AI inference is where pretrained AI models are deployed to generate new data and is where AI delivers results, powering innovation across every industry. AI models are rapidly expanding in size, complexity, and diversity—pushing the boundaries of what’s possible. For the successful use of AI inference, organizations need a full-stack approach that supports the end-to-end AI life cycle and tools that enable teams to meet their goals in the new scaling laws era.
How to Get Started With AI Inference
Explore a series of expert-led talks on the NVIDIA AI inference platform, including its hardware and software, and how it supports use cases in financial services.
Explore the Benefits of NVIDIA AI for Accelerated Inference
Standardize Deployment
Standardize model deployment across applications, AI frameworks, model architectures, and platforms.
Integrate and Scale With Ease
Integrate easily with tools and platforms on public clouds, on-premises data centers, and at the edge.
Lower Cost
Achieve high throughput and utilization from AI infrastructure, thereby lowering costs.
High Performance
Experience industry-leading performance with the platform that has consistently set multiple records in MLPerf, the leading industry benchmark for AI.
Software
Explore Our AI Inference Software
NVIDIA AI Enterprise consists of NVIDIA NIM™, NVIDIA Triton™ Inference Server, NVIDIA® TensorRT™, and other tools to simplify building, sharing, and deploying AI applications. With enterprise-grade support, stability, manageability, and security, enterprises can accelerate time to value while eliminating unplanned downtime.
The Fastest Path to Generative AI Inference
NVIDIA NIM is a set of easy-to-use microservices designed for secure, reliable deployment of high- performance AI model inferencing across clouds, data centers, and workstations.
Unified Inference Server For All Your AI Workloads
NVIDIA Triton Inference Server is an open-source inference serving software that helps enterprises consolidate bespoke AI model serving infrastructure, shorten the time needed to deploy new AI models in production, and increase AI inferencing and prediction capacity.
NVIDIA TensorRT includes an inference runtime and model optimizations that deliver low latency and high throughput for production applications. The TensorRT ecosystem includes TensorRT, TensorRT-LLM, TensorRT Model Optimizer, and TensorRT Cloud.
A high-performance, serverless AI Inference solution that accelerates AI innovation with auto-scaling, cost-efficient GPU utilization, multi-cloud flexibility, and seamless scalability.
Get unmatched AI performance with NVIDIA AI inference software optimized for NVIDIA-accelerated infrastructure. The NVIDIA Blackwell, H200, L40S, and NVIDIA RTX™ technologies deliver exceptional speed and efficiency for AI inference workloads across data centers, clouds, and workstations.
NVIDIA Blackwell Platform
The NVIDIA Blackwell architecture defines the next chapter in generative AI and accelerated computing, with unparalleled performance, efficiency, and scale. Blackwell features six transformative technologies that will help unlock breakthroughs in data processing, electronic design automation, computer-aided engineering, and quantum computing.
The NVIDIA H200 Tensor Core GPU supercharges generative AI and high-performance computing (HPC) workloads with game-changing performance and memory capabilities. As the first GPU with HBM3e, the H200’s larger and faster memory fuels the acceleration of generative AI and large language models (LLMs) while advancing scientific computing for HPC workloads.
Combining NVIDIA’s full stack of inference serving software with the L40S GPU provides a powerful platform for trained models ready for inference. With support for structural sparsity and a broad range of precisions, the L40S delivers up to 1.7X the inference performance of the NVIDIA A100 Tensor Core GPU.
NVIDIA RTX workstations excel at AI inference, powering AI-augmented professional workflows with scalable solutions. Ideal for deploying AI models with smaller parameters or reduced precision, these workstations enable efficient local AI inferencing for workgroups or departments.
DGX Spark brings the power of NVIDIA Grace Blackwell™ to developer desktops. The GB10 Superchip, combined with 128 GB of unified system memory, lets AI researchers, data scientists, and students work with AI models locally with up to 200 billion parameters.
See how NVIDIA AI inference supports industry use cases, and jump-start your AI development and deployment with curated examples.
Digital Humans
Content Generation
Biomolecular Generation
Fraud Detection
AI Chatbot
Security Vulnerability Analysis
Digital Humans
NVIDIA ACE is a suite of technologies that help developers bring digital humans to life. Several ACE microservices are NVIDIA NIMs—easy-to-deploy, high-performance microservices, optimized to run on NVIDIA RTX AI PCs or NVIDIA Graphics Delivery Network (GDN), a global network of GPUs that delivers low-latency digital human processing to 100 countries.
With generative AI, you can generate highly relevant, bespoke, and accurate content, grounded in the domain expertise and proprietary IP of your enterprise.
Biomolecular generative models and the computational power of GPUs efficiently explore the chemical space, rapidly generating diverse sets of small molecules tailored to specific drug targets or properties.
Financial institutions need to detect and prevent sophisticated fraudulent activities, such as identity theft, account takeover, and money laundering. AI-enabled applications can reduce false positives in transaction fraud detection, enhance identity verification accuracy for know-your-customer (KYC) requirements, and make anti-money laundering (AML) efforts more effective, improving both the customer experience and your company’s financial health.
Organizations are looking to build smarter AI chatbots using retrieval-augmented generation (RAG). With RAG, chatbots can accurately answer domain-specific questions by retrieving information from an organization’s knowledge base and providing real-time responses in natural language. These chatbots can be used to enhance customer support, personalize AI avatars, manage enterprise knowledge, streamline employee onboarding, provide intelligent IT support, create content, and more.
Patching software security issues is becoming progressively more challenging as the number of reported security flaws in the common vulnerabilities and exposures (CVE) database hit a record high in 2022. Using generative AI, it’s possible to improve vulnerability defense while decreasing the load on security teams.
Accelerate Generative AI Performance and Lower Costs
Read how Amdocs built amAIz, a domain-specific generative AI platform for telcos, using NVIDIA DGX™ Cloud and NVIDIA NIM inference microservices to improve latency, boost accuracy, and reduce costs.
Learn how Snapchat enhanced the clothes shopping experience and emoji-aware optical character recognition using Triton Inference Server to scale, reduce costs, and accelerate time to production.
AI is fueling a new industrial revolution — one driven by AI factories. Unlike traditional data centers, AI factories do more than store and process data — they manufacture intelligence at scale, transforming raw data into real-time insights. For enterprises and countries around the world, this means dramatically faster time to value — turning AI
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Global telecommunications networks can support millions of user connections per day, generating more than 3,800 terabytes of data per minute on average. That massive, continuous flow of data generated by base stations, routers, switches and data centers — including network traffic information, performance metrics, configuration and topology — is unstructured and complex. Not surprisingly, traditional
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The industrial age was fueled by steam. The digital age brought a shift through software. Now, the AI age is marked by the development of generative AI, agentic AI and AI reasoning, which enables models to process more data to learn and reason to solve complex problems. Just as industrial factories transform raw materials into
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Deploying Generative AI in Production With NVIDIA NIM
Unlock the potential of generative AI with NVIDIA NIM. This video dives into how NVIDIA NIM microservices can transform your AI deployment into a production-ready powerhouse.
Triton Inference Server simplifies the deployment of AI models at scale in production. Open-source inference-serving software lets teams deploy trained AI models from any framework—from local storage or cloud platform—on any GPU- or CPU-based infrastructure.
Ever wondered what NVIDIA’s NIM technology is capable of? Delve into the world of mind-blowing digital humans and robots to see what NIMs make possible.
