NVIDIA A16 16GB vs NVIDIA A10G 24GB
The A10G delivers 3.9x the FP16 throughput of the A16 (70 vs 18 TFLOPS dense). The A10G also carries 8 GB more memory (24 GB vs 16 GB).
NVIDIA A16 16GB
Full specs →NVIDIA A10G 24GB
Full specs →Specifications
Performance (TFLOPS)
FLOPS by Precision
What actually differs
The A10G is the newer part: Ampere, launched in 2022, against the A16's Ampere 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 A16 against the A10G: FP32 4.5 vs 35 TFLOPS, FP16 18 vs 70 TFLOPS. Sparse figures, where the vendor publishes them, appear under each dense number in the performance table.
Memory is 16 GB against 24 GB, fed at 200 GB/s versus 600 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 A16 faster than the A10G?
At FP16 precision the A10G reaches 70 TFLOPS dense against 18 TFLOPS for the A16. The performance table on this page lists every published precision for both GPUs.
Which has more memory, the A16 or the A10G?
The A10G carries 24 GB of memory versus 16 GB for the A16. Memory bandwidth is 200 GB/s for the A16 and 600 GB/s for the A10G.
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