Argonne Launches First Large-Scale AI Inference Service for Open Science

LEMONT, Ill.--(BUSINESS WIRE)--The U.S. Department of Energy’s (DOE) Argonne National Laboratory has launched a first-of-its-kind AI inference service to help researchers across the nation accelerate discovery and innovation.

The service offers cloud-like access to a range of large language models (LLMs) running on Argonne’s high-performance computing (HPC) systems. This gives researchers a powerful and secure resource for analyzing large datasets and testing new ideas.

“Our inference service helps close the gap between developing AI models and putting them to work in scientific research,” said Michael Papka, director of the Argonne Leadership Computing Facility (ALCF). “By offering AI inference as a shared resource, we enable researchers to apply AI at scale to their data, simulations, and experiments, without the burden of building and maintaining their own infrastructure.”

Inference is the process of using trained AI models to analyze data, identify patterns and make predictions. AI chatbots like ChatGPT use inference to answer questions in real time. In research, the same capability can help scientists guide experiments, make sense of complex data and perform other analytical tasks more efficiently.

The ALCF Inference Service provides access to a range of LLMs, including Google’s Gemma series, Meta’s LLaMA models, and OpenAI’s GPT-OSS family, as well as domain-specific foundation models, computer vision models, and in-house models developed at Argonne, such as AuroraGPT.

The service is being used by a growing and diverse set of researchers. In addition to a substantial base of Argonne and ALCF users, it is actively supporting users across the DOE national laboratory ecosystem, enabling seamless access for researchers from several labs using their home institution credentials.

Among its users, the ALCF Inference Service is supporting teams working on DOE’s Genesis Mission. The mission is a national initiative to build the world's most powerful scientific platform to accelerate discovery science, strengthen national security and drive energy innovation.

The service is also being used to advance work in physics, chemistry and materials science. A recent example is ChemGraph, an AI framework that helps researchers simplify and automate molecular simulation workflows and other chemistry tasks. By using the ALCF Inference Service for LLM-driven tasks, ChemGraph lets researchers manage complex, multi-step simulation workflows interactively.

“This allows scientists to explore more candidate molecules, iterate on designs faster and manage large-scale calculations as an integrated process rather than a series of disconnected jobs,” said Murat Keçeli, an Argonne computational scientist who helped develop ChemGraph.

To support these scientific workflows, the service runs on dedicated ALCF systems, including Sophia and Metis. For additional details, see the ALCF user guide or watch the webinar, “Deploying Inference Services at ALCF.”