Posts by Wei-Ting Liao
Technical Dive into AMD’s MLPerf Inference v5.1 Submission
- 09 September 2025
In the rapidly evolving landscape of artificial intelligence, the demand for reliable and efficient model inference has never been greater. With advancements in large language models (LLMs) and a growing reliance on real-time applications, benchmarks are critical in evaluating how well AI systems perform under varying conditions. Enter MLPerf Inference: Datacenter v5.1 — a significant update to the well-respected benchmarking suite that assesses inference performance across a wide array of models and use cases, catering especially to data centers.
Reproducing the AMD Instinct™ GPUs MLPerf Inference v5.1 Submission
- 09 September 2025
MLPerf Inference v5.1 marks AMD’s third round of submissions and the most ambitious yet. This round features submissions on AMD Instinct MI325X and MI355X systems, including multi-node inference and models in MXFP4 datatype. Building upon the success in MLPerf Inference v5.0, AMD has submitted improved results for Llama 2 70B and SDXL on the MI325X platform in this round using new optimization techniques. For a deeper look at these optimizations, see our Technical Dive into AMD’s MLPerf Inference v5.1 Submission. Additionally, explore how we optimized Llama 3.1 405B through pruning and fine-tuning in Slim Down Your Llama: Pruning & Fine-Tuning for Maximum Performance. In addition, AMD has made submissions for the following workloads:
Reproducing the AMD Instinct™ GPUs MLPerf Inference v5.0 Submission
- 02 April 2025
Building upon the success of our MLPerf Inference v4.1 submission, AMD has submitted results for two popular models – Llama 2 70B and Stable Diffusion XL (SDXL) – in the MLPerf Inference v5.0 round. This blog post provides a comprehensive, step-by-step guide on reproducing the results of AMD’s MLPerf submission using ROCm and the AMD Instinct™ MI325X GPUs. Please follow along to independently verify these results and gain hands-on experience with the benchmarking process. If you are interested in learning more about the advanced optimization strategies behind our Llama 2 70B and SDXL inference, from quantization and General Matrix Multiplication (GEMM) tuning to cutting-edge vLLM scheduling and platform enhancements, check out our blog on MLPerf Inference v5.0 optimization strategies.
AMD Instinct™ MI325X GPUs Produce Strong Performance in MLPerf Inference v5.0
- 02 April 2025
AI transformation and its ever-increasing demands of GenAI, LLMs, reasoning models and new advances in inference and training emphasize the need for innovative GPU architectures and products designed and delivered at an accelerated pace. Understanding the performance of AI models on these GPUs is critical for continuous advances in AI deployments and adoption. However, benchmarking AI models is challenging due to their inherent complexity and variety of possible deployments and tasks. Approaching this problem from a cross-industry perspective is preferable to have a benchmark that is comparable across different platforms and vendors. MLPerf is such a benchmark created by a cross-industry MLCommons consortium of which AMD is a founding member.