Intel® AI for Enterprise Inference - Llama-3.1-8B-Instruct
This deployment package enables seamless hosting of the meta-llama/Llama-3.1-8B-Instruct language model on Intel® Xeon® processors using the VLLM CPU-optimized Docker image.
ExploreProduct Description
Overview
This solution enables high-performance deployment of the Llama-3.1-8B-Instruct model - an instruction-tuned, 8-billion-parameter transformer developed by Meta (Llama 3.1 series)-on Intel® Xeon® 6 processors using a vLLM CPU-optimized Docker image. Llama-3.1-8B-Instruct is specifically tuned for multilingual, assistant-style tasks such as conversational agents, summarization, question answering, code generation, and tool-enabled dialogues. Available via Hugging Face under the meta-llama/Llama-3.1-8B-Instruct model card, it supports a broad range of languages - including, but not limited to, English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai - and excels in both general and instruction-following capabilities.
The deployment leverages vLLM, a high-throughput inference engine optimized for CPU environments. VLLM uses PagedAttention, Tensor Parallelism, and PyTorch 2.0 to deliver efficient memory usage and low-latency inference. The Docker image is tuned for Intel® Xeon® 6 processors, which feature advanced architectural enhancements including Efficient-cores (E-cores) and Performance-cores (P-cores), support for Intel® Advanced Matrix Extensions (Intel® AMX), and Intel® Deep Learning Boost (DL Boost). These features accelerate AI workloads and enable scalable deployment of LLMs in cloud, edge, and enterprise environments.
This containerized solution provides a plug-and-play experience for deploying Llama-3.1-8B-Instruct on CPU-only infrastructure, eliminating the need for GPUs while maintaining competitive performance. It supports RESTful APIs, batch inference, and integration into existing ML pipelines, making it ideal for developers, researchers, and enterprises seeking cost-effective, scalable, and production-ready LLM deployment.
Highlights
Run Llama-3.1-8B-Instruct on Intel® Xeon® 6: Deploy Hugging Face instruction-tuned LLM efficiently on CPU-only infrastructure using Intel® AMX and DL Boost.
vLLM-Powered CPU Inference: Use vLLM with PyTorch 2.0 and PagedAttention for fast, scalable inference - no GPU required.