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NVIDIA H800 (2023) vs Huawei Ascend 910C: Spec Comparison & Buyer's Guide

In AI infrastructure selection, NVIDIA H800 (2023) and Huawei Ascend 910C are two accelerators frequently compared. This article contrasts them item by item — architecture, compute, memory, power, and release cadence — to help you quickly judge which fits training or inference workloads.

Spec Comparison Table

VendorNVIDIA H800 (2023)Huawei Ascend 910C
VendorNVIDIAHuawei
ArchitectureHopper GH100Da Vinci
ProcessTSMC 4N (4nm)7nm -class
Release Date20232024-04-24
FP8 Compute3,958 TFLOPS
FP16 Compute1,979 TFLOPS
FP32 Compute67 TFLOPS
INT8 Compute3,958 TOPS
Memory Type
Memory Capacity8× HBM3
Memory Bandwidth3.35 TB/s
TDP Power350W310 W

Key Differences

  • Power: Huawei Ascend 910C has a TDP of 310 W, lower than NVIDIA H800 (2023)'s 350W, friendlier to datacenter PUE and cooling.

Selection Advice

  • When chasing extreme single-card compute and a mature toolchain, prioritize NVIDIA H800 (2023); if budget, power wall, or local support are hard constraints, Huawei Ascend 910C often fits better. Use this site's AI Compute Card Comparison Tool to validate multiple chips side-by-side before deciding.

FAQ

What are the main differences between NVIDIA H800 (2023) and Huawei Ascend 910C?

The core difference is architecture and compute density: NVIDIA H800 (2023) uses Hopper GH100, FP8 ~3,958 TFLOPS, memory —; Huawei Ascend 910C uses Da Vinci, FP8 ~No public FP8 data, memory 8× HBM3. See the comparison table above.

What is the TDP (power) of NVIDIA H800 (2023)?

NVIDIA H800 (2023) has a TDP of 350W; actual whole-system power also includes board, fans, and PUE.

Which is better for large-model training / inference?

Training values memory capacity, bandwidth, and multi-card interconnect; inference values single-card throughput and power efficiency. Combine the "Key Differences" and "Selection Advice" above with your batch size, model size, and SLA.

How much do NVIDIA H800 (2023) and Huawei Ascend 910C differ in memory capacity?

NVIDIA H800 (2023) is —, Huawei Ascend 910C is 8× HBM3; the gap directly affects loadable model size and context length.