Chip comparison
Huawei Ascend 910D vs NVIDIA Jetson AGX Thor
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 Jetson AGX Thor |
|---|---|---|
| Process node | SMIC N+2 (~7nm) | TSMC 4NP |
| TDP | 800 W | 130 W |
| Memory | 192 GB HBM3 | 128 GB LPDDR5X |
| Memory bandwidth | 4,000 GB/s | 273 GB/s |
| FP16 (dense) | 1,200 TFLOPS | — |
| BF16 (dense) | 1,200 TFLOPS | — |
| FP8 (dense) | 2,400 TFLOPS | 2,070 TFLOPS |
| INT8 (dense) | — | 2,070 TOPS |
| Form factor | OAM | Module (AGX Thor) |
| Announced | 2025-04-01 | 2024-03-18 |
| Released | 2025-12-01 | 2025-08-01 |
Robots running Huawei Ascend 910D
No robots publicly running it yet.
Data centers with Huawei Ascend 910D
No data centers publicly running it yet.
Data centers with NVIDIA Jetson AGX Thor
No data centers publicly running it yet.
Common questions
Huawei Ascend 910D vs NVIDIA Jetson AGX Thor: which is faster for training?
Huawei Ascend 910D has 1.16x the dense FP8 throughput of the other (Huawei Ascend 910D: 2,400 TFLOPS; NVIDIA Jetson AGX Thor: 2,070 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 Jetson AGX Thor: which has more memory?
Huawei Ascend 910D carries more HBM (Huawei Ascend 910D: 192 GB HBM3; NVIDIA Jetson AGX Thor: 128 GB LPDDR5X). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.
Huawei Ascend 910D vs NVIDIA Jetson AGX Thor: which is more power-efficient?
Dense FP8 TFLOPS per watt: Huawei Ascend 910D 3.00 (2,400 ÷ 800 W); NVIDIA Jetson AGX Thor 15.92 (2,070 ÷ 130 W). NVIDIA Jetson AGX Thor wins at the die level; system-level efficiency also depends on cooling and interconnect.
Huawei Ascend 910D vs NVIDIA Jetson AGX Thor: which is more widely used?
Huawei Ascend 910D: 0 robots and 0 data centers publicly running it. NVIDIA Jetson AGX Thor: 11 robots and 0 data centers. Empty here means no operator has said publicly, not zero adoption in the market.
See also: every chip comparison · Huawei Ascend 910D full page · NVIDIA Jetson AGX Thor full page.