DEPLOYDatabase

Chip comparison

Huawei Ascend 910C vs Tenstorrent Wormhole

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.

FieldHuawei Ascend 910CTenstorrent Wormhole
Process nodeSMIC N+2 (~7nm)GlobalFoundries 12nm
TDP500 W160 W
Memory128 GB HBM2e12 GB GDDR6
Memory bandwidth3,200 GB/s288 GB/s
FP16 (dense)800 TFLOPS148 TFLOPS
BF16 (dense)800 TFLOPS
INT8 (dense)1,600 TOPS590 TOPS
Form factorOAMPCIe (n300, n150)
Announced2024-09-192024-07-01
Released2025-01-012024-08-01

Robots running Huawei Ascend 910C

No robots publicly running it yet.

Robots running Tenstorrent Wormhole

No robots publicly running it yet.

Data centers with Huawei Ascend 910C

No data centers publicly running it yet.

Data centers with Tenstorrent Wormhole

No data centers publicly running it yet.

Common questions

Huawei Ascend 910C vs Tenstorrent Wormhole: which is faster for training?

Huawei Ascend 910C has 5.41x the dense FP16/BF16 throughput of the other (Huawei Ascend 910C: 800 TFLOPS; Tenstorrent Wormhole: 148 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 Tenstorrent Wormhole: which has more memory?

Huawei Ascend 910C carries more HBM (Huawei Ascend 910C: 128 GB HBM2e; Tenstorrent Wormhole: 12 GB GDDR6). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.

Huawei Ascend 910C vs Tenstorrent Wormhole: which is more power-efficient?

Dense FP16/BF16 TFLOPS per watt: Huawei Ascend 910C 1.60 (800 ÷ 500 W); Tenstorrent Wormhole 0.93 (148 ÷ 160 W). Huawei Ascend 910C wins at the die level; system-level efficiency also depends on cooling and interconnect.

See also: every chip comparison · Huawei Ascend 910C full page · Tenstorrent Wormhole full page.