Lucebox vs. Muse Spark Open Comparison


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About Lucebox is a plug-and-play computer built for running local AI models and agents at full speed. Inside the custom chassis, a Ryzen AI MAX+ 395 with 128GB of unified LPDDR5X memory is paired with an RTX 3090, and the two work together through an open-source inference engine hand-tuned for exactly this hardware. The architecture is what makes it fast. Large models live in the 128GB unified memory tier, while the 3090's high-bandwidth VRAM acts as a fast tier. Speculative decoding (DFlash) and speculative prefill (PFlash) bridge the two, producing inference speeds up to 10x higher than llama.cpp on the same silicon and beating machines like the Mac Studio and DGX Spark at a fraction of their effective cost.	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.
Platforms Supported Windows Not Supported Mac Not Supported Linux Supported Cloud Not Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported	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
Audience Developers	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
Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported	Support Phone Support Not Supported 24/7 Live Support Not Supported Online Not Supported
API Offers API Not Supported	API Offers API Not Supported
Screenshots and Videos No images available	Screenshots and Videos View more images or videos
Pricing $4,900 - One time payment Free Version Not Supported Free Trial Not Supported	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
Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 5.0 / 5 ease 5.0 / 5 Read all reviews
	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.
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 Lucebox Founded: 2026 United States www.lucebox.com	Company Information Meta Founded: 2004 United States research.meta.ai/blog/muse-spark-open
Alternatives Wafer	Alternatives Gemini 4 Carbon Google
DeepInfer DeepSeek	GPT-6.1 Terra OpenAI
BaseRT Base Compute	GPT-6.1 Sol OpenAI
vLLM	Inkling Thinking Machines Lab
Nemotron 3.5 Lightning NVIDIA View All	Muse Glimmer Meta View All
Categories Hardware Supported	Categories AI Coding Models Supported AI Models Supported AI Reasoning Models Supported AI Receptionists Supported Foundation Models Supported Large Language Models Supported Multimodal Models Supported Open-Weight AI Models Supported

Integrations Baseten Not Supported Fireworks AI Not Supported Groq Not Supported Hugging Face Not Supported Modal Not Supported Nebius Not Supported OpenRouter Not Supported Together AI Not Supported vLLM Not Supported	Integrations Baseten Supported Fireworks AI Supported Groq Supported Hugging Face Supported Modal Supported Nebius Supported OpenRouter Supported Together AI Supported vLLM Supported View All 9 Integrations
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