Introducing llm-d on stage at Red Hat Summit was truly a privilege ...

Muse-Glimmer 30B, now in FP8-block. Our quantized checkpoint of the multimodal model, at roughly half the memory and disk. Block-wise FP8 on the linear layers, vision tower kept in full precision. Quantized with LLM Compressor, serve on @vllm_project. Evals coming shortly. huggingface.co/RedHatAI/Muse…

Kimi K3 open weights landed yesterday. By that afternoon, Red Hat AI Inference was serving it on one 8x B300 node. 2.8T params. Day-0 preview images exist so you can experiment the moment weights drop. 👇

🇬🇧 London, June 10. @vllm_project & @_llm_d_ Inference Meetup, hosted by Red Hat AI, @nvidia, and @SteliaAI. Talks on vLLM updates, speculative decoding, llm-d in production, AI safety, and more. Plus food, drinks, and the people building this stuff. luma.com/iuecyow4

Llama 70B as a cloud endpoint costs exponentially more than Llama 8B. For teams where a smaller model meets the quality bar, that gap is hard to ignore. And with INT4 quantization: 4x smaller, 2x faster, less than 1% accuracy loss. The right model isn't always the biggest one. redhat.com/en/blog/when-less…

Calling Boston area startups building with AI. 🤙 We're kicking off 2026 with the first event in a new monthly, in person hackathon series hosted by @RedHat and @IBM in Boston’s Seaport District. This one day hackathon is designed specifically for local startups that want to move faster from idea to working prototype. Instead of a fixed theme, you bring a real AI problem your team is actively facing. We help you build a proof of concept using open source, enterprise ready templates from aitemplates.io, including MCP Server, AI Agent, and UI templates. What you will get: ⚡ Rapid prototyping without boilerplate 🧠 Hands on guidance from Red Hat AI architects 🤝 Connections with other Boston based AI startups and ecosystem partners If you are a Boston startup looking to turn an AI challenge into something real, this is for you. Event details are shared after registration. Register now: luma.com/i3q8df0x

The @RedHat_AI team contributes a lot to vLLM and does amazing work for the open-source community. Great to see vLLM performing so well compared to TRT-LLM on H200! vLLM comes pretty close to B200, with the @NVIDIAAI team working on closing the gap for GPTOSS within the next couple of updates.

InferenceMAX, vLLM TPU, compressed-tensors, MoE support via transformers, DeepSeek-OCR, and more. Here’s what’s new in the @vllm_project community over the past two weeks:

4 tracks. 12 sessions. 1 day of learning. Join us on Oct. 16 for Red Hat AI Day of Learning, a free virtual event for developers, engineers & practitioners. Tracks: ⚡ Fast & efficient inference 🎯 Model customization 🤖 Agentic AI 🌐 Scaling AI over hybrid cloud Sessions include: · Intro to vLLM and how to get started · Model optimization with LLM Compressor · Lossless LLM inference acceleration w/ Speculators · End-to-end model customization · Synthetic data generation and data processing · Continual learning of LLMs with Training Hub · Build open source agentic AI solutions · Intro to Model Context Protocol (MCP) · Intro to Llama Stack · Intro to distributed inference · Distributed inference with llm-d · Scaling AI Infrastructure 👉 Register free: redhat.com/en/events/webinar…

Qwen3-Next dropped yesterday and you can run it with Red Hat AI today. ✅ Day-zero support in vLLM ✅ Day-one deployment with Red Hat AI Step-by-step guide: developers.redhat.com/articl… The future of AI is open.

Thanks to the @lmcache team for joining forces with Red Hat on llm-d! llm-d is a new open source project for scalable, efficient distributed LLM inference with @vllm_project. Learn more about our collaboration here: blog.lmcache.ai/2025-05-22-r…

Really excited to see the emergence of llm-d @addvin ! Inference is the biggest workload in human history and the open source tools need to keep evolving to serve it

The llm-d project is a major step forward for the #opensource AI ecosystem, and we are proud to be one of the founding contributors, reflecting our commitment to collaboration as a catalyst for innovation in generative AI. As generative and agentic AI continue to evolve, scalable, high-performance inference will be critical to unlocking their full potential. That’s why we’re partnering with @RedHat and other contributors to grow the llm-d community and accelerate its capabilities—powered by our contributions, including innovations from NVIDIA Dynamo such as NIXL. 🔗 Explore and contribute on GitHub: nvda.ws/3FlttSL 📰 Read the launch blog: nvda.ws/3FgF0Tn 🎙️ Hear from NVIDIA’s VP of Engineering & AI Frameworks, Ujval Kapasi → nvda.ws/45pyVhU

And was great to see the Red Hat and Google effort announced by my friend the brilliant Amin Vahdat.

DeepSeek’s Open Source Week drops A LOT of exciting goodies! We’re hosting vLLM Office Hours tomorrow—learn what they are, how they integrate with vLLM, & ask questions! Date: Thursday, Thu, Feb 27 Time: 2PM ET / 11AM PT Register: neuralmagic.com/community-of… #DeepSeek #AI

At @RedHat, we believe the future of AI is open. That's why I'm incredibly excited about our acquisition of @NeuralMagic. Together, we're furthering our commitment to our customers and the open source community to deliver on the future of AI—and that starts today.

Today it become official, Neural Magic now a part of Red Hat.

If you are at #NeurIPS2024 this week, stop by the Neural Magic booth #307 and talk to us about the @vllm_project! vLLM core committer @mgoin_ will be there, ready to hear your ideas and share them with the team. The best feature requests always come from in-person chats!

For our last seminar of the year we will end with Lucas Wilkinson from @neuralmagic presenting! Machete: a cutting-edge mixed-input GEMM GPU kernel targeting NVIDIA Hopper GPUs Time: Dec 4, 3pm EST Sign up via scale-ml.org to join our mailing list for the zoom link

I’m thrilled to announce that Neural Magic has signed a definitive agreement to join forces with Red Hat, Inc. At Neural Magic our vision is that the future of AI is open, and we have been on a mission to enable enterprises to capture the powerful innovation from AI, while at the same time being free of friction and restriction. Open-source models, optimization algorithms, and inferencing systems are the heart of this - enabling enterprises to own their own AI models, privately customize them to their datasets, and deploy them on their private multi-vendor infrastructure - whether cloud, datacenter, or edge. For the last 5 years, we have been contributing open research, open-source model quantization and sparsification tools, and open-source pre-optimized models to the community. As part of our increasing shift to support GPUs, we have been recognized as the top commercial contributor to the amazing vLLM project. There is a saying in the startup world that an acquisition is an exit. This is not. It is an entrance. A beginning to create an open source world for AI, where an open ecosystem flourishes, and customers and the community are the benefactors. Red Hat shares this vision, and together we will advance the world of truly “open” AI. It’s a great day for open source AI. Read the Press Release: redhat.com/en/about/press-re…