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Muse Spark Open
Deploy Muse Spark Open on your own machine: an open-weight multimodal engine with a 1M-token window for agentic video editing on Apple silicon.
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What Muse Spark Open Unlocks for Local Video Work
Released as open weights, this natively multimodal system handles coding, agentic tasks and long-horizon jobs on hardware you control.
- Open Weights With US OriginsThe release ships 816B total parameters, 42B active, native multimodality and a 1M-token window — a strong open-weight option for self-hosting.
- Desktop-Scale IntelligenceFrontier models no longer need a remote data center: a pair of Apple M5 Ultra Mac Studios and the latest MLX build can boot the model at your desk.
- Agentic Work, Proven LocallyMuse Code used the model to ship real iOS fixes to Ice Cubes, then controlled DaVinci Resolve end to end and cropped key frames for vertical delivery.
Three Ways to Deploy Muse Spark Open
Choose local Apple silicon, your preferred inference engine, or a hosted API to start working with the model.
What Muse Spark Open Can Do
Open weights, native multimodality, desktop-class memory bandwidth and a million-token window combine to support agentic video workflows.
1M-Token Context
A million-token window keeps long agentic sessions and multi-step reasoning chains connected to earlier context.
Long-Horizon Agentic Coding
Built for software engineering and agentic loops, it manages extended jobs and end-to-end control of tools like DaVinci Resolve.
Native Multimodal Input
The model reads mixed inputs directly instead of relying on bolt-on adapters, enabling frame-by-frame footage review.
Two Mac Studios as One Supercomputer
Unified memory lets each M5 Ultra GPU address up to 512 GB, so two Mac Studios can hold the full model with a terabyte of pooled memory.
1.2 TB/s Memory Bandwidth
The M5 Ultra moves 1.2 TB/s, enough to feed the small per-token slice and keep local inference responsive.
Safety Post-Training
Open weights receive additional safety post-training; the release was scored against the Meta Superintelligence Scaling Framework and met its thresholds across measured risk categories.
Muse Spark Open: Common Questions
Answers about local requirements, licensing, downloads and hosted access for Muse Spark Open.
What hardware is needed for local Muse Spark Open inference?
You need two Apple M5 Ultra Mac Studios running the latest MLX build; each offers up to 512 GB of unified memory, giving roughly a terabyte for the full model.
How many parameters and how much context does the model support?
It has 816B total parameters with 42B active, a 1M-token context window and native multimodality for coding, agentic work and long-horizon tasks.
Where can I get the weights or call the model through an API?
Download weights from Amazon SageMaker AI, Google Cloud Model Garden, Hugging Face and Microsoft Foundry Models; hosted APIs are available at Baseten, Fireworks AI, Groq, Modal, Nebius, OpenRouter and Together AI.
Which inference engines and chips can I use?
Choose MLX, llama.cpp, Unsloth, SGLang, vLLM, TensorRT-LLM or Transformers; the stack is tuned for NVIDIA, AMD, Intel and Apple hardware, with PyTorch available for deeper customization.
What license covers the released weights?
The Muse Model License applies; its limited commercial terms still allow a wide range of developers to run Muse Spark Open without cost.
How was safety evaluated before release?
The model was scored against the Meta Superintelligence Scaling Framework for severe risks, received extra safety post-training for open weights, and passed release thresholds; the model card has details.
Download Muse Spark Open Weights Today
Get Muse Spark Open from Hugging Face, access it through hosted inference partners, and share your builds in the Hugging Face Forums.