Google Lyria 3 Pro
Google DeepMind's latent-diffusion music model, reached via OpenRouter, as a selectable song-generation engine in AutorunX.

Picking Lyria 3 as the model for a generation.
What Lyria 3 does
Lyria 3 generates a complete, high-fidelity track — vocals and instrumentation together — from a text prompt or lyric sheet, spanning genres from pop to funk to Motown-style arrangements per Google's own model description.
On AutorunX it's exposed as a prompt/lyrics-to-song engine inside Song Builder: describe the style or paste your lyrics, and Lyria 3 returns a produced track built to that description.
Key features
Latent-diffusion architecture
Lyria 3 refines audio latents iteratively rather than predicting tokens sequentially, a technically distinct approach from autoregressive music generators like Suno.
Trained with musician input
Google DeepMind describes tuning Lyria 3 with input from producers and musicians specifically to capture musicality — rhythm, arrangement, and flow from note to note.
Multi-genre, multi-language vocals
Per DeepMind's model description, Lyria 3 spans genres from pop to funk to Motown and can generate vocals in different languages.
SynthID watermarking
Google embeds an inaudible SynthID watermark directly into generated audio, which DeepMind states remains detectable even after compression, slowdown, or re-recording.
Routed via OpenRouter
AutorunX reaches Lyria 3 through OpenRouter rather than a direct integration, and it sits in the Song Builder picker alongside Suno v5, Musicful, and ACE-Step.
How Lyria 3 works
Lyria 3 uses latent diffusion applied to temporal audio latents, trained on audio data annotated with text captions at multiple levels of detail. Instead of predicting discrete speech-style tokens one at a time, the model iteratively refines a full audio latent toward the target described by the prompt — a fundamentally different generation process than autoregressive, token-based music models.
On AutorunX, Lyria 3 is reached indirectly through OpenRouter rather than a direct provider integration, which adds a routing layer relative to engines AutorunX connects to natively — one reason it's presented as a selectable alternative in Song Builder rather than the primary path.
It takes the same input as AutorunX's other song engines — a style prompt or a pasted lyric sheet — and returns a finished track with composition and vocals handled together, so switching to Lyria 3 for a given song idea is simply a different choice in the engine picker.
What people use Lyria 3 for
Alternate melodic take
Run a song idea already tried on Suno v5 through Lyria 3 for a distinctly different production and melodic approach.
Multi-language vocal tracks
Use Lyria 3 where its stated multi-language vocal range is useful for a project's audience.
Cross-engine comparison
Generate the same lyric sheet across Lyria 3, Suno v5, and Musicful to compare arrangement styles before finalizing a track.
Provenance-conscious projects
Choose Lyria 3 for content where a built-in SynthID watermark on the generated audio is a wanted signal.
Who built Lyria 3
Google DeepMind
deepmind.googleGoogle DeepMind is Google's AI research lab, known for models like AlphaFold, Gemini, and Veo. Lyria is DeepMind's dedicated music generation model line, and Lyria 3 is its most advanced release — a latent-diffusion model trained with input from producers and musicians to generate high-fidelity tracks with vocals and instrumentation across a wide range of genres.
How to use Lyria 3 on AutorunX
Lyria 3 is available in Song Builder in Music Lab.
Open the service
Go to Music Lab and open the Song Builder editor.
Set up your input
Enter a style prompt or paste a full lyric sheet for the song you want.
Pick Lyria 3
Open the engine picker and select Lyria 3 — it's an alternative, not the default, so choose it explicitly.
Generate
Run the job and review the finished track.

An example generation rendered with Lyria 3.
Credit usage
Billed per completed song, from your shared AutorunX credit wallet.
Tips for better results with Lyria 3
Compare against Suno v5 directly
Try the exact same prompt on both engines to see how differently a diffusion-based model arranges a song versus Suno's approach.
Weigh cost against the other alternatives
At 50 credits/song, it sits between ACE-Step's 25 and Musicful's 72 — a mid-tier alternative worth trying when budget allows.
Write descriptive, layered prompts
Diffusion-based models respond well to detailed mood and instrumentation descriptions rather than short keyword lists.
Paste full lyrics when vocals matter
Lyria 3 composes melody to fit given lyrics, so pasting a complete lyric sheet gives more control over the vocal content than a style prompt alone.
Lyria 3 — frequently asked questions
Related models
Suno v5
Suno's song-generation model — full arranged tracks with vocals from a prompt.
Music GenerationMusicful
A cloud prompt-to-song API that turns text prompts or lyrics into fully produced tracks, selectable in Song Builder.
Music GenerationACE-Step
AutorunX's owned, self-hosted open-source music engine — Apache 2.0 licensed and the cheapest song-generation option available.
Ready to create with Lyria 3?
Sign up for AutorunX to get 200 free credits across every lab, including Song Builder.