DEPLOYDatabase

Chip comparison

AWS Trainium (Trn1) vs SambaNova SN40L

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)SambaNova SN40L
Process nodeTSMC N7TSMC N5
TDP500 W700 W
Memory32 GB HBM2e1500 GB DDR5 (three-tier: 64 MB SRAM + 64 GB HBM3 + 1.5 TB DDR5)
Memory bandwidth820 GB/s
FP16 (dense)638 TFLOPS
BF16 (dense)210 TFLOPS
FP8 (dense)1,250 TFLOPS
Form factorTrn1 EC2 instancePCIe (SN40L DataScale system)
Announced2020-12-012023-09-19
Released2022-10-012024-01-01

Robots running AWS Trainium (Trn1)

No robots publicly running it yet.

Robots running SambaNova SN40L

No robots publicly running it yet.

Data centers with AWS Trainium (Trn1)

No data centers publicly running it yet.

Data centers with SambaNova SN40L

No data centers publicly running it yet.

Common questions

AWS Trainium (Trn1) vs SambaNova SN40L: which is faster for training?

SambaNova SN40L has 5.95x the dense FP16/BF16 throughput of the other (AWS Trainium (Trn1): 210 TFLOPS; SambaNova SN40L: 1,250 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 SambaNova SN40L: which has more memory?

SambaNova SN40L carries more HBM (AWS Trainium (Trn1): 32 GB HBM2e; SambaNova SN40L: 1500 GB DDR5 (three-tier: 64 MB SRAM + 64 GB HBM3 + 1.5 TB DDR5)). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.

AWS Trainium (Trn1) vs SambaNova SN40L: which is more power-efficient?

Dense FP16/BF16 TFLOPS per watt: AWS Trainium (Trn1) 0.42 (210 ÷ 500 W); SambaNova SN40L 1.79 (1,250 ÷ 700 W). SambaNova SN40L wins at the die level; system-level efficiency also depends on cooling and interconnect.

See also: every chip comparison · AWS Trainium (Trn1) full page · SambaNova SN40L full page.