--- 格式版本: 2 标题: "NVIDIA NIM on AWS Supercharges AI Inference | NVIDIA Blog" 原文链接: "https://blogs.nvidia.com/blog/nim-microservices-aws-inference/" 发布日期: "2026-06-30" 发布时间校准状态: "found" 发布时间来源: "llm:strict_original_body" 发布时间证据: "time class=related-news-date nvidia-article-date datetime=2026-06-30T08:00:57-07:00: Jun 30, 2026" 发布时间校准原因: "该日期来自HTML metadata中的article-date字段，位于标题附近，符合文章发布时间的特征。" 发布时间校准置信度: "1" 发布时间候选数量: 36 发布时间严格候选数量: 12 发布时间原页读取状态: "原页面来自已抓取 HTML" 发布时间未找到原因: "候选日期无效或 LLM 未确认" 发布时间校准时间: "2026-07-20T12:35:24+08:00" 发现时间: "2026-07-20T09:26:26+08:00" 入库时间: "2026-07-20T04:43:08.361Z" 来源平台: "NVIDIA Blog 搜索" 搜索渠道: "source_template" 搜索词: "https://blogs.nvidia.com/?s=AWS" 匹配关键词: [] 相关厂家: - "AWS" - "NVIDIA" - "Meta" 相关专家: [] 内容类型: "网页" 抓取工具: "AgentKey Scrape" 清洗工具: "AgentKey Markdown + LLM 正文裁剪" 原始附件: [] AI优质: "否" AI打分: 35 AI分档: "非优质" AI质检状态: "不通过" AI打分理由: "正文主要讨论NVIDIA NIM微服务在AWS上的软件部署与推理优化，未涉及超节点、AI Rack、机柜级硬件架构、供电、散热或高速互连等核心主题，缺乏技术细节与硬件部署信号，不符合项目关注范围。" AI质检模型: "qwen3.6-plus" AI质检时间: "2026-07-20T12:43:08+08:00" AI主题相关性: 5 AI来源权威性: 15 AI新颖性: 10 AI技术细节: 0 AI商业部署信号: 5 AI完整性: 0 图片摘要: - "✗ ./assets/img-83d2f103.jpg | other | 图片主题为AI基础设施能效（Performance per Watt），与正文NIM软件集成主题不符，疑似其他文章配图。" - "✗ ./assets/img-1f6575f1.png | diagram | 图片主题为NVIDIA Vera CPU，正文未提及该硬件，疑似其他文章配图。" - "✗ ./assets/img-3511966c.jpg | photo | NVIDIA总部大楼照片，属于品牌宣传/装饰性配图，与正文技术主题无直接关联。" - "✓ ./assets/img-e47e99dc.png | infographic | 展示NVIDIA推理软件栈概念图，体现NIM微服务在AWS上实现高效、低成本推理的能力。" 采集批次: "2026年7月20日9点23分34秒" 采集批次ID: "20260720-092334-062" 去重键: "https://blogs.nvidia.com/blog/nim-microservices-aws-inference" --- Generative AI is rapidly transforming industries, driving demand for secure, high-performance inference solutions to scale increasingly complex models efficiently and cost-effectively. Expanding its collaboration with NVIDIA, Amazon Web Services (AWS) revealed today at its annual AWS re:Invent conference that it has extended [NVIDIA NIM microservices](https://www.nvidia.com/en-us/ai/) across key AWS AI services to support faster AI inference and lower latency for generative AI applications. NVIDIA NIM microservices are now available directly from the AWS Marketplace, as well as [Amazon Bedrock Marketplace](https://aws.amazon.com/blogs/machine-learning/amazon-bedrock-marketplace-now-includes-nvidia-models-introducing-nvidia-nemotron-4-nim-microservices/) and [Amazon SageMaker](https://aws.amazon.com/blogs/machine-learning/speed-up-your-ai-inference-workloads-with-new-nvidia-powered-capabilities-in-amazon-sagemaker/) JumpStart, making it even easier for developers to deploy NVIDIA-optimized inference for commonly used models at scale. NVIDIA NIM, part of the [NVIDIA AI Enterprise](https://www.nvidia.com/en-us/data-center/products/ai-enterprise/) software platform available in the [AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-ozgjkov6vq3l6), provides developers with a set of easy-to-use microservices designed for secure, reliable deployment of high-performance, enterprise-grade AI model inference across clouds, data centers and workstations. These prebuilt containers are built on robust inference engines, such as [NVIDIA Triton Inference Server](https://developer.nvidia.com/triton-inference-server), NVIDIA TensorRT, [NVIDIA TensorRT-LLM](https://developer.nvidia.com/tensorrt) and PyTorch, and support a broad spectrum of AI models — from open-source community ones to [NVIDIA AI Foundation](https://www.nvidia.com/en-us/ai-data-science/foundation-models/) models and custom ones. NIM microservices can be deployed across various AWS services, including Amazon Elastic Compute Cloud (EC2), Amazon Elastic Kubernetes Service (EKS) and Amazon SageMaker. Developers can preview over 100 NIM microservices built from commonly used models and model families, including Meta’s Llama 3, Mistral AI’s Mistral and Mixtral, NVIDIA’s Nemotron, Stability AI’s SDXL and many more on the [NVIDIA API catalog](http://build.nvidia.com/). The most commonly used ones are available for self-hosting to deploy on AWS services and are optimized to run on NVIDIA accelerated computing instances on AWS. NIM microservices now available directly from AWS include: - [**NVIDIA Nemotron-4**](https://aws.amazon.com/marketplace/pp/prodview-cjge44tau4g36), available in Amazon Bedrock Marketplace, Amazon SageMaker Jumpstart and AWS Marketplace. This is a cutting-edge LLM designed to generate diverse synthetic data that closely mimics real-world data, enhancing the performance and robustness of custom LLMs across various domains. - [**Llama** **3.1 8B-Instruct**](https://aws.amazon.com/marketplace/pp/prodview-eu7sja3mcripu), available on AWS Marketplace. This 8-billion-parameter multilingual large language model is pretrained and instruction-tuned for language understanding, reasoning and text-generation use cases. - [**Llama** **3.1 70B-Instruct**](https://aws.amazon.com/marketplace/pp/prodview-wvgruwuilumfo), available on AWS Marketplace. This 70-billion-parameter pretrained, instruction-tuned model is optimized for multilingual dialogue. - [**Mixtral** **8x7B Instruct v0.1**](https://aws.amazon.com/marketplace/pp/prodview-arpznv6pwje6m), available on AWS Marketplace. This high-quality sparse mixture of experts model with open weights can follow instructions, complete requests and generate creative text formats. ## NIM on AWS for Everyone Customers and partners across industries are tapping NIM on AWS to get to market faster, maintain security and control of their generative AI applications and data, and lower costs. SoftServe, an IT consulting and digital services provider, has developed six generative AI solutions fully deployed on AWS and accelerated by NVIDIA NIM and AWS services. The solutions, available on AWS Marketplace, include [SoftServe Gen AI Drug Discovery](https://www.softserveinc.com/en-us/news/drug-discovery-with-nvidia-at-aws-reinvent-2024), SoftServe Gen AI Industrial Assistant, Digital Concierge, Multimodal RAG System, Content Creator and Speech Recognition Platform. They’re all based on [NVIDIA AI Blueprints](https://www.nvidia.com/en-us/ai-data-science/ai-workflows/), comprehensive reference workflows that accelerate AI application development and deployment and feature NVIDIA acceleration libraries, software development kits and NIM microservices for AI agents, digital twins and more. ## Start Now With NIM on AWS Developers can deploy NVIDIA NIM microservices on AWS according to their unique needs and requirements. By doing so, developers and enterprises can achieve high-performance AI with NVIDIA-optimized inference containers across various AWS services. Visit the [NVIDIA API catalog](https://build.nvidia.com/explore/discover) to try out over 100 different NIM-optimized models, and request either a developer license or 90-day NVIDIA AI Enterprise trial license to get started deploying the microservices on AWS services. Developers can also explore NIM microservices in the AWS Marketplace, Amazon Bedrock Marketplace or Amazon SageMaker JumpStart. *See* [*notice*](https://www.nvidia.com/en-us/about-nvidia/legal-info/) *regarding software product information.* ![How NVIDIA’s Inference Software Stack Powers the Lowest Token Cost](./assets/img-e47e99dc.png)