Runway Research | Introducing Runway GWM-1

A state-of-the-art model built to interact with the real world.

December 11, 2025

by Runway

GWM-1: our state-of-the-art General World Model, built to simulate reality in real time. Interactive, controllable and general-purpose.

Two years ago, we introduced a new research direction: General World Models. A world model is an AI system that builds an internal representation of an environment and uses it to simulate future events within that environment. The aim of general world models is to represent and simulate a wide range of situations and interactions—like those encountered in the real world.

Today, we're announcing GWM-1—our first general world model family. GWM-1 is an autoregressive model built on top of Gen-4.5. It generates frame by frame, runs in real time, and can be controlled interactively with actions—camera pose, robot commands, audio.

GWM-1 comes in three variants: GWM Worlds for explorable environments, GWM Avatars for conversational characters, and GWM Robotics for robotic manipulation. Today, these are separate post-trained models. We're working toward unifying many different domains and action spaces under a single base world model.

We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won't solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world. World models offer the most clear path to general-purpose simulation.

Explore what GWM-1 can do

GWM Robotics brings a state-of-the-art video generation diffusion backbone to robotics — trained at the same scale and with the same large-scale pretraining as our frontier creative models.

Built on top of our frontier video generation model, GWM Robotics gives robot policy models a rich visual understanding of the physical world — enabling better generalization and greater sample efficiency out of the box.

And as a simulator, the model predicts video rollouts conditioned on robot actions, and supports counterfactual generation — letting you explore alternative trajectories and outcomes without ever touching physical hardware.

Use GWM Robotics as a video-generation diffusion backbone for your robot policies. The model's large-scale pretraining provides a powerful representation of the physical world, enabling your policies to generalize across tasks, environments, and embodiments with greater sample efficiency.

Synthetic data augmentation for policy training

Use the world model to generate synthetic training data that augments your existing robotics datasets across multiple dimensions, including novel objects, task instructions, and environmental variations. This synthetic data improves the generalization capabilities and robustness of your trained policies without requiring expensive real-world data collection.

Policy evaluation in simulation

Test the performance of your policy models (such as VLA models like OpenVLA or OpenPi) directly within Runway's world model instead of deploying to physical robots. This approach is faster, more reproducible, and significantly safer than real-world testing while still providing realistic behavioral assessments.

Gen-4.5

GWM-1 Robotics SDK

A Python SDK for Runway's robotics world model API that enables action-conditioned video generation using models trained on robotics data. The SDK supports multi-view video generation and long-context sequences, with an interface designed for seamless integration into modern robotic policy models.

GWM-1 Robotics SDK

A new frontier for open-ended interactive world simulation. A way of building infinite explorable realities in real-time.

Use cases

Gaming

Education

Training Agents

VR and Immersive Experiences

GWM Worlds enables players to move freely through coherent, reactive worlds without the need to manually design every space.

GWM Worlds is a world model for real-time environment simulation. You give the model a static scene, and it generates an immersive, infinite, explorable space as you move through it, with geometry, lighting, physics. All in real time. You can travel to any place, real or imagined. You can become any agent, a person walking through a city, a drone flying over a snowy mountain, a robot navigating a warehouse. What makes this work is consistency. When you explore an environment, you expect the world to stay coherent. Turn around, and what was behind you is still there. Walk forward and back, and you return to where you started. GWM Worlds maintains this spatial consistency across long sequences of movement. And because it's a simulation, the environment can react. You can define the physics of a world with your input prompt, and the world will respond accurately. If you prompt the agent to ride a bike, it stays on the ground; if you prompt for flight, it can freely navigate the sky. This is useful for interactive experiences, games, explorable worlds, immersive environments. But it's equally important for training agents. If you want to train an AI system to navigate and act in the physical world, you need a simulator in which to teach it. GWM Worlds can serve as that sandbox, an environment where agents can explore, make mistakes and learn.

Runway Characters is an audio-driven interactive video generation model that simulates natural human motion and expression for arbitrary photorealistic or stylized characters. The model renders realistic facial expressions, eye movements, lip-syncing and gestures during both speaking and listening, running for extended conversations without quality degradation.

Use cases

Real-time tutoring and education

Customer support and service

Training simulations

Interactive entertainment and gaming

Bring personalized tutors to life. Responsive characters that explain concepts, react to questions, and hold extended conversations with the natural expressions and gestures that make learning feel like a real dialogue.

Runway Characters is now available via the Runway API and Runway web product.

Avatars Hero

Gen-4.5 now supports native audio generation and native audio editing. Not only will you be able to generate novel videos with audio, but you'll also be able to edit the audio of existing videos to suit your needs. Gen-4.5 also introduces multi-shot editing. With multi-shot editing, you can make a change in your initial scene and propagate that change throughout your entire video.

Native Audio

Gen-4.5 can generate realistic dialogue compelling sound effects and immersive background audio, transforming the kinds of stories you can create with the model.

Audio Editing

Gen-4.5 has now the ability to edit the audio of existing videos to suit your needs in any particular way you want.

Multi-shot video editing

Gen-4.5 has the ability to edit videos of arbitrary length applying consistent transformations across multiple shots of arbitrary duration.

Change the background of the video to a jungle.

Change the skunk to a baby elephant.

Change the color of his eyes to red.

New Gen-4.5 capabilities are coming soon to the Runway web product.

Fill out this form to request GWM-1 early access