NVIDIA A10 vs A10G for ML model inference

This post analyzes the performance characteristics of NVIDIA A10 and A10G GPUs for ML model inference. It details their specifications, highlighting similarities in VRAM and bandwidth, and differences in tensor core compute. The analysis proves their interchangeability for most memory-bound inference tasks by comparing ops:byte ratios to the arithmetic intensity of Llama 2 7B. It also discusses potential advantages of the A10 in batched inference and surveys other 24GB GPUs.