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AMD’s MI300X Outperforms NVIDIA’s H100 for LLM Inference

Jun 13, 2024 - blog.tensorwave.com
The article discusses the performance of AMD's flagship MI300X accelerator in comparison to NVIDIA's Hopper architecture for AI workloads. The MI300X, in collaboration with TensorWave and MK1, has shown impressive results, achieving 33% higher throughput compared to the H100 SXM in real-world AI applications. Despite NVIDIA's more mature software ecosystem, AMD is emerging as a strong competitor in the AI market, especially when considering hardware availability and cost.

The article further provides detailed benchmark tests comparing the MI300X and H100 SXM5 accelerators. The MI300X outperformed the H100 in both offline and online inference tasks for MoE architectures like Mixtral 8x7B. The MI300X not only offers higher throughput but also excels in real-world scenarios requiring fast response times. Given its impressive performance, competitive cost, and hardware availability, the MI300X with MK1 software is recommended for enterprises looking to scale their AI inference capabilities.

Key takeaways:

  • AMD's flagship MI300X accelerator, when paired with MK1's inference software, achieves 33% higher throughput compared to NVIDIA’s Hopper architecture, specifically the H100 SXM, for real-world AI workloads.
  • The MI300X outperforms the H100 in both offline and online inference tasks for Mixture of Expert (MoE) architectures like Mixtral 8x7B.
  • Despite NVIDIA’s software ecosystem being more mature, AMD is emerging as a formidable competitor in the AI market.
  • Given its impressive performance, competitive cost, and hardware availability, the MI300X with MK1 software is an excellent choice for enterprises looking to scale their AI inference capabilities.
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