Generate music

Which models are the fastest for generating music?

If speed is your main concern, models like lucataco/ace-step are designed for fast generation of longer tracks. Larger or more complex models such as meta/musicgen (3.5 B parameters) tend to take longer and cost more per minute of audio.

Which models offer the best balance of cost and quality?

For a good balance, the medium- or small-sized variants of meta/musicgen (for example, the “melody” version) are strong choices: they provide solid audio quality without the heavy compute of the largest models. Models like minimax/music-1.5 and google/lyria-2 offer higher fidelity and structure but at a higher cost.

What works best when I want to generate a full-length song (with vocals and instrumentation)?

If you want a structured song with vocals and instrumentation, minimax/music-1.5 is designed for full-length tracks with vocals, verse-chorus structure, and rich arrangements. google/lyria-2 delivers professional-grade stereo audio but may have shorter duration limits. Smaller meta/musicgen models can work well for instrumental tracks.

What if I just need background music for video content or game loops?

For background or looped music, you don’t need the complexity of a full-song model. A loop-optimized variant, such as andreasjansson/musicgen-looper, can generate fixed-BPM loops more quickly and at lower cost. This is ideal for short, repeatable segments used in videos or games.

How do I choose between models when I want a custom style (e.g., “80s neon synth pop with vocals”)?

If you need vocals and a polished result, start with minimax/music-1.5 or google/lyria-2. For instrumental sketches or quick iterations, use a mid-tier meta/musicgen variant. If you already have a chord progression, pick a chord-conditioned model like TODO: add link for "MusicGen-Chord". Experiment with prompts and durations to get the exact style you want.

What are the main types of AI music-generation models, and how do they differ?

There are a few core approaches to how these models create music:

• Text-to-music: Turn a written description (like “lo-fi hip-hop with soft piano”) into a full audio clip.
• Melody-conditioned: Use an existing melody or audio snippet as a foundation and build new music around it.
• Chord-conditioned: Follow a chord progression you provide to shape the harmony and structure.
• Vocal + song models: Generate vocals and structured songs with verses and choruses (e.g., minimax/music-1.5).
• Loop models: Produce short, repeatable segments ideal for background or game music.
  Each type offers a different balance between creative control, audio quality, and generation speed.

What kinds of outputs can I expect from these models?

Most models output stereo audio at 32 kHz or 48 kHz. Duration limits vary—some meta/musicgen models focus on short clips, while models like minimax/music-1.5 support up to around four minutes. Higher-fidelity models produce more polished instrumentation and vocals.

How can I self-host or push a model to Replicate?

You can fine-tune models like meta/musicgen with your own audio dataset and deploy them to Replicate. Fine-tuning requires some setup and compute, especially if you want to maintain or add vocal output.

Can I use these models for commercial work?

Yes, many users use these models in commercial projects. However, you should check the model’s license and any underlying data usage restrictions. Pay special attention to vocal output, which may involve more complex rights considerations.

How do I use or run these models?

Running a model typically involves providing a text prompt and optional inputs like melody or chords. The model generates an audio clip you can download. Each model has its own set of input fields, so check the model’s documentation before running.

What should I know before running a job in this collection?

• Duration: Longer tracks cost more and take longer to generate.
• Fidelity: High-end models like google/lyria-2 offer better audio quality.
• Inputs: Make sure any melody or chord inputs are clean and formatted properly.
• Prompts: Clear genre and instrument prompts improve results.
• Licensing: Check rights if you’re using output commercially.
• Fine-tuning: Some base models don’t support vocals without customization.

Any other tips or considerations?

Start with short clips to test styles and costs before committing to longer tracks. Use chord-conditioned models if you already have a harmonic structure. Loop models are best for game audio or UX sound design. Even with AI, you may want to do some final mixing or mastering for professional use.