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
About Muse Spark Open
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.
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Muse Spark Open Frequently Asked Questions
Q: What kinds of users and organization types does Muse Spark Open work with?
Q: What languages does Muse Spark Open support in their product?
Q: What other applications or services does Muse Spark Open integrate with?
Q: What type of training does Muse Spark Open provide?
Q: How much does Muse Spark Open cost?
Muse Spark Open Product Features
Muse Spark Open Verified User Reviews
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Probability You Would Recommend? 9 out of 10
"Meta AI delivers again!" 5 out of 5 stars Posted 2026-10-15
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.
Overall: Muse Spark Open is of the STRONGEST open-weight options for developers building coding agents, multimodal systems, and long-running AI workflows. The combination of frontier-level capability, huge context, broad inference support, and local deployment makes it much more interesting than a typical open-model release.
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