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Video GenerationLatent SpacePublished: Sep 25, 2026, 13:00 JST

Runway's GWM Worlds 2 lets you prompt real-time worlds

Runway's GWM Worlds 2 lets you prompt real-time worlds

3 Key Points

  1. What happened

    Runway released GWM Worlds 2, a research preview that turns video and audio generation into real-time interactive simulation, featuring WorldPrompt for setting the first frame and adding timestamped actions in real time.

  2. Why it matters

    Runway is reportedly valued at $5.3 billion after a $315 million fund raise in February, and WorldPrompt helps differentiate it from Google DeepMind's Genie 3, Odyssey-2 Pro, and World Labs' RTFM.

  3. What to watch

    CTO Kamil Sindi says more training plus scaling data and models is resulting in better following, but the research preview has flaws and long-term memory remains an open research problem.

WHO IT HITSGame developers and robotics engineers could use GWM Worlds 2 to create interactive environments on demand, with Kahlow noting that having thousands of simulated environments is much less challenging for testing agents at scale.

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Context & Analysis

Runway's path to GWM Worlds 2 did not start with worlds at all. The company began as a way to make open-source models usable for artists, then spent its early years on a segmentation tool called Green Screen that was used in Everything Everywhere All at Once. The pivot to generative video came in 2022, when Runway signed a deal for a cluster of a thousand A100s and released Gen-1 in January 2023.

The engineering challenges behind real-time worlds are substantial. Kahlow described two: making the model generate frame by frame rather than a whole clip at once, and making generation fast enough to play in real time. Runway addressed this by fine-tuning its foundational audio-video model, post-training for autoregressive generation, and using distillation methods. Germanidis said a model might go from around 50 denoising steps to four, with some quality loss but potentially comparable results.

Whether GWM Worlds 2 becomes more than a research preview hinges on several open problems. Error accumulation in autoregressive models, managing GPU memory during infinite generations, and the lack of perfect memory are all acknowledged by the Runway team. The harder test may be counterfactual generation: Germanidis noted that football training data contains more successful goals than failed attempts, so the model might render success more convincingly. Until that gap closes, the fully self-generated, real-time games that world models promise will likely remain a goal rather than a product.

FAQ
What is WorldPrompt and how does it work?
WorldPrompt is a proposed input format for specifying a generated world and the actions within it. It lets you fix some aspects of a simulated environment, including the first frame, and then create a series of timestamped events that can be prompted in real time.
What are the current limitations of GWM Worlds 2?
Kahlow said it's a research preview and "not perfect," with reliability depending on how difficult the action is; movement works quite reliably. The model also does not have perfect memory, which Kahlow called an open research problem.
What can you use GWM Worlds 2 for?
Gaming is the obvious use case, but Kahlow also mentioned robotics to test how a robot works and testing agents at scale. Sindi noted it can also be used for synthetic data generation for agents.

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