Day-0 Muse Glimmer Support on Intel Platforms with vLLM and Hugging Face

Muse Glimmer, Meta’s 30-billion-parameter model distilled from Muse Spark for always-on agent workflows, is presented as a fast, private, and efficient option for responsive AI assistants, with support for text, image, video, reasoning, and tool-calling use cases. Intel reports day-zero compatibility through upstream vLLM and Hugging Face Transformers across Intel Arc Pro GPUs and Intel Xeon CPUs, enabled through collaboration with Meta and open-source contributions, although vLLM users may need a specified pull request or branch until support is merged into the main repository. The instructions cover building and running vLLM Docker environments, starting an OpenAI-compatible inference server with configurable tensor parallelism, reasoning parsing, and optional automatic tool selection, then sending text-chat or image-question requests. For Hugging Face deployments, the article details required GPU drivers and PyTorch packages, offers scripts for distributed GPU inference and CPU inference, and demonstrates prompts for text and image tasks. The CPU workflow also supports optional DFlash speculative decoding using an assistant model to potentially improve generation performance.

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