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Description

Muse Spark 1.1 is Meta’s upgraded multimodal reasoning model designed to support advanced agentic workflows, coding tasks, computer use, and complex tool orchestration. Developed by Meta Superintelligence Labs, it builds on Muse Spark with major gains in planning, tool use, long-context reasoning, multimodal perception, and real-world task execution. The model can work across external apps and services, native tools, MCP servers, custom skills, browsers, scripts, images, video, PDFs, and audio inputs. Muse Spark 1.1 can act as a main agent by gathering context, creating a plan, and delegating work to parallel subagents, or operate as a subagent that follows instructions and escalates when needed. Its 1 million token context window allows it to retain earlier actions, retrieve information from long workflows, and compact context while preserving critical details. The model is also trained for computer-use tasks, deciding when to automate with scripts and when to interact directly with an interface. In coding workflows, Muse Spark 1.1 can diagnose bugs, implement features, migrate large codebases, generate web applications, take screenshots, identify UI issues, and validate fixes. Its multimodal strengths include visual-to-code generation, detailed image and video captioning, grounded perception, and workflows where seeing, reasoning, and acting happen together. Available through the Meta Model API public preview and in Thinking mode inside Meta AI, Muse Spark 1.1 gives developers and users a more capable foundation for building agents, automations, coding assistants, and multimodal productivity tools.

Description

We have developed MuseNet, an advanced deep neural network capable of producing 4-minute musical pieces featuring 10 distinct instruments, while seamlessly merging genres ranging from country to the classical compositions of Mozart and even the iconic sounds of the Beatles. Rather than being programmed with musical knowledge, MuseNet identifies and learns patterns of harmony, rhythm, and style through the process of predicting the subsequent token in a vast collection of MIDI files. This innovative model employs the same unsupervised technology as GPT-2, a robust transformer model designed to anticipate the next token in a sequence, whether it pertains to audio or text. Thanks to MuseNet's understanding of diverse musical styles, we are able to create unique blends of musical generations. We eagerly anticipate the creative ways in which both musicians and those without formal training will leverage MuseNet to craft original compositions! Users can select a composer or style and optionally begin with a well-known piece, allowing them to delve into the rich array of musical styles that the model can produce. This opens up exciting possibilities for artistic exploration and experimentation.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

.NET Yes 
Claude Agent SDK Yes 
Codex CLI Yes 
Facebook Messenger Yes 
Go Yes 
Gray Swan Yes 
Hermes Agent Yes 
Instagram Yes 
Lua Yes 
Meta Model API Yes 
Muse Video Yes 
OpenAI No 
OpenAI Agents SDK Yes 
OpenClaw Yes 
PowerShell Yes 
Python Yes 
R Yes 
Ruby Yes 
Rust Yes 
Solidity Yes 

Integrations

.NET No 
Claude Agent SDK No 
Codex CLI No 
Facebook Messenger No 
Go No 
Gray Swan No 
Hermes Agent No 
Instagram No 
Lua No 
Meta Model API No 
Muse Video No 
OpenAI Yes 
OpenAI Agents SDK No 
OpenClaw No 
PowerShell No 
Python No 
R No 
Ruby No 
Rust No 
Solidity No 

Pricing Details

$1.25 per 1M tokens (input)
$1.25 per million tokens in input, and $4.25 per million tokens of output
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Meta

Founded

2004

Country

United States

Website

meta.ai

Vendor Details

Company Name

OpenAI

Founded

2015

Country

United States

Website

openai.com/blog/musenet/

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