Suno Releases v6 Music Model Family Trained on Licensed Data from Warner, BMG, Believe
Suno unveiled its v6 model family, trained on licensed data from Warner Music Group, BMG, and Believe, as the AI music startup continues fighting copyright lawsuits from Sony, Universal Music Group, and individual artists. The company plans to retire its older, non-licensed models entirely.
Suno unveiled a new model family called Suno v6 on Wednesday, built using licensed data from music labels and distributors including Warner Music Group, BMG, and Believe. The company said Suno v6 was not trained on the data used to build its earlier models, which are now the subject of multiple copyright lawsuits.
Suno is releasing three versions of the family. The base Suno v6 model, available to paying users, is designed for reliable, steerable output. Suno v6 Wild is an experimental version, also paid-tier only, intended for ideation and less predictable results. Suno v6 Mini is a faster model available to all users, including free tier. Suno plans to retire its older models entirely, though an exact retirement date was not disclosed. Pricing per generation and any API cost structure were not disclosed.
New capabilities in v6 include prompt-based or lyric-word editing of specific song sections, and support for text, image, or video references when generating tracks. Users can also isolate an instrument from a sample and build a new beat around it.
Suno also plans to let users remix existing songs, but only for artists who opt in through a new program the company is building with music labels. Jack Brody, Suno's chief product officer, told TechCrunch the feature is designed to create new revenue streams for rights holders. "I think the music ecosystem and our partners are always looking for ways to create more revenue opportunities for their rights holders and artists. So a big part of this release is creating additional revenue streams there," Brody said.
Legal backdrop
The release lands amid a wave of litigation. Suno settled with Warner Music Group last year and struck a licensing deal with BMG last month. But the company still faces active lawsuits from Sony Music and Universal Music Group, from artist Jason Isbell, and from users alleging Suno prioritized growth over data security. The v6 announcement also comes one day after Suno admitted it had trained its models using YouTube videos — a disclosure that raises fresh questions about the provenance of data behind its prior model generations.
Suno has previously said it will add watermarks to AI-generated songs and recently introduced download limits tied to account tier. Brody framed these moves as an effort to address platform-level issues like streaming fraud, though he pushed responsibility for content moderation onto distributors: "We can help manage some of the broader ecosystem challenges like streaming fraud and kind of mass exportation and uploading to distributors that are low intent. At the end of the day, we think it is up to the distributors and the platforms to govern what content goes on there."
Despite the legal exposure, Suno has raised more than $819 million in funding to date, according to PitchBook data.
What this means
Suno's pivot to licensed training data is a direct response to legal and reputational risk, not a voluntary shift. By retiring its older models — the ones actually named in lawsuits from Sony and UMG — Suno appears to be trying to draw a line between its legally exposed past and a cleaner, licensed future, even as those older lawsuits remain unresolved. The YouTube training admission, surfacing just a day before this launch, undercuts the narrative that v6 represents a clean break: it confirms the company's data practices were murkier than previously acknowledged. Whether licensing deals with three companies (Warner, BMG, Believe) are enough to satisfy holdouts like Sony and UMG, or to settle claims from artists like Jason Isbell, remains the open question. The revenue-share remix program signals Suno's long-term bet: that labels will eventually see AI remixing as a monetizable feature rather than an infringement, provided they control the opt-in.
Related Articles
Nanbeige4.3-33B released: 33B open model with 512K context targets agentic coding and cowork tasks
Nanbeige has released Nanbeige4.3-33B, a 33B-parameter BF16 model with a 524,288-token (512K) context length. It is the flagship teacher model of the Nanbeige4.3 series and will anchor distillation into smaller models such as Nanbeige4.3-3B. Nanbeige claims state-of-the-art agentic performance among open models in the ~30B class.
KRAFTON releases Raon-1 mini preview, a 28.8B-parameter MoE model with 4.3B active and 262,144-token context
KRAFTON AI has released Raon-1 mini preview, a Mixture-of-Experts language model trained from scratch with 28.8B total and 4.3B active parameters. It is Apache 2.0 licensed, supports 262,144 tokens of context, and ships with a speculative decoding draft model that KRAFTON says reaches up to 2.18× higher output throughput on a single NVIDIA B300.
NVIDIA releases Nemotron 3.5 Bolt E4B 4GB, an open small model targeting 4GB of VRAM
NVIDIA released Nemotron 3.5 Bolt E4B 4GB, an open small language model post-trained from Gemma 4 E4B. It targets local voice assistants, game characters and robots, with a footprint of about 4GB of VRAM on RTX and Jetson hardware.
iFLYTEK Healthcare Upgrades Spark Medical Model to V3.7, Claims 99.6 on MedBench 5.0
iFLYTEK Healthcare announced on October 22 a full upgrade of its Spark medical large model to V3.7, and reports a score of 99.6 on MedBench 5.0. The company says the model now combines speech, medical imaging and language understanding for clinical agent use. The benchmark and usage figures are company-reported.
Comments
Loading...