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Chip comparison

Cambricon MLU370-X8 vs Huawei Ascend 910C

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.

FieldCambricon MLU370-X8Huawei Ascend 910C
Process nodeTSMC N7SMIC N+2 (~7nm)
TDP250 W500 W
Memory48 GB LPDDR5128 GB HBM2e
Memory bandwidth3,200 GB/s
FP16 (dense)96 TFLOPS800 TFLOPS
BF16 (dense)800 TFLOPS
INT8 (dense)256 TOPS1,600 TOPS
Form factorPCIeOAM
Announced2022-03-252024-09-19
Released2025-01-01

Robots running Cambricon MLU370-X8

No robots publicly running it yet.

Robots running Huawei Ascend 910C

No robots publicly running it yet.

Data centers with Cambricon MLU370-X8

No data centers publicly running it yet.

Data centers with Huawei Ascend 910C

No data centers publicly running it yet.

Common questions

Cambricon MLU370-X8 vs Huawei Ascend 910C: which is faster for training?

Huawei Ascend 910C has 8.33x the dense FP16/BF16 throughput of the other (Cambricon MLU370-X8: 96 TFLOPS; Huawei Ascend 910C: 800 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.

Cambricon MLU370-X8 vs Huawei Ascend 910C: which has more memory?

Huawei Ascend 910C carries more HBM (Cambricon MLU370-X8: 48 GB LPDDR5; Huawei Ascend 910C: 128 GB HBM2e). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.

Cambricon MLU370-X8 vs Huawei Ascend 910C: which is more power-efficient?

Dense FP16/BF16 TFLOPS per watt: Cambricon MLU370-X8 0.38 (96 ÷ 250 W); Huawei Ascend 910C 1.60 (800 ÷ 500 W). Huawei Ascend 910C wins at the die level; system-level efficiency also depends on cooling and interconnect.

See also: every chip comparison · Cambricon MLU370-X8 full page · Huawei Ascend 910C full page.