Sony and Universal Sue Suno Again, This Time Over Its v6 Music Model

Sony Music and Universal Music Group have sued Suno over its v6 generative music model, alleging copyright infringement. The complaint targets v6 alone, not earlier models, and is the labels' second action against the company.

The suit was filed in the U.S. District Court for the District of Massachusetts. The complaint runs to 45 pages, according to case details reported on Sept. 18 Variety. Trade coverage has described it as a second lawsuit following the labels' original 2024 action The Hollywood Reporter.

At issue is how v6 was built. Sony and UMG allege v6 was trained on user outputs from earlier Suno models. Those earlier models, the labels allege, were trained on unlicensed music taken from YouTube and other sources The Verge. No license exists between the labels and Suno.

The labels call that lineage "model laundering." Their argument is that training a new model on outputs of an infringing model does not remove infringement. Sony further alleges Suno used distillation, where a new student model learns to match the behavior of older teacher models. Many labs use such synthetic outputs and interaction data from a live system to train its successor.

Suno disputes that account. Jack Brody of Suno said v6 was trained from the ground up with a new set of data including user data The Verge. The company has not licensed repertoire from Sony and UMG, but says v6 training data is separate from the prior models at issue in the earlier case.

On June 24, 2024, Sony Music, Universal Music Group and Warner Records sued Suno and Udio for copyright infringement Reuters. That case set out the labels' claim that training on copyrighted recordings without authorization infringes. The v6 suit extends that claim to a second generation trained in part on synthetic data from the first.

Udio has taken a different path. Universal Music Group and Udio settled litigation and announced strategic agreements for a new licensed AI music creation platform Universal Music Group. The companies plan to launch it in 2026. Suno has no equivalent agreement with Sony or UMG.

The broader context here is provenance across generations. If version one ingested unlicensed audio, does version two trained on version-one outputs inherit that liability. The labels answer yes. Suno's public answer is that retraining from the ground up with a new dataset resets the chain.

In my view, the stakes extend beyond music. Distillation, synthetic-data loops, and user-interaction logs are now standard for improving models in many fields. A ruling that synthetic outputs carry forward the copyright status of the teacher's training data would force closer tracking of lineage, filtering, and consent at each step. It would also give licensors leverage over successor models, not only the first model.

Worth flagging for builders is the licensing split now emerging. One lab settles and builds a licensed platform with UMG. Another litigates whether retraining cleans the dataset. For enterprise buyers and API consumers, that affects indemnity, data governance, and product plans. Licensed catalogs cost more and limit coverage. User-data-trained systems may generate more broadly, with higher legal uncertainty.

In practical terms, the case will turn on details not yet public. What audio was in the teacher set. What share of v6 data came from user outputs. How distillation was implemented. Whether filtering or deduplication limited memorization. Clearer rules here could make licensed building easier for the next wave of music tools.