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Musenet (OpenAI)

By OpenAI
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Free
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What is Musenet (OpenAI)?

MuseNet is a deep neural network that generates 4-minute musical compositions using 10 different instruments, blending various styles from country to classical to pop. It learns patterns of harmony, rhythm, and style from predicting the next token in a vast number of MIDI files, akin to GPT-2's text prediction. It allows the creation of unique compositions by combining multiple styles and instruments, though it has limitations in handling odd pairings. MuseNet uses advanced tokens and the Sparse Transformer to create structured, long-form music.

Music Generation18 favourites
Musenet (OpenAI) screenshot

Musenet (OpenAI)'s Top Features

Key capabilities that make Musenet (OpenAI) stand out.

Generates 4-minute compositions

Supports 10 different instruments

Blends multiple musical styles

Learns from millions of MIDI files

Uses composer and instrumentation tokens

Employs the Sparse Transformer

Handles long-term musical structures

Interactive advanced mode

Simple mode for quick generation

Creates both curated and random samples

Key Details

Pricing Model
Free
Last Updated
August 8, 2024

Tags

musical compositionsdeep neural networkvarious stylesharmonyrhythmGPT-2MIDI filescompositionsmultiple stylesinstrumentsstructured musicSparse Transformer

About the Maker

The organization behind Musenet (OpenAI).

OpenAI logo
OpenAIai lab

Creating safe AGI that benefits all of humanity

234 Tools6 ModelsFounded 2015San Francisco, CA
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AI Models by OpenAI

Large language models from the same organization.

ModelContext WindowPrice (In / Out per M)
GPT-5.4Current1.1M$2.50 / $15.00
GPT-5.3 CodexCurrent400K$1.75 / $14.00
o3Current200K$10.00 / $40.00
GPT-4o miniCurrent128K$0.15 / $0.60
GPT-4oCurrent128K$2.50 / $10.00
GPT-5400K$1.25 / $10.00

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Use Cases

Who benefits most from this tool.

Composers

Creating innovative music by blending multiple styles and instruments.

Music Producers

Generating unique samples for new tracks.

Songwriters

Exploring new melodies and harmonies.

Film & Game Scorers

Composing background scores with diverse styles.

Non-musicians

Experimenting with music creation without formal training.

Music Educators

Teaching musical patterns and styles through AI-generated examples.

AI Researchers

Studying the application of neural networks in creative fields.

Hobbyists

Creating personalized music compositions for fun.

Music Students

Learning about different styles by generating examples.

Podcast Creators

Generating unique music for podcast intros and outros.

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