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What is Muse Spark Open?

Muse Spark Open is a large-scale open-weight artificial intelligence model developed by Meta for multimodal understanding, software engineering, autonomous agents, and long-horizon reasoning. Released in October 2026, the model provides downloadable weights that allow developers to deploy and customize it outside Meta's hosted AI services. It uses a mixture-of-experts architecture containing 816 billion total parameters, with approximately 42 billion parameters activated during inference. Its one-million-token context window supports processing extensive documents, large software repositories, and lengthy sequences of instructions and interactions. The model is designed for complex coding workflows involving source code analysis, debugging, feature implementation, application development, and software testing. Its multimodal capabilities enable AI agents to interpret visual information and combine that understanding with reasoning and automated computer interactions. Meta demonstrated the model performing local software development tasks and controlling DaVinci Resolve to analyze video footage and prepare edited content. Muse Spark Open supports on-device deployment using two Apple M5 Ultra Mac Studio computers running the MLX framework, with additional compatibility across AMD, Intel, and NVIDIA hardware. Supported inference frameworks include SGLang, vLLM, TensorRT-LLM, Hugging Face Transformers, llama.cpp, and Unsloth, with optimized GPU kernels for improved processing performance. Developers can customize the model using PyTorch and TorchTitan to adapt its behavior to specialized tasks, organizational requirements, and application workflows. Muse Spark Open is distributed under the Muse Model License with limited commercial terms and is available through Hugging Face, Amazon SageMaker AI, Google Cloud Model Garden, Microsoft Foundry Models, and several hosted API providers.

What is DeepSeek-V4-Pro?

DeepSeek-V4-Pro is a next-generation Mixture-of-Experts language model designed to deliver high performance across reasoning, coding, and long-context AI tasks. It features a massive architecture with 1.6 trillion total parameters and 49 billion activated parameters, enabling efficient computation while maintaining strong capabilities. The model supports an industry-leading context window of up to one million tokens, allowing it to process extremely large datasets, documents, and workflows. Its hybrid attention mechanism combines advanced techniques to optimize long-context efficiency and reduce computational requirements. DeepSeek-V4-Pro is trained on over 32 trillion tokens, enhancing its knowledge base and reasoning abilities. It incorporates advanced optimization methods to improve training stability and convergence. The model supports multiple reasoning modes, including fast responses and deep analytical thinking for complex problem solving. It performs strongly across benchmarks in coding, mathematics, and knowledge-based tasks. The architecture is designed for agentic workflows, enabling it to handle multi-step tasks and tool-based interactions. As an open-source model, it offers flexibility for customization and deployment across various environments. It also supports efficient memory usage and reduced inference costs compared to previous versions. The model’s capabilities make it suitable for both research and enterprise applications. Overall, DeepSeek-V4-Pro represents a significant advancement in scalable, high-performance AI with long-context intelligence.

Media

Media

Integrations Supported

Together AI
Baseten
Fireworks AI
Hugging Face

Integrations Supported

Together AI
C
C#
C++
Cheaper Inference
Cline
Go
Java
Kotlin
Kubernetes
PowerShell
Reasonix
Scala
Swift
TypeScript
YAML
ZooClaw

API Availability

API Availability

Has API

Pricing Information

$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

Pricing Information

$0.435 per 1M tokens (input)
$0.435 per 1 million input tokens (cache miss), $0.003625 per 1 million input tokens (cache hit), and $0.87 per 1 million output tokens
Free Version

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Customer Service / Support

Not specified

Customer Service / Support

Not specified

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Meta

Date Founded

2004

Company Location

United States

Company Website

research.meta.ai/blog/muse-spark-open

Company Facts

Organization Name

DeepSeek

Date Founded

2023

Company Location

China

Company Website

deepseek.com

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

AI Receptionists

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Large Language Models

Not specified

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