DEPLOYDatabase

Chip comparison

AWS Trainium (Trn1) vs Tenstorrent Wormhole

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)Tenstorrent Wormhole
Process nodeTSMC N7GlobalFoundries 12nm
TDP500 W160 W
Memory32 GB HBM2e12 GB GDDR6
Memory bandwidth820 GB/s288 GB/s
FP16 (dense)148 TFLOPS
BF16 (dense)210 TFLOPS
INT8 (dense)590 TOPS
Form factorTrn1 EC2 instancePCIe (n300, n150)
Announced2020-12-012024-07-01
Released2022-10-012024-08-01

Robots running AWS Trainium (Trn1)

No robots publicly running it yet.

Robots running Tenstorrent Wormhole

No robots publicly running it yet.

Data centers with AWS Trainium (Trn1)

No data centers publicly running it yet.

Data centers with Tenstorrent Wormhole

No data centers publicly running it yet.

Common questions

AWS Trainium (Trn1) vs Tenstorrent Wormhole: which is faster for training?

AWS Trainium (Trn1) has 1.42x the dense FP16/BF16 throughput of the other (AWS Trainium (Trn1): 210 TFLOPS; Tenstorrent Wormhole: 148 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 Tenstorrent Wormhole: which has more memory?

AWS Trainium (Trn1) carries more HBM (AWS Trainium (Trn1): 32 GB HBM2e; Tenstorrent Wormhole: 12 GB GDDR6). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.

AWS Trainium (Trn1) vs Tenstorrent Wormhole: which is more power-efficient?

Dense FP16/BF16 TFLOPS per watt: AWS Trainium (Trn1) 0.42 (210 ÷ 500 W); Tenstorrent Wormhole 0.93 (148 ÷ 160 W). Tenstorrent Wormhole wins at the die level; system-level efficiency also depends on cooling and interconnect.

See also: every chip comparison · AWS Trainium (Trn1) full page · Tenstorrent Wormhole full page.