Polyant

Polyant

Exelab
+
+

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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

Polyant is an open source platform for building teams of specialised AI agents that work alongside the people in a company, handling work like sales briefs, customer triage, document extraction, and compliance reporting. Its composable, self-hosted architecture lets teams choose their own model providers, including open-weight models, and their own infrastructure, so they're never locked into one vendor. Governance and audit tooling designed around EU AI Act requirements is built in from day one, with every agent decision logged in an audit registry compliance teams can query directly. Companies keep full control over data residency, deploying on-premises, in their own cloud, or on EU infrastructure managed by Exelab. And agents reach production in days rather than months, without giving up self-hosting or governance. It's built for mid-to-large European enterprises in regulated sectors like banking, insurance, and healthcare, where "just use a hosted API" isn't an option.

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 Supported
Linux Supported
Cloud Supported
On-Premises Supported
iPhone Supported
iPad Supported
Android Supported
Chromebook 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

Enterprises

Support

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

$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

No information available.
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 Not Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

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

Company Information

Exelab
Italy
polyant.ai

Alternatives

Alternatives

Qwen3.8-27B

Qwen3.8-27B

Alibaba
Recursive Flint

Recursive Flint

Recursive

Categories

Categories

AI Agent Builders Supported

Integrations

Amazon Bedrock Not Supported
Amazon Transcribe Not Supported
Anthropic Not Supported
Baseten Supported
Deepgram Not Supported
Fireworks AI Supported
Groq Supported
Hugging Face Supported
Modal Supported
Nebius Supported
Nebius Token Factory Not Supported
OpenAI Not Supported
OpenAI Whisper Not Supported
OpenRouter Supported
Slack Not Supported
Telegram Not Supported
Together AI Supported
WhatsApp Not Supported
vLLM Supported

Integrations

Amazon Bedrock Supported
Amazon Transcribe Supported
Anthropic Supported
Baseten Not Supported
Deepgram Supported
Fireworks AI Not Supported
Groq Not Supported
Hugging Face Not Supported
Modal Not Supported
Nebius Not Supported
Nebius Token Factory Supported
OpenAI Supported
OpenAI Whisper Supported
OpenRouter Not Supported
Slack Supported
Telegram Supported
Together AI Not Supported
WhatsApp Supported
vLLM Not Supported
Claim Muse Spark Open and update features and information
Claim Muse Spark Open and update features and information
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Claim Polyant and update features and information