Chip comparison
Huawei Ascend 910D vs NVIDIA V100 Tensor Core GPU
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 910D | NVIDIA V100 Tensor Core GPU |
|---|---|---|
| Process node | SMIC N+2 (~7nm) | TSMC 12FFN |
| Transistors (B) | — | 21.1 |
| Die size | — | 815 mm² |
| TDP | 800 W | 300 W |
| Memory | 192 GB HBM3 | 32 GB HBM2 |
| Memory bandwidth | 4,000 GB/s | 900 GB/s |
| FP16 (dense) | 1,200 TFLOPS | 125 TFLOPS |
| BF16 (dense) | 1,200 TFLOPS | — |
| FP8 (dense) | 2,400 TFLOPS | — |
| Form factor | OAM | SXM2 / PCIe |
| Announced | 2025-04-01 | 2017-05-10 |
| Released | 2025-12-01 | 2017-12-01 |
Robots running Huawei Ascend 910D
No robots publicly running it yet.
Robots running NVIDIA V100 Tensor Core GPU
No robots publicly running it yet.
Data centers with Huawei Ascend 910D
No data centers publicly running it yet.
Data centers with NVIDIA V100 Tensor Core GPU
No data centers publicly running it yet.
Common questions
Huawei Ascend 910D vs NVIDIA V100 Tensor Core GPU: which is faster for training?
Huawei Ascend 910D has 19.20x the dense FP16/BF16 throughput of the other (Huawei Ascend 910D: 2,400 TFLOPS; NVIDIA V100 Tensor Core GPU: 125 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 NVIDIA V100 Tensor Core GPU: which has more memory?
Huawei Ascend 910D carries more HBM (Huawei Ascend 910D: 192 GB HBM3; NVIDIA V100 Tensor Core GPU: 32 GB HBM2). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.
Huawei Ascend 910D vs NVIDIA V100 Tensor Core GPU: which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: Huawei Ascend 910D 3.00 (2,400 ÷ 800 W); NVIDIA V100 Tensor Core GPU 0.42 (125 ÷ 300 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 · NVIDIA V100 Tensor Core GPU full page.