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Description
Muse Code is a beta terminal coding agent from Meta designed to help developers complete complex software engineering work across large codebases. Powered by Muse Spark 1.2, the agent can plan repository changes, write code, run validation steps, and coordinate persistent subagents for difficult development tasks. Muse Code uses a simple main agent loop supported by async background agents that remain active throughout each session. These background agents can gather information, carry out next steps, and decide when to report back to the main agent, reducing latency and unnecessary user steering. The runtime is built around a local event log where every model call, tool run, approval, and edit is appended. This event log makes Muse Code replay-exact and restart-safe, allowing it to resume from the point of failure after a crash. Muse Code also ships with default skills, including /plan, /grill, and /goal, to support structured planning, plan validation, and objective completion. It can be installed on macOS or Linux and is integrated with Meta’s AI developer ecosystem. By combining terminal-based coding, persistent subagents, replay-safe execution, bundled skills, and Muse Spark 1.2, Muse Code helps developers automate larger and longer software engineering workflows.
Description
Muse Voice Transcribe represents Meta’s inaugural venture into real-time audio perception, providing instantaneous automatic speech recognition (ASR), speaker diarization, and endpointing capabilities. This autoregressive multimodal model, part of the Muse Spark series, analyzes audio segments of 80 milliseconds and makes real-time decisions on whether to keep listening or to convert the spoken words into text. The adaptive delay mechanism allows it to adjust the audio context utilized for each word according to the complexity of the speech, thus optimizing the balance between transcription precision and response time. With training encompassing over 70 languages, 25 of which were rigorously validated at the time of its release, the model also seamlessly accommodates arbitrary code-switching, allowing transitions within and across sentences. Furthermore, language, keyword, and contextual biasing features enhance the recognition capabilities for specific names, locations, contacts, or specialized terms. The streaming diarization functionality enables the model to recognize shifts in speakers and can differentiate between more than 20 individual voices. Additionally, the endpointing feature is adept at identifying the commencement of speech and knowing when a user has completed their statement, ensuring a fluid interaction experience. Overall, Muse Voice Transcribe stands out as a cutting-edge tool in the realm of speech recognition technology, merging advanced features with user-friendly application.
API Access
Has API
API Access
Has API
Integrations
Meta AI
Muse Glimmer
Muse Spark
Muse Spark 1.1
Muse Spark 1.2
Muse Spark 1.3
Integrations
Meta AI
Muse Glimmer
Muse Spark
Muse Spark 1.1
Muse Spark 1.2
Muse Spark 1.3
Pricing Details
$1.25 per 1M tokens (input)
Standard pricing: $1.25 per million input tokens and $4.25 per million output tokens
Discounted "contributor" tier costing $0.10 per million input tokens and $0.20 per million output tokens for users who agree to share feedback to improve the AI.
Discounted "contributor" tier costing $0.10 per million input tokens and $0.20 per million output tokens for users who agree to share feedback to improve the AI.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Meta
Founded
2004
Country
United States
Website
meta.ai
Vendor Details
Company Name
Meta
Founded
2004
Country
United States
Website
research.meta.ai/blog/introducing-muse-voice-transcribe
