NVIDIA A10 vs A100 GPUs for LLM and Stable Diffusion inference

This post provides a technical comparison of NVIDIA A10 and A100 GPUs for LLM and Stable Diffusion inference. It details their architectural differences (Tensor Cores, VRAM, memory type), benchmarks their performance on specific models (Llama 2, Stable Diffusion), and analyzes their cost-effectiveness for both latency-critical and throughput-oriented workloads. It also discusses the use of multi-GPU instances (multiple A10s vs. a single A100) as a strategy for balancing cost and performance for larger models or higher throughput requirements.