IBM-Backed Llm-D Framework Adds Controls for Running AI Models in-House

IBM-Backed llm-d 1.0 Adds Controls for AI Inference Workloads

The release also supports coordinated upgrades and context-aware routing. A pre-release benchmark reached 6.60 million output tokens per minute with 3,000 coding agents.

llm-d 1.0 Advances Open, Cost-Efficient AI Inference for Production Scale

SAN JOSE, Calif., Oct. 20, 2026 /PRNewswire/ -- Today, llm-d project contributors announced the release of llm-d 1.0, a major milestone for the open source project designed to help organizations deploy and scale large language model inference more efficiently across modern infrastructure. Founded in 2025 by Red Hat, IBM (NYSE: IBM), Google Cloud, CoreWeave and NVIDIA, and now governed by the Cloud Native Computing Foundation (CNCF), llm-d...

IBM-backed llm-d framework adds controls for running AI models in-house

IBM Corp. and several other contributors to the open-source llm-d project are releasing version 1.0 of their distributed artificial intelligence inference framework, adding operational controls intended to help enterprises run large models reliably on their own infrastructure. The release, announced ahead of the PyTorch Conference North America in San Jose today and tomorrow, focuses on […] The post IBM-backed llm-d framework adds controls for r…

llm-d 1.0: Red Hat, IBM, Google and Nvidia bet that AI’s real bill is inference, not training

For three years the AI conversation has been about who can build the biggest model. The less glamorous question — what it costs to keep that model answering, millions of times a day, without falling over — is where the money now leaks. llm-d, the open-source inference project started by Red Hat, IBM, Google Cloud, CoreWeave and Nvidia, has shipped its first stable release, and its pitch is aimed squarely at that leak.