MuSES

MuSES

ThermoAnalytics
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About

Electro-optic and infrared renderings in MuSES achieve global benchmark accuracy through a stepwise workflow – beginning with heat sources such as engines, exhaust, bearings, and electronics, followed by an in-band diffuse radiosity solution. Then place your sensor at range and render multi-bounce, spectrally-summed radiance values, with DeltaT-RSS contrast metrics. Sensor response curve handy? Import it and see what you’ve been missing. With MuSES, you have reality at your fingertips. Because MuSES covers physics all the way back to heat sources and environmental loads, you can manage thermal signature contrast and evaluate control kits for low observable design in any global location. Heat shields, cooling schemes, and even camo surface treatments can be tested and evaluated for in-band radiance, replete with atmospheric attenuation along sensor line-of-sight. Triage and prioritize your engineering with MuSES early in the development cycle.

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 Supported
Mac Not Supported
Linux Not 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

Companies seeking a complete EO/IR signature simulation software

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 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

Screenshots and Videos

Pricing

No information available.
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:

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Reviews/Ratings

Overall 5.0 / 5
ease 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.

Training

Documentation Supported
Webinars Supported
Live Online Supported
In Person Not Supported

Training

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

Company Information

ThermoAnalytics
Founded: 1996
United States
www.thermoanalytics.com/muses

Company Information

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

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Categories

Simulation Supported

Categories

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
Claim MuSES and update features and information
Claim MuSES and update features and information
Claim Muse Spark Open and update features and information
Claim Muse Spark Open and update features and information