LALAL.AI ranks closest among commercial solutions in Meta's benchmark for professional instrument and vocal separation.
ZUG, SWITZERLAND / ACCESS Newswire / December 23, 2025 / Meta has recently released SAM Audio, a large-scale research model designed for multimodal audio segmentation using text, visual, and temporal prompts. As part of its official evaluation, Meta benchmarked SAM Audio against a range of existing audio separation systems, including LALAL.AI, positioning the study as one of the most comprehensive public comparisons in the field to date.
According to Meta's published results, LALAL.AI demonstrated the smallest performance gap to SAM Audio among commercially available solutions in professional instrument separation, a category focused on high-quality music recordings where fidelity and faithfulness are critical.
"Being selected as a reference in Meta's benchmark confirms that LALAL.AI continues to set the standard for high-quality, production-ready music stem separation," said Nik Pogorski, LALAL.AI Product Owner and Co-founder. "Among all commercial services evaluated, we achieved the smallest performance gap to the research-level SAM Audio, while offering fast, accessible, and reliable solutions for professional workflows."
LALAL.AI's models are built on targeted, transformer-based architectures specifically designed for music stem separation. Unlike generative diffusion models, LALAL.AI uses discriminative transformers that model long-range musical structure while preserving stereo information, timbre, dynamics, and subtle mix details. This approach ensures that separated stems remain faithful to the original recording and suitable for downstream professional use.
Beyond benchmark results, LALAL.AI focuses on practical performance: fast processing, scalable infrastructure, and accessibility without specialized hardware or machine learning expertise.
The platform is used across music production, video production, film, dubbing, broadcasting, and professional studio workflows - environments where speed, reliability, and audio integrity matter as much as raw model capability.
Meta's SAM Audio underscores how rapidly audio AI is advancing and brings valuable attention to the field of audio separation. LALAL.AI welcomes this progress and is proud to be included as a reference point in Meta's research.
At the same time, LALAL.AI remains focused on what matters most for professionals today: high-quality, faithful, stereo-aware music stem separation that is fast, accessible, and production-ready.
With this recognition, LALAL.AI reinforces its position as a go-to solution for high-fidelity music stem separation, trusted by professionals across music production, film, dubbing, video content, and recording studios.
About LALAL.AI:
LALAL.AI is a leading AI-powered audio processing service that helps users separate vocals, instruments, and other audio components from music and video files. Launched in 2020, the platform is used by musicians, producers, audio engineers, content creators, and media professionals for remixing, mastering, audio restoration, dubbing, and content repurposing.
Contact Information
Clara Alex
PR & Communications Manager
klara.alexeeva@lalal.ai
SOURCE: LALAL.AI
View the original press release on ACCESS Newswire:
https://www.accessnewswire.com/newsroom/en/computers-technology-and-internet/lalal.ai-leads-commercial-tools-in-metas-benchmark-for-profession-1120473
