The Best 56 Audio Generation Tools in 2025

MusicGen is a text-to-music model that generates high-quality music samples based on text descriptions or audio prompts, utilizing a 1.5-billion-parameter autoregressive Transformer architecture.

EnCodec is a high-fidelity real-time neural audio codec developed by Meta AI, employing end-to-end training and supporting multiple bandwidth settings.

High-fidelity real-time neural audio codec developed by Meta AI, specifically trained for the MusicGen project

BigVGAN is a universal neural vocoder based on large-scale training, capable of generating high-quality audio waveforms.

MusicGen is a text-to-music model that generates high-quality music samples based on text descriptions or audio prompts.

Stable Audio Open 1.0 is a text-to-audio generation model capable of generating up to 47 seconds of 44.1kHz stereo audio based on text prompts.

BigVGAN is a high-performance neural vocoder that achieves high-quality audio synthesis through large-scale training, supporting multiple sampling rates and frequency band configurations.

EnCodec is a real-time high-fidelity neural audio codec developed by Meta AI, supporting multiple bandwidth configurations and streaming processing.

A text-to-audio model fine-tuned from musicgen-stereo-melody-large, designed for music producers to generate 32kHz stereo audio song ideas

AI model that generates high-quality stereo music samples based on text descriptions, supporting 300M parameter scale

MusicGen Small is a Transformer-based music generation model capable of producing high-quality music clips from text descriptions.

MusicGen is a text-to-music generation model capable of producing high-quality music samples based on text descriptions or audio prompts.

MusicGen is a simple and controllable music generation model capable of producing high-quality music based on text descriptions or melody inputs.

MusicGen is a text-to-music generation model developed by Meta AI, capable of producing high-quality music samples based on text descriptions or audio prompts.

ACE-Step-v1-3.5B is a text-to-audio model that supports high-quality audio generation, suitable for music and sound effects creation.

A diffusion model that generates up to 11 seconds of 44.1kHz stereo audio based on text prompts

High-quality low-bitrate speech codec model based on Transformer architecture, specifically designed for speech data compression and generative modeling

MAGNeT is a text-to-music and text-to-audio model capable of generating high-quality audio samples from text descriptions.

A hybrid rap vocal model focused on improving the generation quality of Chinese rap/hip-hop music

A high-quality speech language model trained on a single GPU within 24 hours, fine-tuned based on Qwen2.5-0.5B, using Hubert tokens as vocabulary

InspireMusic is a unified toolkit focused on music generation, song generation, and audio generation, supporting high-fidelity and long-form music generation.

TangoFlux is an efficient text-to-audio generation system that combines flow matching and CLAP preference optimization technologies to quickly produce high-quality audio.

MAGNeT is a non-autoregressive Transformer-based text-to-music and sound effects generation model capable of producing high-quality audio samples from text descriptions.

MAGNeT is a text-to-music and text-to-sound model capable of generating high-quality audio samples from text descriptions.

MusicGen is a text-to-music generation model developed by Meta AI, supporting stereo generation and capable of producing high-quality music samples based on text descriptions or audio prompts.

MAGNeT is a text-to-music and text-to-sound model that can generate high-quality audio samples based on text descriptions.

YuE is a groundbreaking open-source foundational model series specifically designed for music generation, particularly for converting lyrics into complete songs (lyrics2song).

Stereo music generation model released by Meta AI, capable of generating high-quality music from text descriptions

MAGNeT is a text-to-music and text-to-sound model capable of generating high-quality audio samples from text descriptions.

A Meta MusicGen model verified by Unity Sentis that can generate stylized music up to 30 seconds long based on text prompts.

MAGNeT is a text-to-music and text-to-sound model capable of generating high-quality audio samples based on text descriptions. It is a non-autoregressive Transformer model based on masked generation, using a 32kHz EnCodec tokenizer.

A symbolic audio model based on the Perceiver AR architecture, pre-trained on the GiantMIDI-Piano dataset for symbolic audio generation

Tango 2 is an improved text-to-audio generation model based on Tango, optimizing audio generation quality through DPO alignment training

YuE is a series of open-source foundational models specifically designed for music generation, particularly for converting lyrics into complete songs (lyrics2song).

TANGO is an instruction-guided diffusion model for text-to-audio generation, capable of producing realistic audio including human voices, animal sounds, and natural or artificial sound effects based on text prompts.

This is a speech language model based on discrete Hubert tokens, focusing on efficient training and capable of generating speech segment continuations.

TunesFormer is a Transformer-based dual-decoder model designed to generate melodies that conform to user-defined musical forms, especially suitable for traditional Irish music.

Generative AI-based MIDI music creation model supporting generation from scratch or template-based continuation

MusicGen is a text-to-music generation model developed by Meta AI, capable of producing high-quality stereo music samples based on text descriptions or audio prompts.

This is a large Transformer model with 780 million parameters, specifically designed for music generation and transcription tasks, using anticipatory training methods.

Tango 2 is an improved text-to-audio generation model based on Tango, achieving alignment training for audio generation through Direct Preference Optimization (DPO) technology

InspireMusic is a unified framework focused on music generation, song generation, and audio generation, integrating autoregressive transformers with flow-matching models through audio tokenization technology, supporting high-quality long audio generation.