在 GCP 上的第五代 Intel Xeon 處理器（C4 執行個體）進行語言模型效能基準測試
Original: Benchmarking Language Model Performance on 5th Gen Xeon at GCP
This technical blog post from Hugging Face provides a detailed benchmark of running large language models (LLMs) on Google Cloud Platform's…
Hugging Face 發布在 Google Cloud Platform (GCP) 全新 C4 執行個體上運行語言模型的效能評測。C4 搭載第五代 Intel Xeon 可擴充處理器，內建 Intel AMX 加速技術。測試顯示，透過 Optimum Intel 與 IPEX 優化，CPU 在中小型開源模型（如 Llama 3）的推論上展現出極佳的延遲表現與高性價比，為 GPU 短缺或預算有限的企業提供強大的替代方案。
This technical blog post from Hugging Face provides a detailed benchmark of running large language models (LLMs) on Google Cloud Platform's (GCP) new C4 instances. The C4 instances are powered by 5th-generation Intel Xeon Scalable processors (codenamed Emerald Rapids), whose most critical advantage is the built-in Intel AMX (Advanced Matrix Extensions) hardware acceleration technology, designed specifically for deep learning and matrix computation.
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