by Maryam Tahhan, John Harrigan, Anton Ivanov, Evgenii Dushkin, Ryan Malone | Oct 6, 2026 | AI
What if your standard-issue CPU infrastructure could serve as a hub for enterprise AI? With the right tools, it can. You can deploy a large language model on CPU inside a container on Red Hat Enterprise Linux (RHEL), query it via an OpenAI compatible REST API, and...
by Evgenii Dushkin, Ryan Malone, Maryam Tahhan | Sep 28, 2026 | AI
Deploying large language models (LLMs) on enterprise hardware requires a balance of reproducibility, security, and performance. Accurately benchmarking model performance under production-like workloads is both challenging and crucial for optimizing infrastructure...
by Maryam Tahhan, John Harrigan, Anton Ivanov, Paul Power, Luigi Mario Zuccarelli | May 28, 2026 | AI
As enterprises look to optimize the total cost of ownership (TCO) of Large Language Model deployment, utilizing existing enterprise CPU infrastructure alongside GPU resources for specific inference workloads has become a strategic initiative. However, infrastructure...
