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Cloudflare's release of Clef-omni marks a significant architectural shift in decision models by natively integrating audio, video, images, and text into a single inference pipeline. This eliminates the need for cascading transcription or modality-splitting workflows, offering developers a more direct interface to multimodal data while simultaneously improving speed and reducing costs for existing Clef variants.

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Introducing Clef-omni with full multimodality, plus a faster Clef and a cheaper Clef-flash

Cloudflare BlogOctober 9, 20267 min read

We are expanding the Clef decision model family with Clef-omni, natively processing audio, video, images, and text in a single pipeline. We’ve also lowered Clef-flash pricing and boosted Clef inference speeds by up to 2.0x.

Following last week’s release of Clef and Clef-flash, Cloudflare’s open-weight decision models, we decided to bring forth more gifts. Today, we’re releasing Clef-omni, which takes in audio and video input alongside text and image. We also cut the price of Clef-flash so it is now cheaper than Jev, and we made Clef faster. Although the model game is still early for Cloudflare, innovation and iteration is in our DNA, and we apply these principles to everything we do. In fact, the story of Clef came together over the course of less than a week. We decided we wanted to do something in the decision model space on a Friday evening, trained the model over the weekend, and launched it on Thursday. Even with such a short timeline, we were able to ship performant, high-quality, open-weight models for…

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