Matrix-Game 3.0: Real-Time and Streaming Interactive World Model with Long-Horizon Memory

• URL: http://arxiv.org/abs/2604.08995v2
• Date: Mon, 13 Apr 2026 03:48:38 GMT
• Title: Matrix-Game 3.0: Real-Time and Streaming Interactive World Model with Long-Horizon Memory
• Abstract summary: Matrix-Game 3.0 is a memory-augmented interactive world model designed for 720p real-time longform video generation.<n>We introduce systematic improvements across data, model, and inference.<n> Experimental results show that Matrix-Game 3.0 achieves up to 40 FPS real-time generation at 720p resolution with a 5B model.
• Score: 53.39687409541093
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: With the advancement of interactive video generation, diffusion models have increasingly demonstrated their potential as world models. However, existing approaches still struggle to simultaneously achieve memory-enabled long-term temporal consistency and high-resolution real-time generation, limiting their applicability in real-world scenarios. To address this, we present Matrix-Game 3.0, a memory-augmented interactive world model designed for 720p real-time longform video generation. Building upon Matrix-Game 2.0, we introduce systematic improvements across data, model, and inference. First, we develop an upgraded industrial-scale infinite data engine that integrates Unreal Engine-based synthetic data, large-scale automated collection from AAA games, and real-world video augmentation to produce high-quality Video-Pose-Action-Prompt quadruplet data at scale. Second, we propose a training framework for long-horizon consistency: by modeling prediction residuals and re-injecting imperfect generated frames during training, the base model learns self-correction; meanwhile, camera-aware memory retrieval and injection enable the base model to achieve long horizon spatiotemporal consistency. Third, we design a multi-segment autoregressive distillation strategy based on Distribution Matching Distillation (DMD), combined with model quantization and VAE decoder pruning, to achieve efficient real-time inference. Experimental results show that Matrix-Game 3.0 achieves up to 40 FPS real-time generation at 720p resolution with a 5B model, while maintaining stable memory consistency over minute-long sequences. Scaling up to a 2x14B model further improves generation quality, dynamics, and generalization. Our approach provides a practical pathway toward industrial-scale deployable world models.

Related papers

• Matrix-Game 3.5: Enhancing Real-Time Streaming Interactive World Models with Patch Memory [28.887112448832525]
  We present Matrix-Game 3.5, which advances real-time interactive world generation through three key improvements.<n>First, we propose a unified geometry-aware memory framework, whose patch-memory and tiled-PRoPE components introduce no additional learnable parameters.<n>Second, we introduce a static-dynamic disentangled world representation that separately models static scene geometry and dynamic subjects.<n>Third, we develop a two-stage progressive real-time distillation framework that converts a bidirectional diffusion model into a few-step causal generator.
  arXiv  Detail & Related papers  (2026-08-30T17:11:00Z)
• Unified 4D World Action Modeling from Video Priors with Asynchronous Denoising [22.899605451385824]
  We propose X-WAM, a Unified 4D World Model that unifies real-time robotic action execution and high-fidelity 4D world synthesis (video + 3D reconstruction) in a single framework.<n>To leverage the strong visual priors of pretrained video diffusion models, X-WAM imagines the future world by predicting multi-view RGB-D videos.<n>Asynchronous Noise Sampling (ANS) to jointly optimize generation quality and action decoding efficiency.
  arXiv  Detail & Related papers  (2026-04-29T14:01:54Z)
• InSpatio-WorldFM: An Open-Source Real-Time Generative Frame Model [17.421965971185134]
  We present InSpatio-WorldFM, an open-source real-time frame model for spatial intelligence.<n>InSpatio-WorldFM adopts a frame-based paradigm that generates each frame independently, enabling low-latency real-time spatial inference.
  arXiv  Detail & Related papers  (2026-03-12T13:28:50Z)
• RAYNOVA: Scale-Temporal Autoregressive World Modeling in Ray Space [51.441415833480505]
  RAYNOVA is a multiview world model for driving scenarios that employs a dual-causal autoregressive framework.<n>It constructs an isotropic-temporal representation across views, frames, and scales based on relative Plcker-ray positional encoding.
  arXiv  Detail & Related papers  (2026-02-24T08:41:40Z)
• Infinite-World: Scaling Interactive World Models to 1000-Frame Horizons via Pose-Free Hierarchical Memory [101.2076718776139]
  We propose a robust interactive world model capable of maintaining coherent visual memory over 1000+ frames in complex real-world environments.<n>We introduce a Pose-free Memory (HPMC) that distills historical latents into a fixed-budget geometric representation.<n>We also propose an Uncertainty-aware Action Labeling module that discretizes continuous motion into a tri-state logic.
  arXiv  Detail & Related papers  (2026-02-02T17:52:56Z)
• TeleWorld: Towards Dynamic Multimodal Synthesis with a 4D World Model [53.555353366322464]
  We present TeleWorld, a real-time multimodal 4D world modeling framework that unifies video generation, dynamic scene reconstruction, and long-term world memory within a closed-loop system.<n>Our approach achieves seamless integration of dynamic object modeling and static scene representation within a unified 4D framework, advancing world models toward practical, interactive, and computationally accessible synthesis systems.
  arXiv  Detail & Related papers  (2025-12-31T18:31:46Z)
• RELIC: Interactive Video World Model with Long-Horizon Memory [74.81433479334821]
  A truly interactive world model requires real-time long-horizon streaming, consistent spatial memory, and precise user control.<n>We present RELIC, a unified framework that tackles these three challenges altogether.<n>Given a single image and a text description, RELIC enables memory-aware, long-duration exploration of arbitrary scenes in real time.
  arXiv  Detail & Related papers  (2025-12-03T18:29:20Z)
• CVD-STORM: Cross-View Video Diffusion with Spatial-Temporal Reconstruction Model for Autonomous Driving [26.379817613036597]
  CVD-STORM is a cross-view video diffusion model utilizing a spatial-temporal reconstruction Variational Autoencoder (VAE)<n>Our approach first fine-tunes the VAE with an auxiliary 4D reconstruction task, enhancing its ability to encode 3D structures and temporal dynamics.<n> Experimental results demonstrate that our model achieves substantial improvements in both FID and FVD metrics.
  arXiv  Detail & Related papers  (2025-10-09T08:41:58Z)
• Matrix-Game 2.0: An Open-Source, Real-Time, and Streaming Interactive World Model [15.16063778402193]
  Matrix-Game 2.0 is an interactive world model generates long videos on-the-fly via few-step auto-regressive diffusion.<n>It can generate high-quality minute-level videos across diverse scenes at an ultra-fast speed of 25 FPS.
  arXiv  Detail & Related papers  (2025-08-18T15:28:53Z)
• RAVEN: Rethinking Adversarial Video Generation with Efficient Tri-plane Networks [93.18404922542702]
  We present a novel video generative model designed to address long-term spatial and temporal dependencies. Our approach incorporates a hybrid explicit-implicit tri-plane representation inspired by 3D-aware generative frameworks. Our model synthesizes high-fidelity video clips at a resolution of $256times256$ pixels, with durations extending to more than $5$ seconds at a frame rate of 30 fps.
  arXiv  Detail & Related papers  (2024-01-11T16:48:44Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.