Huawei Atlas 200I A2 8 TOPS vs Huawei Atlas 300I Pro
The Atlas 300I Pro delivers 17.5x the FP16 throughput of the Atlas 200I A2 (70 vs 4 TFLOPS dense). The Atlas 300I Pro also carries 20 GB more memory (24 GB vs 4 GB).

Huawei Atlas 200I A2 8 TOPS
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Huawei Atlas 300I Pro
Full specs →Specifications




Performance (TFLOPS)




FLOPS by Precision
What actually differs
The Atlas 200I A2 is the newer part: Da Vinci, launched in 2023, against the Atlas 300I Pro's Da Vinci from 2021. 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 Atlas 200I A2 against the Atlas 300I Pro: FP16 4 vs 70 TFLOPS. Sparse figures, where the vendor publishes them, appear under each dense number in the performance table.
Memory is 4 GB against 24 GB, fed at 26 GB/s versus 205 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 Atlas 200I A2 faster than the Atlas 300I Pro?
At FP16 precision the Atlas 300I Pro reaches 70 TFLOPS dense against 4 TFLOPS for the Atlas 200I A2. The performance table on this page lists every published precision for both GPUs.
Which has more memory, the Atlas 200I A2 or the Atlas 300I Pro?
The Atlas 300I Pro carries 24 GB of memory versus 4 GB for the Atlas 200I A2. Memory bandwidth is 26 GB/s for the Atlas 200I A2 and 205 GB/s for the Atlas 300I Pro.
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