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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

NVIDIA TensorRT is an ecosystem of APIs for high-performance deep learning inference, encompassing an inference runtime and model optimizations that deliver low latency and high throughput for production applications. Built on the CUDA parallel programming model, TensorRT optimizes neural network models trained on all major frameworks, calibrating them for lower precision with high accuracy, and deploying them across hyperscale data centers, workstations, laptops, and edge devices. It employs techniques such as quantization, layer and tensor fusion, and kernel tuning on all types of NVIDIA GPUs, from edge devices to PCs to data centers. The ecosystem includes TensorRT-LLM, an open source library that accelerates and optimizes inference performance of recent large language models on the NVIDIA AI platform, enabling developers to experiment with new LLMs for high performance and quick customization through a simplified Python API.

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 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

Machine learning engineers and data scientists seeking a tool to optimize their deep learning operations

Support

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

Support

Phone Support 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

Free
Free Version Supported
Free Trial Not Supported

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5

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

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 Supported
Live Online Not Supported
In Person Supported

Company Information

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

Company Information

NVIDIA
Founded: 1993
United States
developer.nvidia.com/tensorrt

Alternatives

Alternatives

OpenVINO

OpenVINO

Intel
GPT-6.1 Sol

GPT-6.1 Sol

OpenAI
Inkling

Inkling

Thinking Machines Lab

Categories

Categories

AI Inference Supported

Integrations

Hugging Face Supported
Baseten Supported
Dataoorts GPU Cloud Not Supported
Fireworks AI Supported
Groq Supported
Kimi K2.6 Not Supported
Kimi K3.1 Pro Not Supported
LaunchX Not Supported
NVIDIA AI Enterprise Not Supported
NVIDIA Jetson Not Supported
NVIDIA Morpheus Not Supported
NVIDIA NIM Not Supported
NVIDIA virtual GPU Not Supported
OpenRouter Supported
PyTorch Not Supported
Python Not Supported
Rosepetal AI Not Supported
TensorFlow Not Supported
Together AI Supported
Ultralytics Not Supported

Integrations

Hugging Face Supported
Baseten Not Supported
Dataoorts GPU Cloud Supported
Fireworks AI Not Supported
Groq Not Supported
Kimi K2.6 Supported
Kimi K3.1 Pro Supported
LaunchX Supported
NVIDIA AI Enterprise Supported
NVIDIA Jetson Supported
NVIDIA Morpheus Supported
NVIDIA NIM Supported
NVIDIA virtual GPU Supported
OpenRouter Not Supported
PyTorch Supported
Python Supported
Rosepetal AI Supported
TensorFlow Supported
Together AI Not Supported
Ultralytics Supported
Claim Muse Spark Open and update features and information
Claim Muse Spark Open and update features and information
Claim NVIDIA TensorRT and update features and information
Claim NVIDIA TensorRT and update features and information