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ease
features
design
support

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Description

On June 23, 2025, Microsoft unveiled Mu, an innovative 330-million-parameter encoder–decoder language model specifically crafted to enhance the agent experience within Windows environments by effectively translating natural language inquiries into function calls for Settings, all processed on-device via NPUs at a remarkable speed of over 100 tokens per second while ensuring impressive accuracy. By leveraging Phi Silica optimizations, Mu’s encoder–decoder design employs a fixed-length latent representation that significantly reduces both computational demands and memory usage, achieving a 47 percent reduction in first-token latency and a decoding speed that is 4.7 times greater on Qualcomm Hexagon NPUs when compared to other decoder-only models. Additionally, the model benefits from hardware-aware tuning techniques, which include a thoughtful 2/3–1/3 split of encoder and decoder parameters, shared weights for input and output embeddings, Dual LayerNorm, rotary positional embeddings, and grouped-query attention, allowing for swift inference rates exceeding 200 tokens per second on devices such as the Surface Laptop 7, along with sub-500 ms response times for settings-related queries. This combination of features positions Mu as a groundbreaking advancement in on-device language processing capabilities.

Description

SmolLM2 comprises an advanced suite of compact language models specifically created for on-device functionalities. This collection features models with varying sizes, including those with 1.7 billion parameters, as well as more streamlined versions at 360 million and 135 million parameters, ensuring efficient performance on even the most limited hardware. They excel in generating text and are fine-tuned for applications requiring real-time responsiveness and minimal latency, delivering high-quality outcomes across a multitude of scenarios such as content generation, coding support, and natural language understanding. The versatility of SmolLM2 positions it as an ideal option for developers aiming to incorporate robust AI capabilities into mobile devices, edge computing solutions, and other settings where resources are constrained. Its design reflects a commitment to balancing performance and accessibility, making cutting-edge AI technology more widely available.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Hugging Face No 
Locally AI No 
Mirai No 
Private Mind No 
Runpod No 

Integrations

Hugging Face Yes 
Locally AI Yes 
Mirai Yes 
Private Mind Yes 
Runpod Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based No 
On-Premises Yes 
iPhone App Yes 
iPad App Yes 
Android App Yes 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Microsoft

Founded

1975

Country

United States

Website

blogs.windows.com/windowsexperience/2025/06/23/introducing-mu-language-model-and-how-it-enabled-the-agent-in-windows-settings/

Vendor Details

Company Name

Hugging Face

Founded

2016

Country

United States

Website

huggingface.co/collections/HuggingFaceTB/smollm2-6723884218bcda64b34d7db9

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