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Huawei Ascend 910C vs NVIDIA H100 NVL 94GB

The H100 delivers 20% more FP32 throughput than the Ascend 910C (60 vs 50 TFLOPS dense). The Ascend 910C counters with 34 GB more memory (128 GB vs 94 GB).

Ascend 910C: Da Vinci v2 (dual-die), 2025 H100: Hopper, 2023
FP32 dense lead
+20%
H100: 60 vs 50 TFLOPS
Memory
128 vs 94 GB
34 GB more for the Ascend 910C
Bandwidth
3.2 TB/s vs 3.9 TB/s
H100 moves data faster
TDP
600 W vs 400 W
H100 draws 200 W less
See rental pricing from $2.27/hr Download comparison sheet

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Huawei Ascend 910C vs NVIDIA H100 NVL 94GB

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Huawei Ascend 910C

Full specs →

What is the Huawei Ascend 910C?

The Ascend 910C is an NPU from Huawei on the Da Vinci v2 (dual-die) architecture, an accelerator built for AI inference. It is an OAM module, the open accelerator format used in multi-GPU servers. Ascend 910C full specifications →

Can I rent the Ascend 910C in the cloud?

Flopper is not tracking any live rental listings for the Ascend 910C yet. The provider directory lists the clouds that rent comparable accelerators on demand. GPU cloud providers →

How does the Ascend 910C compare with other accelerators?

This page sets the Ascend 910C against the H100. The Ascend 910C is the newer generation of the two. This is a cross-vendor matchup, Huawei against NVIDIA; the Ascend 910C is an OAM module while the H100 is a PCIe card. The compare tool builds the same comparison for any two parts in the catalogue. All GPU comparisons →

Where do the Ascend 910C figures come from?

Every Ascend 910C figure on this page traces to Huawei's own datasheet or specification table. How Flopper verifies specifications →

NVIDIA H100 NVL 94GB

Leads on FP32 Full specs →

What is the NVIDIA H100?

The H100 is a GPU from NVIDIA on the Hopper architecture, an accelerator for AI training, inference and high-performance computing. It is a PCIe add-in card, so it fits standard servers and workstations. H100 full specifications →

Can I rent the H100 in the cloud?

Yes. Cloud providers tracked by Flopper rent the H100 by the hour, and the pricing page compares their current rates and the price history side by side. H100 rental prices →

How does the H100 compare with other accelerators?

This page sets the H100 against the Ascend 910C. The H100 is the older generation of the two. This is a cross-vendor matchup, NVIDIA against Huawei; the H100 is a PCIe card while the Ascend 910C is an OAM module. The compare tool builds the same comparison for any two parts in the catalogue. All GPU comparisons →

Where do the H100 figures come from?

Every H100 figure on this page traces to NVIDIA's own datasheet or specification table. How Flopper verifies specifications →

Specifications

Huawei logo
Ascend 910C
H100
Architecture
Da Vinci v2 (dual-die)Hopper
Launch Year
20252023
Form Factor
OAMPCIe
Memory
128 GB94 GB
Memory Bandwidth
3.2 TB/s3.9 TB/s
TDP
600 W400 W
Process Node
SMIC 7nm4nm

Performance (TFLOPS)

Huawei logo
Ascend 910C
H100
No verified data available30 TFLOPS
50 TFLOPS 60 TFLOPS
No verified data available The vendor publishes only the 2:4 sparse figure for this precision
835 TFLOPS sparse
800 TFLOPS The vendor publishes only the 2:4 sparse figure for this precision
1,671 TFLOPS sparse
800 TFLOPS The vendor publishes only the 2:4 sparse figure for this precision
1,671 TFLOPS sparse
No verified data available The vendor publishes only the 2:4 sparse figure for this precision
3,341 TFLOPS sparse
FP6
No verified data available No verified data available
No verified data available No verified data available
1,600 TOPS The vendor publishes only the 2:4 sparse figure for this precision
3,341 TOPS sparse
Tensor Core
No verified data available60 TFLOPS

Figures are dense. Where a vendor publishes a figure it sits under the dense one and never decides a winner. Hover any precision for its definition, or read the GPU glossary.

FLOPS by Precision

What actually differs

The Ascend 910C is the newer part: Da Vinci v2 (dual-die) (2025) against the H100's Hopper (2023).

The Ascend 910C carries 34 GB more memory (128 GB against 94 GB), so larger models fit on one GPU before you shard. Bandwidth is 3.2 TB/s against 3.9 TB/s, which sets the ceiling on decode speed.

Power is 600 W against 400 W, and at FP32 the H100 does more work per watt. Weight the FP8 and FP16 rows for LLM work and the FP64 row for HPC.

New to the terms? The glossary explains FP64, FP32, TF32, BF16, FP16, FP8, INT8, Sparsity and TFLOPS. For how the generations relate, see NVIDIA architectures explained.

Frequently asked questions

Is the Ascend 910C faster than the H100?

At FP32 precision the H100 reaches 60 TFLOPS dense against 50 TFLOPS for the Ascend 910C. The performance table on this page lists every published precision for both GPUs.

Which should you choose, the Ascend 910C or the H100?

Choose the H100 for training and high-throughput inference: it has 20% more FP32 throughput than the Ascend 910C. Choose the Ascend 910C when the model has to fit on one GPU: it carries 34 GB more memory. The H100 draws 200 W less power, which matters in an air-cooled or power-capped rack. Packaging differs too: the Ascend 910C is an OAM module while the H100 is a PCIe card, so check what your servers accept.

Which has more memory, the Ascend 910C or the H100?

The Ascend 910C carries 128 GB of memory versus 94 GB for the H100. Memory bandwidth is 3.2 TB/s for the Ascend 910C and 3.9 TB/s for the H100.

How much power do the Ascend 910C and the H100 draw?

The Ascend 910C is rated at 600 W TDP and the H100 at 400 W. On FP32 throughput per watt, the H100 is the more efficient part.

How much do the Ascend 910C and the H100 cost to rent?

Live cloud listings tracked by Flopper price no live listings yet for the Ascend 910C, and the H100 from $2.27 per GPU-hour across 5 providers. The rental section on this page links to every provider, rate and the price history for each GPU.

Where to Rent

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Huawei Ascend 910C

No live rental listings tracked for the Ascend 910C yet.

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NVIDIA H100 NVL 94GB

Rent from

$2.27 / GPU-hr

Lowest of 9 live listings across 5 providers · median $3.17

See all H100 rental prices →

Price history and every provider on the pricing page. Some links are affiliate links.

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