Databricks and NVIDIA: Building for the Agentic Era - Cloned

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Summary

Databricks and NVIDIA are expanding their collaboration to deliver an end-to-end AI platform that accelerates model training, inference, and agentic AI development on governed enterprise data.

New capabilities include Multinode training in AI Runtime, GPU support in Databricks Free Edition, Model Serving Enhancements, and support for NVIDIA technologies such as NVIDIA Agent Toolkit.

Customers can leverage NVIDIA’s industry-specific AI frameworks directly within Databricks to accelerate use cases across healthcare, life sciences, supply chain, robotics, digital twins, and document intelligence.

The Full Stack of AI, Accelerated NVIDIA accelerated computing powers some of the most demanding AI workloads on Databricks, from large-scale training, fine-tuning, and inference to industry-specific AI solutions. Today at Data + AI Summit, we're highlighting how NVIDIA AI infrastructure lies at the center of new announcements from Databricks AI Runtime, Model Serving, and Industry AI solutions, including a look at how the new NVIDIA Vera CPU will power the next generation of agentic infrastructure. "Our partnership with NVIDIA spans the full AI lifecycle - from NVIDIA accelerated infrastructure powering distributed training in AI Runtime to software running inside our serving and developer platforms. We're excited to combine NVIDIA technology with the data and governance capabilities of Databricks to unlock incredible value for our customers: enterprise AI that's fast, scalable, and built on a foundation they can trust." — Adam Conway, SVP, Product, Databricks "Our partnership with NVIDIA spans the full AI lifecycle – from NVIDIA accelerated infrastructure powering distributed training in AI Runtime to software running inside our serving and developer platforms. We're excited to combine NVIDIA technology with the data and governance capabilities of Databricks to unlock incredible value for our customers: enterprise AI that's fast, scalable, and built on a foundation they can trust." — Adam Conway, SVP, Product, Databricks "Our partnership with NVIDIA spans the full AI lifecycle _ from NVIDIA accelerated infrastructure powering distributed training in AI Runtime to software running inside our serving and developer platforms. We're excited to combine NVIDIA technology with the data and governance capabilities of Databricks to unlock incredible value for our customers: enterprise AI that's fast, scalable, and built on a foundation they can trust." — Adam Conway, SVP, Product, Databricks "Our partnership with NVIDIA spans the full AI lifecycle — from NVIDIA accelerated infrastructure powering distributed training in AI Runtime to software running inside our serving and developer platforms. We're excited to combine NVIDIA technology with the data and governance capabilities of Databricks to unlock incredible value for our customers: enterprise AI that's fast, scalable, and built on a foundation they can trust." "Our partnership with NVIDIA spans the full AI lifecycle – from NVIDIA accelerated infrastructure powering distributed training in AI Runtime to software running inside our serving and developer platforms. We're excited to combine NVIDIA technology with the data and governance capabilities of Databricks to unlock incredible value for our customers: enterprise AI that's fast, scalable, and built on a foundation they can trust."

"Our partnership with NVIDIA spans the full AI lifecycle — from NVIDIA accelerated infrastructure powering distributed training in AI Runtime to software running inside our serving and developer platforms. We're excited to combine NVIDIA technology with the data and governance capabilities of Databricks to unlock incredible value for our customers: enterprise AI that's fast, scalable, and built on a foundation they can trust."

"Our partnership with NVIDIA spans the full AI lifecycle. From NVIDIA accelerated infrastructure powering distributed training in AI Runtime to software running inside our serving and developer platforms. We're excited to combine NVIDIA technology with the data and governance capabilities of Databricks to unlock incredible value for our customers: enterprise AI that's fast, scalable, and built on a foundation they can trust." — Adam Conway, SVP, Product, Databricks “Databricks enables enterprises to build, deploy, scale and govern AI agents that are informed by their most valuable resource: business data. Through our expanded partnership, NVIDIA and Databricks are supercharging the next wave of enterprise AI by embedding full-stack NVIDIA accelerated computing with Vera CPUs, Rubin GPUs, NVIDIA Quantum InfiniBand networking and NVIDIA Agent Toolkit software into the Databricks platform.” — Pat Lee, Vice President, Enterprise Strategic Partnerships, NVIDIA Here's how Databricks and NVIDIA are building an AI platform together, from GPUs for training and inference, to purpose-built CPUs for the agentic era. 1. Training and Fine-Tuning Databricks AI Runtime (AIR) brings NVIDIA GPU acceleration directly to data and AI teams, so they can train and fine-tune models on governed enterprise data without managing separate GPU infrastructure. With AIR, customers obtain the advanced NVIDIA hardware and networking, directly where their governed data is on Databricks: NVIDIA Hopper GPUs with NVIDIA Quantum InfiniBand : purpose-built for multi-node distributed training. Whether you're pre-training a foundation model or running large-scale fine-tuning, AIR provides built-in support for NVIDIA’s high-bandwidth, low-latency GPU interconnects (RDMA-capable networking) that eliminate communication bottlenecks across nodes. AIR is also being prepared for the NVIDIA Blackwell architecture, ensuring customers are always on the leading edge of accelerated computing. NVIDIA GPUs in Free Edition: at DAIS, we’re excited to announce the support of GPUs within Databricks Free Edition, supporting developers, students, and startups worldwide to build and deploy their AI workloads on GPUs. Support for NVIDIA containers: Soon, Databricks will support NGC containers and custom NVIDIA CUDA environments, enabling them to run natively on data within the platform.

AI Runtime enables seamless access to NVIDIA GPUs within Databricks. 2. Inference: NVIDIA Acceleration in Databricks...