Audience
Game developers wanting a tool to streamline prototyping and explore new gameplay concepts through AI-generated sequences
About Muse
Microsoft has unveiled Muse, a groundbreaking generative AI model designed to revolutionize gameplay ideation. Developed in collaboration with Ninja Theory, Muse is a World and Human Action Model (WHAM) trained on data from the game Bleeding Edge. This AI model possesses a comprehensive understanding of 3D game environments, including physics and player interactions, enabling it to generate consistent and diverse gameplay sequences. Muse can produce game visuals and predict controller actions, facilitating rapid prototyping and creative exploration for game developers. By analyzing over 1 billion images and actions, Muse demonstrates the potential to assist in game preservation by recreating classic titles for modern platforms. While still in the early stages, with current outputs at a resolution of 300×180 pixels, Muse represents a significant advancement in integrating AI into the game development process, aiming to enhance, not replace, human creativity.
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Muse Ember
Muse Ember is an efficient multimodal AI model developed by Meta for autonomous agents, software engineering, complex reasoning, and high-volume task automation. The model specializes in repetitive agentic operations such as tool calling, code analysis, information extraction, workflow routing, and document processing. It supports text, images, audio, video, and PDF inputs with a one-million-token context window and a maximum output length of 512,000 tokens. Muse Ember can execute multistep business workflows, analyze large software repositories, perform coding tasks, and interpret visual information from documents and screenshots. Its cost-efficient architecture makes it suitable for multi-agent systems in which larger models handle planning while Muse Ember executes frequent subtasks. The model is available through Meta Model API and Muse Code, with API pricing starting at $0.10 per million input tokens and $0.50 per million output tokens.
Learn more about Muse Ember
Muse Wonder
Muse Wonder is a frontier artificial intelligence model developed by Meta for personal assistance, professional workflows, software development, and autonomous agent tasks. The model combines Active Memory, which retrieves relevant information from previous conversations, with Active Focus, which supports sustained execution of complex, multistep assignments. Muse Wonder can assist with research, document analysis, financial and legal information, software engineering, and business process automation. Its agentic capabilities enable it to work across applications, use contextual information, adapt to obstacles, and request clarification or approval when necessary. The model supports coding activities ranging from small application development to complex software projects involving repeated testing and revision. Muse Wonder is available through the Meta Model API and Muse Code, with additional integration into Meta's Muse assistant planned for future releases.
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Muse Spark 1.2
Muse Spark 1.2 is Meta’s coding-focused model update designed to power Muse Code and improve software engineering workflows. The model is built for code generation, complex debugging, codebase understanding, long-horizon development tasks, and end-to-end developer workflows. Muse Spark 1.2 was co-trained with Muse Code to improve performance inside the terminal coding agent environment. It supports planning, goal conditioning, context compaction, subagent coordination, and iterative coding workflows across large repositories. The model was trained with expanded coding compute, diverse development environments, self-improvement loops, and long-running engineering tasks. Built for AI developers and software teams, Muse Spark 1.2 helps agents plan, write, validate, debug, and optimize code with greater autonomy.
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Muse Spark Open
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.
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Integrations
Company Information
Microsoft
Founded: 1975
United States
microsoft.com
Videos and Screen Captures
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Product Details
Platforms Supported
Cloud
Training
Documentation
Live Online
Webinars
In Person
Videos
Support
Phone Support
Online
Muse Frequently Asked Questions
Q: What kinds of users and organization types does Muse work with?
Muse works with these users and organization types: Mid Size Business, Small Business, Enterprise, Freelance, Nonprofit, Government, and Startup.
Q: What languages does Muse support in their product?
Muse supports these languages: English.
Q: What kind of support options does Muse offer?
Muse offers support via phone support and online.
Q: What other applications or services does Muse integrate with?
Muse integrates with: Microsoft Foundry, Claude Fable 5.1, Claude Fable 5.2, Claude Haiku 5.5, Claude Mythos 5.2, Claude Mythos 5, Claude Opus 5.5, Claude Opus 5, Claude Sonnet 5.5, GPT-5.4 mini, GPT-5.4 nano, GPT-5.6 Sol Ultrafast, GPT-5.6 Terra, GPT-6.2 Astra, GPT-6.1 Sol, GPT-6.1 Terra, GPT-6.2 Sol, GPT‑6 Cyber, GPT-6 Luna, GPT-6 Sol, GPT-6 Astra, Holo4, Hugging Face, and OpenAI Bel.
Q: What type of training does Muse provide?
Muse provides training in the form of documentation, live online, webinars, in person, and videos.
