Can Huawei’s Ascend 910C Challenge Nvidia’s H100? A Deep Dive into Architecture, Performance, and Strategy

Technical Composition: Dual‑Chip Combination

The "C" in Ascend 910C does not denote a radical new architecture but rather a clever "Clever Combination" of two existing Ascend 910B chips integrated through advanced packaging. By re‑using mature 7 nm process technology, Huawei achieves a performance boost without the risk and expense of developing a brand‑new core.

Old Design, New Use

Rather than pursuing an untested architecture, the strategy leverages proven silicon, allowing faster time‑to‑market and lower R&D costs while still delivering a competitive AI accelerator.

Packaging Choices: Balancing Performance and Cost

The 910C uses a relatively mature packaging approach: each 910B die is placed on its own silicon interposer and then bonded together with an organic substrate. This is less advanced than Nvidia's CoWoS or Foveros solutions, resulting in lower inter‑chip bandwidth—estimated to be 10‑20 times lower than Nvidia's top‑tier packages—but it reduces cost, improves yield, and accelerates volume production.

Performance and Technical Parameters: Gap with Nvidia H100

According to analyst Lennart Heim, the 910C delivers about 800 TFLOPS FP16 performance and roughly 3.2 TB/s memory bandwidth, which translates to roughly 80 % of the performance of Nvidia's 2022 H100. However, the chip’s logical area is about 60 % larger, indicating lower architectural efficiency.

When compared with Nvidia's upcoming B200 series, the 910C falls behind by a factor of three in compute performance and 2.5 × in memory bandwidth, highlighting a widening generational gap.

Compute performance: ~3× lower than B200

Memory bandwidth: ~2.5× lower than B200

Energy efficiency: noticeably worse than the latest Nvidia offerings

Supply Chain and Production: The Source Mystery

Heim speculates that a large portion of the 910C dies may have been sourced from TSMC before export controls tightened, with estimates of up to 3 million 7 nm dies stockpiled via unofficial channels. Additional HBM2E memory modules are also thought to have been secured from Samsung, potentially enabling the assembly of up to 1.4 million 910C accelerators.

If these numbers hold, the combined compute capacity of those accelerators would be comparable to roughly one million Nvidia H100 cards, a scale that could dramatically shift global AI compute rankings.

Strategic Significance in Global AI Competition

Even though the 910C trails the most advanced Western chips, its existence demonstrates China's ability to sustain AI hardware development under export‑control pressure. Heim argues that China can compensate for raw performance gaps by concentrating compute resources on inference workloads and specific industry verticals such as smart cities, transportation, and manufacturing.

The analysis also warns that while a focus on differentiated inference may yield short‑term advantages, long‑term competitiveness still depends on expanding overall compute capacity and advancing process technology.

Conclusion and Outlook

The Ascend 910C is not a breakthrough in raw performance, but it is a strategic milestone that showcases pragmatic engineering, supply‑chain ingenuity, and a clear intent to remain a player in the AI accelerator market. Future developments will hinge on whether Huawei can transition from stockpiled dies to truly domestic 7 nm production and how effectively the ecosystem can leverage the chip for targeted AI applications.