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Chip comparison

Huawei Ascend 910D 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.

FieldHuawei Ascend 910DSambaNova SN40L
Process nodeSMIC N+2 (~7nm)TSMC N5
TDP800 W700 W
Memory192 GB HBM31500 GB DDR5 (three-tier: 64 MB SRAM + 64 GB HBM3 + 1.5 TB DDR5)
Memory bandwidth4,000 GB/s
FP16 (dense)1,200 TFLOPS638 TFLOPS
BF16 (dense)1,200 TFLOPS
FP8 (dense)2,400 TFLOPS1,250 TFLOPS
Form factorOAMPCIe (SN40L DataScale system)
Announced2025-04-012023-09-19
Released2025-12-012024-01-01

Robots running Huawei Ascend 910D

No robots publicly running it yet.

Robots running SambaNova SN40L

No robots publicly running it yet.

Data centers with Huawei Ascend 910D

No data centers publicly running it yet.

Data centers with SambaNova SN40L

No data centers publicly running it yet.

Common questions

Huawei Ascend 910D vs SambaNova SN40L: which is faster for training?

Huawei Ascend 910D has 1.92x the dense FP8 throughput of the other (Huawei Ascend 910D: 2,400 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.

Huawei Ascend 910D vs SambaNova SN40L: which has more memory?

SambaNova SN40L carries more HBM (Huawei Ascend 910D: 192 GB HBM3; 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.

Huawei Ascend 910D vs SambaNova SN40L: which is more power-efficient?

Dense FP8 TFLOPS per watt: Huawei Ascend 910D 3.00 (2,400 ÷ 800 W); SambaNova SN40L 1.79 (1,250 ÷ 700 W). Huawei Ascend 910D wins at the die level; system-level efficiency also depends on cooling and interconnect.

See also: every chip comparison · Huawei Ascend 910D full page · SambaNova SN40L full page.