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Average Ratings 0 Ratings
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
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