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Chip comparison

AWS Trainium (Trn1) vs Google TPU v4

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 (Trn1)Google TPU v4
Process nodeTSMC N7TSMC N7
TDP500 W192 W
Memory32 GB HBM2e32 GB HBM2
Memory bandwidth820 GB/s1,200 GB/s
BF16 (dense)210 TFLOPS275 TFLOPS
INT8 (dense)275 TOPS
Form factorTrn1 EC2 instanceOAM (per-chip in v4 pod)
Announced2020-12-012021-05-18
Released2022-10-012022-05-01

Robots running AWS Trainium (Trn1)

No robots publicly running it yet.

Robots running Google TPU v4

No robots publicly running it yet.

Data centers with AWS Trainium (Trn1)

No data centers publicly running it yet.

Common questions

AWS Trainium (Trn1) vs Google TPU v4: which is faster for training?

Google TPU v4 has 1.31x the dense FP16/BF16 throughput of the other (AWS Trainium (Trn1): 210 TFLOPS; Google TPU v4: 275 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 Google TPU v4: which has more memory?

Google TPU v4 carries more HBM (AWS Trainium (Trn1): 32 GB HBM2e; Google TPU v4: 32 GB HBM2). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.

AWS Trainium (Trn1) vs Google TPU v4: which is more power-efficient?

Dense FP16/BF16 TFLOPS per watt: AWS Trainium (Trn1) 0.42 (210 ÷ 500 W); Google TPU v4 1.43 (275 ÷ 192 W). Google TPU v4 wins at the die level; system-level efficiency also depends on cooling and interconnect.

AWS Trainium (Trn1) vs Google TPU v4: which is more widely used?

AWS Trainium (Trn1): 0 robots and 0 data centers publicly running it. Google TPU v4: 0 robots and 2 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 · Google TPU v4 full page.