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What is Muses?

Muses functions as a sophisticated writing companion driven by artificial intelligence, aimed at simplifying the content creation journey by providing expert-level assistance without requiring any installations or extensive learning curves. It allows users to seamlessly switch among various high-quality AI models, accommodating a range of creative styles and needs. The unique "Tab to Flow" feature is designed to remain discreet until needed, offering smart completions that help maintain the momentum of writing, while "Spark to Story" skillfully converts spontaneous thoughts or moments of inspiration into well-structured narratives. Users can conveniently upload reference materials, enabling the AI to craft content that is informed and supported by their research, and all generated text is automatically checked for factual correctness to boost reliability. Muses also compiles relevant information from the internet, sourcing materials that enhance articles, blog posts, marketing copy, and larger writing endeavors. With a focus on nurturing creativity effortlessly, it integrates state-of-the-art AI technology, immediate support, and thorough validation, ensuring a smooth writing experience that empowers users to improve their work with ease. The platform's intuitive design invites writers at all skill levels to unleash their creativity without the usual challenges associated with writing tools, making it accessible to everyone eager to express their ideas. Ultimately, Muses stands as a valuable resource for anyone looking to elevate their writing while enjoying the process.

What is Muse Spark 1.2?

Muse Spark 1.2 is a coding-focused AI model from Meta designed to support advanced software engineering tasks through Muse Code and the Meta Model API. The model builds on Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows. Muse Spark 1.2 powers Muse Code, a terminal coding agent that can plan repository changes, write code, validate outputs, and work across large codebases. Muse Code uses persistent async background agents that stay active throughout a session to reduce redundant information gathering and support difficult multi-step work. The runtime uses a local event log where model calls, tool runs, approvals, and edits are appended, making sessions replay-exact and restart-safe. Muse Spark 1.2 was co-trained with Muse Code so the model can take advantage of its toolset, harness workflows, goals, compaction, and subagent architecture. Meta significantly scaled training compute on coding tasks and expanded training environment diversity to improve the model’s engineering capabilities. The model was also trained on long-horizon coding tasks, including whole-repository generation, large end-to-end projects, auto-research, and extended iterative work. Its training approach uses planning, goal conditioning, context compaction, rejection-sampled harness trajectories, and self-improvement data generated with Muse Spark 1.1. Meta also tested Muse Spark 1.2 on long-running GPU kernel optimization workflows where the model wrote, compiled, profiled, and improved Triton kernels over many tool calls. By combining coding-focused training, agentic runtime integration, persistent subagents, long-horizon reasoning, replay-safe execution, and API availability, Muse Spark 1.2 helps developers and AI agents complete complex software engineering work with less intervention.

Media

Media

Integrations Supported

C#
Claude Agent SDK
Claude Code
Claude Opus 4.6
Claude Sonnet 4.5
GPT-5
Hermes Agent
Java
JavaScript
LangChain
Lua
Muse Code
Muse Video
OpenAI Codex
OpenClaw
Python
R
Scala
Swift
Vercel AI SDK

Integrations Supported

C#
Claude Agent SDK
Claude Code
Claude Opus 4.6
Claude Sonnet 4.5
GPT-5
Hermes Agent
Java
JavaScript
LangChain
Lua
Muse Code
Muse Video
OpenAI Codex
OpenClaw
Python
R
Scala
Swift
Vercel AI SDK

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Version
Free Trial Offered?

Pricing Information

$1.25 per 1M tokens (input)
$1.25 per million tokens in input, and $4.25 per million tokens of output
Free Version
Free Trial Offered?

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Muses

Company Location

United States

Company Website

www.muses.my/

Company Facts

Organization Name

Meta

Date Founded

2004

Company Location

United States

Company Website

meta.ai

Categories and Features

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