Muse Spark Open
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What is Muse Spark Open?
Muse Spark Open is a large-scale open-weight artificial intelligence model developed by Meta for multimodal understanding, software engineering, autonomous agents, and long-horizon reasoning. Released in October 2026, the model provides downloadable weights that allow developers to deploy and customize it outside Meta's hosted AI services. It uses a mixture-of-experts architecture containing 816 billion total parameters, with approximately 42 billion parameters activated during inference. Its one-million-token context window supports processing extensive documents, large software repositories, and lengthy sequences of instructions and interactions. The model is designed for complex coding workflows involving source code analysis, debugging, feature implementation, application development, and software testing. Its multimodal capabilities enable AI agents to interpret visual information and combine that understanding with reasoning and automated computer interactions. Meta demonstrated the model performing local software development tasks and controlling DaVinci Resolve to analyze video footage and prepare edited content. Muse Spark Open supports on-device deployment using two Apple M5 Ultra Mac Studio computers running the MLX framework, with additional compatibility across AMD, Intel, and NVIDIA hardware. Supported inference frameworks include SGLang, vLLM, TensorRT-LLM, Hugging Face Transformers, llama.cpp, and Unsloth, with optimized GPU kernels for improved processing performance. Developers can customize the model using PyTorch and TorchTitan to adapt its behavior to specialized tasks, organizational requirements, and application workflows. Muse Spark Open is distributed under the Muse Model License with limited commercial terms and is available through Hugging Face, Amazon SageMaker AI, Google Cloud Model Garden, Microsoft Foundry Models, and several hosted API providers.
What is ExecuTorch?
ExecuTorch is an innovative open-source framework created for PyTorch, tailored to enable the deployment of artificial intelligence and machine learning models directly on edge devices, which supports various functions including text, vision, speech, recommendation, and multimodal inference without relying on cloud services. This framework simplifies the process of exporting models from PyTorch by eliminating the need for any intermediate conversion formats, thereby preserving ATen operators and utilizing ahead-of-time compilation to optimize performance for specific hardware before deployment. With a modular architecture, developers enjoy the flexibility to choose both compile-time and runtime optimizations, all while working within the familiar PyTorch ecosystem, which incorporates torchao specifically for quantization purposes. The lightweight C++ runtime of ExecuTorch, which is approximately 50 KB in size, ensures its adaptability across an array of platforms, such as smartphones, desktops, embedded systems, microcontrollers, DSPs, and Cortex-M processors. Additionally, it supports a range of operating systems, including Android, iOS, Linux, Windows, macOS, and WebAssembly, and provides native APIs in languages like C++, Swift, Kotlin, and Objective-C. Consequently, ExecuTorch empowers developers with a robust tool for efficiently deploying AI models across a wide variety of devices and applications, making it a crucial asset in the field of edge computing. Its flexible architecture and multi-platform compatibility highlight its potential to support the growing demand for localized AI solutions.
Integrations Supported
Baseten
Fireworks AI
Groq
Hugging Face
Modal
Integrations Supported
C++
Facebook
Instagram
LLaVA
Llama 3.2
API Availability
API Availability
Has API
Pricing Information
$0
Model weights are available at no charge under the Muse Model License, which has limited commercial-use terms. Hosted inference providers set their own usage prices.
Free Version
Pricing Information
Free
Free Version
Supported Platforms
SaaS
Windows
Mac
On-Prem
Linux
Supported Platforms
Android
iPhone
iPad
Windows
Mac
On-Prem
Linux
Customer Service / Support
Not specified
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
research.meta.ai/blog/muse-spark-open
Company Facts
Organization Name
ExecuTorch
Company Location
United States
Company Website
executorch.ai/
Categories and Features
AI Coding Models
Not specified
AI Models
Not specified
AI Reasoning Models
Not specified
Foundation Models
Not specified
Large Language Models
Not specified
Multimodal Models
Not specified
Open-Weight AI Models
Not specified
Categories and Features
AI Inference
Not specified