Chip comparison
Huawei Ascend 910C vs NVIDIA L40S
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.
| Field | Huawei Ascend 910C | NVIDIA L40S |
|---|---|---|
| Process node | SMIC N+2 (~7nm) | TSMC 4N |
| Transistors (B) | — | 76.3 |
| TDP | 500 W | 350 W |
| Memory | 128 GB HBM2e | 48 GB GDDR6 |
| Memory bandwidth | 3,200 GB/s | 864 GB/s |
| FP16 (dense) | 800 TFLOPS | 362 TFLOPS |
| BF16 (dense) | 800 TFLOPS | 362 TFLOPS |
| FP8 (dense) | — | 733 TFLOPS |
| INT8 (dense) | 1,600 TOPS | 733 TOPS |
| Form factor | OAM | PCIe |
| Announced | 2024-09-19 | 2023-08-08 |
| Released | 2025-01-01 | — |
Robots running Huawei Ascend 910C
No robots publicly running it yet.
Robots running NVIDIA L40S
No robots publicly running it yet.
Data centers with Huawei Ascend 910C
No data centers publicly running it yet.
Data centers with NVIDIA L40S
No data centers publicly running it yet.
Common questions
Huawei Ascend 910C vs NVIDIA L40S: which is faster for training?
Huawei Ascend 910C has 1.09x the dense FP16/BF16 throughput of the other (Huawei Ascend 910C: 800 TFLOPS; NVIDIA L40S: 733 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.
Huawei Ascend 910C vs NVIDIA L40S: which has more memory?
Huawei Ascend 910C carries more HBM (Huawei Ascend 910C: 128 GB HBM2e; NVIDIA L40S: 48 GB GDDR6). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.
Huawei Ascend 910C vs NVIDIA L40S: which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: Huawei Ascend 910C 1.60 (800 ÷ 500 W); NVIDIA L40S 2.09 (733 ÷ 350 W). NVIDIA L40S wins at the die level; system-level efficiency also depends on cooling and interconnect.
See also: every chip comparison · Huawei Ascend 910C full page · NVIDIA L40S full page.