IBM is expanding its collaboration with NVIDIA to help enterprises operationalize AI at scale.
Advancing efforts across GPU-native data analytics, intelligent document processing, on-premises and regulated infrastructure deployments, cloud, and consulting, the collaboration aims to give enterprises the data foundation, infrastructure, and expertise to move AI from pilot to production, according to the companies.
"In the next wave of enterprise AI, the model layer will rely on the data, infrastructure, and orchestration layers—and on businesses that can bring all three together,” said Arvind Krishna, chairman and CEO, IBM. “Our partnership with NVIDIA goes to the heart of that challenge. Together, we're giving enterprises the solutions they need to stop experimenting with AI and start running on it."
IBM and NVIDIA are collaborating on an open-source integration to increase performance and reduce costs around how enterprises extract intelligence from their massive datasets. IBM watsonx.data’s SQL engine Presto is accelerated by NVIDIA cuDF to enable faster query execution on large datasets.
IBM and NVIDIA are providing Docling from IBM and NVIDIA Nemotron open models—a combination designed to make intelligent document extraction available at enterprise scale. Docling standardizes and converts documents into AI-ready formats with source-level traceability, while NVIDIA Nemotron models accelerate ingestion of multi-modal content. Early results show significantly higher throughput compared to other open-source models, while maintaining or improving accuracy wherever GPU-accelerated infrastructure is available.
IBM and NVIDIA are extending their data efforts to the infrastructure layer. NVIDIA has selected IBM Storage Scale System 6000 to provide 10PB of high-performance storage to serve massive data for its GPU-native advanced analytics engines, pairing IBM’s unified data access layer and massive parallel throughput with NVIDIA’s GPU pipelines.
For enterprises and governments requiring data residency and regulatory control, IBM and NVIDIA are exploring the integration of IBM Sovereign Core and NVIDIA infrastructure and NVIDIA Nemotron models that would focus on enabling GPU-intensive AI workloads that run entirely within regional boundaries—without compromising governance or compliance.
IBM and NVIDIA are also deepening their partnership across cloud and enterprise consulting to advance clients’ enterprise AI adoption.
IBM plans to offer NVIDIA Blackwell Ultra GPUs on IBM Cloud in early Q2 2026 for large-scale training, high-throughput inferencing, and AI reasoning. This technology will also be integrated across Red Hat AI Factory with NVIDIA, and VPC servers with enterprise-grade compliance and data residency controls.
Additionally, IBM Consulting plans to bring Red Hat AI Factory with NVIDIA to clients through IBM Consulting Advantage—an IBM enterprise AI platform that helps clients build and scale AI across their technology environments.
Combined with Red Hat AI Factory with NVIDIA, the platform is built to simplify how companies prepare data, build models, and deploy AI, while also enhancing performance and oversight. This builds on IBM Consulting’s broader efforts to help clients maximize outputs from their AI investments.
“IBM pioneered enterprise computing and data processing six decades ago—and today they are redefining it for the AI era,” said Jensen Huang, founder and CEO of NVIDIA. “Data is the ground truth that gives AI context and meaning. Together with IBM, we are bringing CUDA GPU acceleration directly into the data layer—turning analytics and document processing from bottlenecks into real-time intelligence engines.”
For more information about this news, visit www.ibm.com.