TLDR: Cloudflare has expanded its Workers AI platform by integrating state-of-the-art image generation models from Leonardo.Ai and text-to-speech/speech-to-text models from Deepgram. This partnership enables developers to leverage high-performance AI capabilities directly on Cloudflare’s global network, facilitating the creation of low-latency image generation platforms and real-time voice agents. The integration highlights Cloudflare’s commitment to providing a comprehensive developer platform for AI applications, emphasizing speed, efficiency, and a holistic suite of tools.
Cloudflare today announced a significant expansion of its Workers AI platform, incorporating advanced image generation models from Leonardo.Ai and cutting-edge text-to-speech and speech-to-text models from Deepgram. This strategic move aims to empower developers with state-of-the-art AI capabilities, hosted directly on Cloudflare’s globally distributed infrastructure, to build highly efficient and low-latency AI-powered applications.
The integration stems from Cloudflare’s foundational belief that AI models would become increasingly faster and smaller, a hypothesis that guided the development of its Workers AI infrastructure with specialized GPUs deployed worldwide. This setup is particularly well-suited for niche use cases requiring rapid inference, such as real-time image generation and responsive audio voice agents.
Peter Runham, CTO of Leonardo.Ai, expressed enthusiasm for the partnership, stating, “We’re excited to enable Cloudflare customers a new avenue to extend and use our image generation technology in creative ways such as creating character images for gaming, generating personalized images for websites, and a host of other uses… all through the Workers AI and the Cloudflare Developer Platform.” Leonardo.Ai, a generative AI media lab, contributes two prominent image generation models: `@cf/leonardo/phoenix-1.0` and `@cf/leonardo/lucid-origin`. The Phoenix model, known for its text rendering and prompt coherence, demonstrated an impressive end-to-end image generation time of 4.89 seconds for a 25-step, 1024×1024 image. The Lucid Origin model, specializing in photorealistic images, achieved a generation time of 4.38 seconds for a similar 25-step, 1024×1024 image.
Deepgram, a leading voice AI company, brings its audio models to the platform, enabling extremely fast speech-to-text and text-to-speech inference. Adam Sypniewski, CTO of Deepgram, highlighted the benefits: “By hosting our voice models on Cloudflare’s Workers AI, we’re enabling developers to create real-time, expressive voice agents with ultra-low latency. Cloudflare’s global network brings AI compute closer to users everywhere, so customers can now deliver lightning-fast conversational AI experiences without worrying about complex infrastructure.” The integrated models include `@cf/deepgram/nova-3` for high-accuracy speech-to-text transcription and `@cf/deepgram/aura-1` for context-aware text-to-speech with natural pacing and expressiveness. The newer Aura 2 model is slated for future release on Workers AI. Enhancements have also been made to simplify the handling of binary MP3 files, eliminating the need for prior conversion to Uint8 arrays.
Cloudflare emphasizes that Workers AI is not merely a standalone inference service but is part of a comprehensive Developer Platform. This allows developers to build complete AI applications by combining Workers for application logic, R2 for storage, and Images for media serving and transformation for image-based platforms.
For real-time voice agents, the platform offers WebRTC and WebSocket support via Workers, along with speech-to-text, text-to-speech, and turn detection models via Workers AI, all orchestrated through Cloudflare Realtime. The platform also supports WebSocket for bi-directional input and output with Deepgram models, enabling persistent connections to inference servers.
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This expansion underscores Cloudflare’s strategy to leverage its unique infrastructure advantages and robust developer tools to foster the creation of advanced AI applications.
