What is Muse Glimmer? Meta’s 30 Billion Parameter AI Model Explained

Last Updated: Aug 11, 2026, 15:38 IST

Muse Glimmer is Meta’s new 30-billion-parameter AI model for local AI agents. Know its objective, features, uses, licence, and key facts.

Muse Glimmer: What Is Meta’s New AI Model? Objective, Features and Key Facts
Muse Glimmer: What Is Meta’s New AI Model? Objective, Features and Key Facts

Key Takeaways

  • Muse Glimmer is a new AI model from Meta.

  • It has 30 billion parameters.

  • It focuses on local AI agents.

  • It can understand text and images.

  • It supports 100+ languages.

  • It can help with coding and tool use.

  • It uses quantization for smaller size.

  • It uses speculative decoding for faster generation.

  • It is available as an open-weight model under the Apache 2.0 licence.

  • It was introduced on August 10, 2026.

Meta has introduced a new Artificial Intelligence (AI) model called Muse Glimmer. It was introduced on August 10, 2026, by Meta Superintelligence Labs.

Muse Glimmer is a 30-billion-parameter AI model. It is designed to run directly on computers. It can work without always depending on cloud servers or an internet connection.

Key Facts About Muse Glimmer

Feature

Details

Model

Muse Glimmer

Developed by

Meta Superintelligence Labs

Parameters

30 billion

Released

August 10, 2026

Licence

Apache 2.0

Main focus

Local AI agents

Languages

100+

Input

Text and images

Model size after quantization

Under 20 GB

Main uses

Coding, reasoning and tool use

muse glimmer-1

Source: meta

What is Muse Glimmer?

Muse Glimmer is an open-weight AI model made mainly for local AI agents.

An AI agent can perform several steps to complete a task. Muse Glimmer can help with coding, tool use, reasoning and understanding images.

Meta has released its model weights under the Apache 2.0 licence.

What is the Objective of Muse Glimmer?

The main objective is to make AI agents work efficiently on local devices.

Main objectives:

  • Run AI directly on computers

  • Reduce dependence on cloud servers

  • Support AI agents

  • Help with coding tasks

  • Use different digital tools

  • Work with text and images

  • Support offline AI use

  • Give developers an open AI model

What are the Different task can Muse Glimmer do?

Muse Glimmer has been designed for different AI tasks.

Multi-step tasks

It can plan and work through several steps to complete a task.

Tool use

It can use digital tools through function calls.

Coding

It can write, understand and debug code.

Error recovery

If a tool fails, it can identify the problem and try again.

Image understanding

It can understand screenshots, charts and documents.

Multilingual support

It has been trained using data from more than 100 languages.

Muse Glimmer vs Other AI Models

Meta compared Muse Glimmer with models such as Gemma 4 31B and Qwen3.6 27B.

Feature

Muse Glimmer

Gemma 4 31B

Qwen3.6 27B

Parameters

30 billion

31 billion

27 billion

Local use

Major focus

Supported

Supported

Coding

Yes

Yes

Yes

AI agents

Strong focus

Yes

Yes

Multimodal use

Text + images

Multimodal

Multimodal

How Does Muse Glimmer Run Locally?

A 30-billion-parameter model can need more than 55 GB of memory at full precision.

Meta uses quantization to reduce its size.

With around 4-bit precision, Muse Glimmer can be reduced to under 20 GB.

This makes it more suitable for computers with around 24 GB or 32 GB of memory.

What is Speculative Decoding?

Muse Glimmer also uses speculative decoding to improve speed.

A smaller model first suggests several tokens. The main model then checks them. 

This can make responses faster while keeping the output quality.

Why is Muse Glimmer Important?

Muse Glimmer focuses on local AI.

This can provide several benefits:

  • AI can run directly on a computer.

  • Internet may not always be needed.

  • Developers get more control.

  • Local AI agents can be built.

  • Users can experiment with an open-weight model.

Where is Muse Glimmer Available?

Meta has released the model weights through Hugging Face.

It also provides developer documentation.

The model is being integrated with tools such as:

  • llama.cpp

  • MLX

  • ExecuTorch

  • Ollama

  • LM Studio

  • Unsloth

  • vLLM

  • SGLang

Muse Glimmer is designed to bring powerful AI agents directly to personal computers. Its focus on local use, coding, tool calling and multi-step tasks makes it an important development in agentic AI.

Prabhat Mishra
Prabhat Mishra

Executive - Editorial

    Prabhat Mishra is a Subject Matter Expert and digital journalist with an extensive background in the competitive exam landscape and over 4 years of experience in education, national and international news, and current affairs. Over his tenure with top knowledge platforms like Mentorship India, IAS BABA, IAS SARTHI, and now Jagran Josh, he has a deep understanding of government exams like UPSC and State PCS, including UP and Bihar, as he has already qualified for the UPPCS 2022 Mains and Bihar 68th Mains. With his core expertise in history, polity, geography & current affairs, he specialises in creating well-researched, aspirant-centric content and simplifying complex topics for competitive examinations.

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    First Published: Aug 11, 2026, 15:38 IST

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