MuMicrosoft
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Related Products
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About
Mu is a 330-million-parameter encoder–decoder language model designed to power the agent in Windows settings by mapping natural-language queries to Settings function calls, running fully on-device via NPUs at over 100 tokens per second while maintaining high accuracy. Drawing on Phi Silica optimizations, Mu’s encoder–decoder architecture reuses a fixed-length latent representation to cut computation and memory overhead, yielding 47 percent lower first-token latency and 4.7× higher decoding speed on Qualcomm Hexagon NPUs compared to similar decoder-only models. Hardware-aware tuning, including a 2/3–1/3 encoder–decoder parameter split, weight sharing between input and output embeddings, Dual LayerNorm, rotary positional embeddings, and grouped-query attention, enables fast inference at over 200 tokens per second on devices like Surface Laptop 7 and sub-500 ms response times for settings queries.
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About
vLLM is a high-performance library designed to facilitate efficient inference and serving of Large Language Models (LLMs). Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evolved into a community-driven project with contributions from both academia and industry. It offers state-of-the-art serving throughput by efficiently managing attention key and value memory through its PagedAttention mechanism. It supports continuous batching of incoming requests and utilizes optimized CUDA kernels, including integration with FlashAttention and FlashInfer, to enhance model execution speed. Additionally, vLLM provides quantization support for GPTQ, AWQ, INT4, INT8, and FP8, as well as speculative decoding capabilities. Users benefit from seamless integration with popular Hugging Face models, support for various decoding algorithms such as parallel sampling and beam search, and compatibility with NVIDIA GPUs, AMD CPUs and GPUs, Intel CPUs, and more.
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Platforms Supported
Windows
Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Not Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
Developers seeking a solution to navigate and configure system settings through natural language
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Audience
AI infrastructure engineers looking for a solution to optimize the deployment and serving of large-scale language models in production environments
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Support
Phone Support
Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Supported
Online
Supported
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API
Offers API
Not Supported
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API
Offers API
Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Supported
Live Online
Supported
In Person
Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationMicrosoft
Founded: 1975
United States
blogs.windows.com/windowsexperience/2025/06/23/introducing-mu-language-model-and-how-it-enabled-the-agent-in-windows-settings/
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Company InformationvLLM
United States
vllm.ai
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Categories |
Categories |
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Integrations
Database Mart
Not Supported
Docker
Not Supported
DocsGPT
Not Supported
Hugging Face
Not Supported
KServe
Not Supported
Kubernetes
Not Supported
NGINX
Not Supported
NVIDIA DRIVE
Not Supported
OpenAI
Not Supported
PyTorch
Not Supported
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Integrations
Database Mart
Supported
Docker
Supported
DocsGPT
Supported
Hugging Face
Supported
KServe
Supported
Kubernetes
Supported
NGINX
Supported
NVIDIA DRIVE
Supported
OpenAI
Supported
PyTorch
Supported
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