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About

Muse Spark Open is an open-weight, natively multimodal language model for developers and organizations building AI applications, coding systems, and agentic workflows. The released model has 816 billion total parameters, 42 billion active parameters, and a 1-million-token context window. Teams can download the model weights, run inference through supported engines such as vLLM, SGLang, TensorRT-LLM, Hugging Face Transformers, Apple MLX, llama.cpp, or Unsloth, and customize the model using PyTorch. It supports long-context reasoning, software engineering, coding, tool use, and multimodal inputs. Deployment options include cloud inference through listed API providers or self-hosting on compatible GPU systems; Meta documents a desktop setup using two Apple M5 Ultra Mac Studio computers. The model is released under the Muse Model License with limited commercial terms.

About

Muse Wonder is a frontier artificial intelligence model developed by Meta for personal assistance, professional workflows, software development, and autonomous agent tasks. The model combines Active Memory, which retrieves relevant information from previous conversations, with Active Focus, which supports sustained execution of complex, multistep assignments. Muse Wonder can assist with research, document analysis, financial and legal information, software engineering, and business process automation. Its agentic capabilities enable it to work across applications, use contextual information, adapt to obstacles, and request clarification or approval when necessary. The model supports coding activities ranging from small application development to complex software projects involving repeated testing and revision. Muse Wonder is available through the Meta Model API and Muse Code, with additional integration into Meta's Muse assistant planned for future releases.

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

AI developers, machine learning engineers, software engineers, AI researchers, enterprise development teams, and organizations seeking customizable open-weight multimodal models for local inference, autonomous agents, complex coding, and long-context AI applications

Audience

Software developers, AI engineers, researchers, business professionals, knowledge workers, enterprise teams, and individuals seeking advanced AI assistance for complex reasoning, software development, personalized workflows, and autonomous task execution

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Not Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Not Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

$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 Supported
Free Trial Not Supported

Pricing

$4 per 1M tokens (input)
Input: $4 per 1M tokens
Output: $20 per 1M tokens
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5

Pros & Cons from Real Users

Pros

  • Meta finally opened up a genuinely frontier-level Muse model. The 1M-token context window and 42B active parameters make it strong enough for large repos, long agent sessions, multimodal work, and complex coding without feeling like a stripped-down open model. The local deployment story is also a huge deal. Being able to run something this capable on two M5 Ultra Mac Studios is impressive, especially for teams that want more control over data, infrastructure, and customization. I also like how much of the stack is open around it. Muse Spark Open works with MLX, vLLM, SGLang, TensorRT-LLM, Transformers, llama.cpp, and Unsloth, and Meta is making the weights available through Hugging Face, SageMaker, Google Cloud Model Garden, and Microsoft Foundry.

Cons

  • Even though it is technically desktop-capable, needing two M5 Ultra Mac Studios for the full local experience is still a serious setup, so most developers will probably use hosted inference instead.

Pros & Cons from Real Users

Pros

  • It feels much better at keeping track of what I am trying to accomplish across longer coding, research, and agent workflows instead of slowly losing the thread. Active Memory is especially useful. The model does a better job carrying important context forward, which makes extended projects feel less like repeatedly briefing a new assistant. I also like the new Active Focus approach. Wonder feels more deliberate about working toward the actual goal instead of getting distracted by side issues, which matters a lot when I give an agent something that takes many steps to finish. The coding ability is strong too. Meta is positioning Wonder against models like GPT-6 Astra and Claude Opus 5.5, and early reporting says it is especially competitive in software development and professional agentic work.

Cons

  • No real cons so far. I am still not sure how efficient pricing is.

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Meta
Founded: 2004
United States
research.meta.ai/blog/muse-spark-open

Company Information

Meta
Founded: 2004
United States
meta.ai/

Alternatives

Alternatives

Laguna XS 2.1

Laguna XS 2.1

Poolside

Categories

AI Coding Models Supported
AI Models Supported
AI Receptionists Supported
Foundation Models Supported
Multimodal Models Supported

Categories

AI Coding Models Supported
AI Models Supported
Foundation Models Supported
Multimodal Models Supported

Integrations

C Not Supported
Claude Code Not Supported
Continue Not Supported
Facebook Not Supported
Fireworks AI Supported
Go Not Supported
Hugging Face Supported
Kubernetes Not Supported
Lua Not Supported
Modal Supported
Muse Not Supported
Muse Image Not Supported
Muse Spark Not Supported
Nebius Supported
Python Not Supported
SQL Not Supported
Swift Not Supported
Vercel AI SDK Not Supported
XML Not Supported
vLLM Supported

Integrations

C Supported
Claude Code Supported
Continue Supported
Facebook Supported
Fireworks AI Not Supported
Go Supported
Hugging Face Not Supported
Kubernetes Supported
Lua Supported
Modal Not Supported
Muse Supported
Muse Image Supported
Muse Spark Supported
Nebius Not Supported
Python Supported
SQL Supported
Swift Supported
Vercel AI SDK Supported
XML Supported
vLLM Not Supported
Claim Muse Spark Open and update features and information
Claim Muse Spark Open and update features and information
Claim Muse Wonder and update features and information
Claim Muse Wonder and update features and information