Cloudflare Launches Clef-omni: 30B-A3B Multimodal Decision Model for Audio, Video, Image, and Text

Cloudflare has released Clef-omni, a 30B-parameter mixture-of-experts model with an active 3B parameter footprint, designed specifically as a multimodal decision model capable of processing audio, video, image, and text inputs. The model is framed as a 'decision model,' meaning it is optimized for routing, classification, and policy-enforcement tasks across modalities rather than pure generation. This positions Clef-omni as infrastructure-layer AI, sitting between raw inputs and downstream models to make fast, low-latency routing or filtering decisions at Cloudflare's network edge. Developers building pipelines that need to triage or classify heterogeneous media inputs before passing them to specialized models will find this directly applicable. The MoE architecture keeps inference costs low despite the large parameter count, making it viable for high-throughput edge deployments.