Chip comparison
Huawei Ascend 910C 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 910C | NVIDIA Jetson AGX Thor |
|---|---|---|
| Process node | SMIC N+2 (~7nm) | TSMC 4NP |
| TDP | 500 W | 130 W |
| Memory | 128 GB HBM2e | 128 GB LPDDR5X |
| Memory bandwidth | 3,200 GB/s | 273 GB/s |
| FP16 (dense) | 800 TFLOPS | — |
| BF16 (dense) | 800 TFLOPS | — |
| FP8 (dense) | — | 2,070 TFLOPS |
| INT8 (dense) | 1,600 TOPS | 2,070 TOPS |
| Form factor | OAM | Module (AGX Thor) |
| Announced | 2024-09-19 | 2024-03-18 |
| Released | 2025-01-01 | 2025-08-01 |
Robots running Huawei Ascend 910C
No robots publicly running it yet.
Data centers with Huawei Ascend 910C
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 910C vs NVIDIA Jetson AGX Thor: which is faster for training?
NVIDIA Jetson AGX Thor has 2.59x the dense FP16/BF16 throughput of the other (Huawei Ascend 910C: 800 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 910C vs NVIDIA Jetson AGX Thor: which has more memory?
NVIDIA Jetson AGX Thor carries more HBM (Huawei Ascend 910C: 128 GB HBM2e; 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 910C vs NVIDIA Jetson AGX Thor: which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: Huawei Ascend 910C 1.60 (800 ÷ 500 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 910C vs NVIDIA Jetson AGX Thor: which is more widely used?
Huawei Ascend 910C: 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 910C full page · NVIDIA Jetson AGX Thor full page.