UFC: Universal FocalCodec for Ultra-low Bitrate Audio Compression

Neural audio codecs (NACs) provide compact discrete representations for audio language models (ALMs). However, many NACs rely on multiple codebooks, increasing token rates and often requiring a two-stage autoregressive and non-autoregressive decoding procedure, and are limited to speech. We propose Universal FocalCodec (UFC), a family of single-codebook NACs for 16 kHz speech, music, and sound. UFC builds on the Qwen3-Omni Audio Transformer (AuT) encoder and quantizes its intermediate representations into a single discrete token stream. We introduce variants operating at frame rates from 13 to 52 Hz, corresponding to bitrates of 0.195 to 0.780 kbps, offering a speed-quality trade-off. Across multiple domains and evaluation metrics, UFC is competitive with state-of-the-art universal codecs. UFC-13 achieves the strongest overall performance among universal codecs operating around 0.195 kbps, leading on most metrics and outperforming several higher-bitrate systems. Our ablations further reveal that early AuT layers provide a favorable balance of semantic and acoustic information for neural audio coding. UFC shows that ALMs can reuse their own audio encoders to generate audio instead of relying on a separate decoding methodology.