Huawei Ascend 910A vs Huawei Atlas 300I Duo 96GB
The Ascend 910A delivers 83% more FP16 throughput than the Atlas 300I Duo (256 vs 140 TFLOPS dense). The Atlas 300I Duo counters with 64 GB more memory (96 GB vs 32 GB).
Huawei Ascend 910A
Full specs →Huawei Atlas 300I Duo 96GB
Full specs →Specifications
Performance (TFLOPS)
FLOPS by Precision
What actually differs
The Atlas 300I Duo is the newer part: Da Vinci, launched in 2022, against the Ascend 910A's Da Vinci from 2019. Newer architectures typically add lower-precision formats and better throughput per watt, so check the precision rows your workload actually uses.
Dense throughput for the Ascend 910A against the Atlas 300I Duo: FP16 256 vs 140 TFLOPS. Sparse figures, where the vendor publishes them, appear under each dense number in the performance table.
Memory is 32 GB against 96 GB, fed at 1.2 TB/s versus 408 GB/s. More memory per GPU means larger models fit before you have to shard across cards, which often matters more than raw TFLOPS for inference.
For LLM training and inference, weight the FP8 and FP16 rows and memory capacity most heavily. For scientific and HPC workloads, the FP64 row is the one to read.
Frequently asked questions
Is the Ascend 910A faster than the Atlas 300I Duo?
At FP16 precision the Ascend 910A reaches 256 TFLOPS dense against 140 TFLOPS for the Atlas 300I Duo. The performance table on this page lists every published precision for both GPUs.
Which has more memory, the Ascend 910A or the Atlas 300I Duo?
The Atlas 300I Duo carries 96 GB of memory versus 32 GB for the Ascend 910A. Memory bandwidth is 1.2 TB/s for the Ascend 910A and 408 GB/s for the Atlas 300I Duo.
How much power do the Ascend 910A and the Atlas 300I Duo draw?
The Ascend 910A is rated at 310 W TDP and the Atlas 300I Duo at 150 W. On FP32 throughput per watt, the Ascend 910A is the more efficient part.
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