Replicate Is Joining Cloudflare

We have some big news to share today: Replicate, the leading platform for running AI models, is joining Cloudflare.

We first started talking to Replicate because we shared a lot in common beyond just a passion for bright color palettes. Our mission for Cloudflare’s Workers developer platform has been to make building and deploying full-stack applications as easy as possible. Meanwhile, Replicate has been on a similar mission to make deploying AI models as easy as writing a single line of code. And we realized we could build something even better together by integrating the Replicate platform into Cloudflare directly.

We are excited to share this news and even more excited for what it will mean for customers. Bringing Replicate’s tools into Cloudflare will continue to make our Developer Platform the best place on the Internet to build and deploy any AI or agentic workflow.

Before we spend more time talking about the future of AI, we want to answer the questions that are top of mind for Replicate and Cloudflare users. In short: 

For existing Replicate users: Your APIs and workflows will continue to work without interruption. You will soon benefit from the added performance and reliability of Cloudflare's global network.

For existing Workers AI users: Get ready for a massive expansion of the model catalog and the new ability to run fine-tunes and custom models directly on Workers AI.

Now – let’s get back into why we’re so excited about our joint future.

Before AI was AI, and the subject of every conversation, it was known for decades as “machine learning”. It was a specialized, almost academic field. Progress was steady but siloed, with breakthroughs happening inside a few large, well-funded research labs. The models were monolithic, the data was proprietary, and the tools were inaccessible to most developers. Everything changed when the culture of open-source collaboration — the same force that built the modern Internet — collided with machine learning, as researchers and companies began publishing not just their papers, but their model weights and code.

This ignited an incredible explosion of innovation. The pace of change in just the past few years has been staggering; what was state-of-the-art 18 months ago (or sometimes it feels like just days ago) is now the baseline. This acceleration is most visible in generative AI. 

We went from uncanny, blurry curiosities to photorealistic image generation in what felt like the blink of an eye. Open source models like Stable Diffusion unlocked immediate creativity for developers, and that was just the beginning. If you take a look at Replicate’s model catalog today, you’ll see thousands of image models of almost every flavor, each iterating on the previous. 

This happened not just with image models, but video, audio, language models and more…. 

But this incredible, community-driven progress creates a massive practical challenge: How do you actually run these models? Every new model has different dependencies, requires specific GPU hardware (and enough of it), and needs a complex serving infrastructure to scale. Developers found themselves spending more time fighting with CUDA drivers and requirements.txt files than actually building their applications.

This is exactly the problem Replicate solved. They built a platform that abstracts away all that complexity (using their open-source tool Cog to package models into standard, reproducible containers), letting any developer or data scientist run even the most complex open-source models with a simple API call. 

Today, Replicate’s catalog spans more than 50,000 open-source models and fine-tuned models. While open source unlocked so many possibilities, Replicate’s toolset goes beyond that to make it possible for developers to access any models they need in one place. Period. With their marketplace, they also offer seamless access to leading proprietary models like GPT-5 and Claude Sonnet, all through the same unified API.

What’s worth noting is that Replicate didn't just build an inference service; they built a community. So much innovation happens through being inspired by what others are doing, iterating on it, and making it better. Replicate has become the definitive hub for developers to discover, share, fine-tune, and experiment with the latest models in a public playground. 

Coming back to the Workers Platform mission: Our goal all along has been to enable developers to build full-stack applications without having to burden themselves with infrastructure. And while that hasn’t changed, AI has changed the requirements of applications.

The types of applications developers are building are changing — three years ago, no one was building agents or creating AI-generated launch videos. Today they are. As a result, what they need and expect from the cloud, or the AI cloud, has changed too.

To meet the needs of developers, Cloudflare has been building the foundational pillars of the AI Cloud, designed to run inference at the edge, close to users. This isn't just one product, but an entire stack:

• Workers AI: Serverless GPU inference on our global network.

• AI Gateway: A control plane for caching, rate-limiting, and observing any AI API.

• Data Stack: Including Vectorize (our vector database) and R2 (for model and data storage).

• Orchestration: Tools like AI Search (formerly Autorag), Agents, and Workflows to build complex, multi-step applications.

• Foundation: All built on our core developer platform of Workers, Durable Objects, and the rest of our stack.

As we’ve been helping developers scale up their applications, Replicate has been on a similar mission — to make deploying AI models as easy as deploying code. This is where it all comes together. Replicate brings one of the industry's largest and most vibrant model catalog and developer community. Cloudflare brings an incredibly performant global network and serverless inference platform. Together, we can deliver the best of both worlds: the most comprehensive selection of models, runnable on a fast, reliable, and affordable inference platform.

The ability to share models, publish fine-tunes, collect stars, and experiment in the playground is the heart of the Replicate community. We will continue to invest in and grow this as the premier destination for AI discovery and experimentation, now supercharged by Cloudflare's global network for an even faster, more responsive experience for everyone.

Our vision is to bring the best of both platforms together. We will bring the entire Replicate catalog — all 50,000+ models and fine-tunes — to Workers AI. This gives you the ultimate choice: run models in Replicate's flexible environment or on Cloudflare's serverless platform, all from one place.

But we're not just expanding the catalog. We are thrilled to announce that we will be bringing fine-tuning capabilities to Workers AI, powered by Replicate's deep expertise. We are also making Workers AI more flexible than ever. Soon, you'll be able to bring your own custom models to our network. We'll leverage Replicate's expertise with Cog to make this process seamless, reproducible, and easy.

Running a model is just one piece of the puzzle. The real magic happens when you connect AI to your entire application. Imagine what you can build when Replicate's massive catalog is deeply integrated with the entire Cloudflare developer platform: run a model and store the results directly in R2 or Vectorize; trigger inference from a Worker or Queue; use Durable Objects to manage state for an AI agent; or build real-time generative UI with WebRTC and WebSockets.

To manage all this, we will integrate our unified inference platform deeply with the AI Gateway, giving you a single control plane for observability, prompt management, A/B testing, and cost analytics across all your models, whether they're running on Cloudflare, Replicate, or any other provider.

We are incredibly excited to welcome the Replicate team to Cloudflare. Their passion for the developer community and their expertise in the AI ecosystem are unmatched. We can't wait to build the future of AI together.

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