案例研究：使用 Hugging Face Infinity 與現代 CPU 實現毫秒級延遲
Original: Case Study: Millisecond Latency using Hugging Face Infinity and modern CPUs
This case study focuses on the performance of "Hugging Face Infinity" — Hugging Face's high-performance inference container solution — on…
本案例研究探討了 Hugging Face Infinity 在現代 CPU（如 Intel Xeon）上的效能表現。透過硬體加速與優化技術，Infinity 能在 CPU 上實現單數位毫秒級的推理延遲。這為企業提供了一種高性價比、無需依賴昂貴 GPU 的 Transformer 模型部署選擇，特別適合文本分類與特徵提取等任務。
This case study focuses on the performance of "Hugging Face Infinity" — Hugging Face's high-performance inference container solution — on modern CPUs. Traditionally, deploying Transformer models has been heavily reliant on GPUs to meet low-latency requirements, but this comes with high infrastructure costs and supply constraints.
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