Introducing Solaris August 31, 2026 by Runway Today, we're sharin

Introducing Solaris August 31, 2026 by Runway Today, we're sharing Solaris : the first model in a new family of AI systems we call Interface World Models . Solaris starts with a question: what happens when an operating system generates apps and websites as you use them? Every operating system, from early terminals to Linux and macOS, has dictated what's rendered on screen and what happens when a person or program acts on it. Applications get built on top, and stay fixed until someone pushes an update. Solaris instead renders that layer directly. It's a real-time interactive model that generates the interface itself, frame by frame. Every frame is synthesized as you interact, allowing the interface to respond continuously to your actions. Design is more visual than ever, with pixel-perfect mockups and image models that can generate entire screens that are nearly indistinguishable from finished products. But images don’t run like a website or app. Every piece of software built today still requires a translation: the visual design must first be converted into an intermediate representation (e.g. code) before it can do anything. That intermediate representation limits what an interface can be, and how it responds to human and agent interaction. Every behavior has to be explicitly defined and implemented ahead of time, so software ships as a lossy compression of the space of possible interactions, frozen before any user arrives. The same translation process also sacrifices visual fidelity. Once a design is reduced to a simplified representation, the interface can respond quickly, but only by giving up much of the richness of the original design. Solaris handles rendering and interactions jointly, removing many of the tradeoffs we associate with design today. A single world model generates every frame and every response to user input, eliminating the need for an intermediate representation. Because there’s no conversion step, there’s no loss, and the entire frame becomes the interface. We think Solaris opens up new ways of building websites, apps and other online interfaces. But it’s also a new way to train agents, in much more dynamic environments. Even the best LLMs today struggle to complete basic computer use tasks, like booking a hotel or ordering groceries. Because text-based models are being trained to use coded interfaces, they tend to learn the specific layout they were trained on, and can’t adapt to a slightly different interface (say, two different hotel websites). By collapsing the space between action and response, Solaris lets agents train against interfaces that are constantly changing, and layouts that may never have existed before. What’s New Solaris brings three new capabilities to software. First, Solaris is entirely visual. When an image becomes the application itself, there is no need for a second implementation step hidden beneath the visuals that a user sees. Imagine browsing a virtual clothing store where the showroom itself is the interface. Using a single image of yourself as a reference, you can pick up a shirt from a rack, drag it onto yourself to try it on or rearrange the display as naturally as you would in a physical store. Second, it is alive. Because the application is continuously rendered, it is always evolving rather than waiting for the next user action. Reflections shift with the lighting, and objects respond naturally as they're manipulated. A user can say something as simple as: "Move the table so I can see how it looks" or “Change the color of the couch. ” The result is software that feels less like navigating through scripted pages and more like interacting with a living environment. Even the same starting frame — here, an x-ray of a hand — can respond to the same drag in two entirely different ways. Finally, it is open-ended. Traditional interfaces are limited to the interactions developers anticipated during development, but Solaris can support entirely different behaviors in the same scene, reacting to user interactions in real-time. This flexibility decouples the interface from predefined workflows, instead leaving the capabilities of the driving world model to determine what is possible. Solaris turns an interface into an interactive experience rather than a sequence of pages. Instead of selecting options from menus, users interact directly with the scene itself. Building a salad is as simple as dragging ingredients into a bowl, with the interface responding naturally as each ingredient is added. Today, people turn to an LLM when they get stuck while online. But LLMs answer in text, and most hands-on tasks are not text-based problems. Solaris renders the next step in your context with visuals, and you can steer it. For instance, you can generate an interactive demonstration of combustion, allowing users to experiment with different materials and observe physically plausible reactions as they interact. Why Hasn't This Existed Until Now? Digital interfaces are built on two systems, which until now have lived in different worlds. The systems that know things (e.g., search engines and AI assistants) answer with static content: text, an image, maybe an embedded video. The systems that respond in real time (e.g., JavaScript/CSS, game engines and more recently, interactive world models) create rich, interactive experiences, but they know nothing about your products, your task or what you're trying to accomplish. We've traditionally thought of software interfaces as deterministic programs and world models as generators of visual content. An Interface World Model has to be both at once: a system that understands your intent while continuously rendering an interactive world around it. Once you try to build one, three engineering challenges immediately appear: Speed. Interactions stop feeling interactive somewhere around half a second of delay. Video diffusion models take seconds or minutes to produce a clip, which is acceptable for content creation but too slow for an interface. To cross that threshold, the model has to generate frames sequentially, with each frame depending only on what came before, cheaply enough to keep up with the user. Staying coherent. An interface has to remain consistent across an entire session, not just a single clip. The things it needs to preserve (e.g., text, layout, the identity of objects) are the same things generated video has historically struggled to maintain, and small errors compound the longer generation continues. Cost. Generating every frame is still more expensive than serving a page that was built once. The same work that made Solaris real time also made it orders of magnitude cheaper to run than a standard video diffusion model, and the cost curve continues to improve. Solaris is our bet that these conceptual and technical barriers can be overcome. We built it with three focuses: real-time interaction, coherence over an entire session and visual quality that holds at 720p. How Solaris Works Solaris builds on our Gen-4.5 video generation model, which we adapted to (1) understand interaction and (2) respond in real time. It follows the path we opened with GWM-1 , our general world model. Learning interaction. Solaris treats user input as conditioning for the next frame, the same way it treats text or images. The model observes clicks, drags and other interactions as it generates, using them as signals for what comes next. Because the model only ever sees interactions that have already happened (never future ones), it learns the relationship between user actions and visual outcomes. This means that it knows what should happen when something is clicked, dragged or modified, without requiring those interactions to be explicitly programmed. Running in real time. Standard video diffusion models refine an entire clip over dozens of denoising steps, a process that is far too slow for dynamic user interaction. We converted Solaris into a real-time engine in three stages. First, we taught it to generate frames autoregressively, with each frame depending only on what came before. Next, we distilled the many-step denoising process into just a few steps. Finally, we trained the fast model on its own outputs so visual quality remains stable over long interactions. The result generates frames at interactive speeds while preserving the visual quality of the original teacher model. Reasoning and rendering. Solaris generates the interface one frame at a time, while a language model determines how that interface evolves. The LLM interprets user requests, decides when interactions should modify the current scene versus transition to a new one, defines the behaviors that make the world feel alive and produces the prompts that guide Solaris as it renders each state. Together, the language model and world model separate reasoning from rendering: one decides what the application should do next, while the other generates how that behav