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What is Muse Glimmer?

Muse Glimmer is a cutting-edge model boasting 30 billion parameters, crafted by Meta Superintelligence Labs, specifically optimized for seamless local agent functionality. Its streamlined architecture enables operation on standard Mac or PC systems with a single consumer GPU, making it suitable for a range of applications, including local agent management, programming tasks, function invocation, and evaluations within LLM-as-a-judge scenarios, all without needing cloud services or an internet connection. This groundbreaking model features sophisticated abilities like long-horizon execution, precise tool invocation, multimodal understanding, expanded memory for contextual awareness, and proficient instruction adherence. It excels in performing comprehensive tasks as an agent, adeptly navigates complex multi-step reasoning across extensive workflows, and can recover effectively from unexpected tool interactions. Additionally, it interprets interleaved text and images through a specialized perception encoder tailored for analyzing screenshots, graphs, and various document types. Beyond its primary functions, Muse Glimmer is designed to work harmoniously with OpenClaw and other orchestration frameworks, allowing for customizable reasoning capabilities and has been trained on a rich dataset that spans over 100 languages. The adaptability of this model not only enhances its effectiveness across different fields but also positions it as a significant asset in the evolving landscape of AI applications. Its innovative features and user-friendly deployment make it a versatile choice for professionals seeking to leverage AI for complex problem-solving.

What is Gemma 2?

The Gemma family is composed of advanced and lightweight models that are built upon the same groundbreaking research and technology as the Gemini line. These state-of-the-art models come with powerful security features that foster responsible and trustworthy AI usage, a result of meticulously selected data sets and comprehensive refinements. Remarkably, the Gemma models perform exceptionally well in their varied sizes—2B, 7B, 9B, and 27B—frequently surpassing the capabilities of some larger open models. With the launch of Keras 3.0, users benefit from seamless integration with JAX, TensorFlow, and PyTorch, allowing for adaptable framework choices tailored to specific tasks. Optimized for peak performance and exceptional efficiency, Gemma 2 in particular is designed for swift inference on a wide range of hardware platforms. Moreover, the Gemma family encompasses a variety of models tailored to meet different use cases, ensuring effective adaptation to user needs. These lightweight language models are equipped with a decoder and have undergone training on a broad spectrum of textual data, programming code, and mathematical concepts, which significantly boosts their versatility and utility across numerous applications. This diverse approach not only enhances their performance but also positions them as a valuable resource for developers and researchers alike.

Media

Media

Integrations Supported

Hugging Face
Ollama
Meta AI
OpenClaw

Integrations Supported

Hugging Face
Ollama
C++
F#
Gemini Enterprise Agent Platform
Gemma
Google Cloud Platform
Google Colab
Java
JavaScript
Julia
LangChain
LlamaCoder
MongoDB
Nebius Token Factory
Pipeshift
Python
SQL

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

Windows
Mac
On-Prem
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Meta

Date Founded

2004

Company Location

United States

Company Website

meta.ai/

Company Facts

Organization Name

Google

Company Location

United States

Company Website

ai.google.dev/gemma

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

Open-Weight AI Models

Not specified

Small Language Models

Not specified

Categories and Features

AI Models

Not specified

Large Language Models

Not specified

Open-Weight AI Models

Not specified

Small Language Models

Not specified

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