DEPLOYDatabase

Chip comparison

Google TPU v4 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.

FieldGoogle TPU v4SambaNova SN40L
Process nodeTSMC N7TSMC N5
TDP192 W700 W
Memory32 GB HBM21500 GB DDR5 (three-tier: 64 MB SRAM + 64 GB HBM3 + 1.5 TB DDR5)
Memory bandwidth1,200 GB/s
FP16 (dense)638 TFLOPS
BF16 (dense)275 TFLOPS
FP8 (dense)1,250 TFLOPS
INT8 (dense)275 TOPS
Form factorOAM (per-chip in v4 pod)PCIe (SN40L DataScale system)
Announced2021-05-182023-09-19
Released2022-05-012024-01-01

Robots running Google TPU v4

No robots publicly running it yet.

Robots running SambaNova SN40L

No robots publicly running it yet.

Data centers with SambaNova SN40L

No data centers publicly running it yet.

Common questions

Google TPU v4 vs SambaNova SN40L: which is faster for training?

SambaNova SN40L has 4.55x the dense FP16/BF16 throughput of the other (Google TPU v4: 275 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.

Google TPU v4 vs SambaNova SN40L: which has more memory?

SambaNova SN40L carries more HBM (Google TPU v4: 32 GB HBM2; 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.

Google TPU v4 vs SambaNova SN40L: which is more power-efficient?

Dense FP16/BF16 TFLOPS per watt: Google TPU v4 1.43 (275 ÷ 192 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.

Google TPU v4 vs SambaNova SN40L: which is more widely used?

Google TPU v4: 0 robots and 2 data centers publicly running it. SambaNova SN40L: 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 · Google TPU v4 full page · SambaNova SN40L full page.