AMD MI300X vs. NVIDIA H100: Mixtral 8x7B Inference Benchmark

Nvidia has historically dominated AI workloads, but there is growing interest in AMD's MI300X, which offers better specifications than Nvidia's H100 SXM. Despite this, Nvidia's CUDA software remains more popular than AMD's ROCm for machine learning applications. Benchmarks comparing the two GPUs on MistralAI's Mixtral 8x7B LLM indicate that the MI300X outperforms the H100 SXM at small and large batch sizes due to its larger VRAM, though it struggles at medium batch sizes. The MI300X is also more cost-effective at very low and very high batch sizes, whereas the H100 SXM provides better throughput and cost-efficiency at medium batch sizes. Serving benchmarks show that the MI300X has lower latency and consistent performance under high loads, while the H100 SXM excels in throughput at smaller batch sizes. The choice between these GPUs depends on specific workload requirements and the balance between throughput and latency needed.