Video diffusion models have crossed the hard threshold of "real-time playability". WanToFight, posted to arXiv 2607.12592, is the first to simultaneously pack the four hard challenges of a generative game engine — multi-player control, real-time inference, complex physical interaction, adversarial play — into a single system. Its base is Alibaba's open-source Wan-1.3B video diffusion Transformer; the authors (Li Hu, Guangyuan Wang, Peng Zhang, Bang Zhang) build a three-layer incremental architecture on top, turning "painting by frame" into "input-triggered move". The first layer is a streaming autoregressive generator, with block-causal attention + rolling KV cache as the core, slicing global denoising into causal blocks with constant memory usage — long sequences no longer blow up. The second layer is the Player Association module: keyboard signals are first visually grounded to character identity, then routed back into the denoising network through a gated, locally causal injection module, avoiding the control signal contaminating the shared representation; training uses a progressive curriculum from single-player to all-gameplay, learning single-player first then adversarial play. The third layer is an engineering distillation stack: a four-step DMD-distilled student model + a pruned VAE decoder, compressing end-to-end latency to 512×384@30FPS on a single RTX 5090 — enough to last a full round of KOF'97. Zooming out, the real meaning of WanToFight is not "another stronger model", but the engineering paradigm it demonstrates: 1.3B scale + consumer single-card + the three-piece set of distillation + KV cache + pruned VAE, video diffusion models can now step out of the "bill by the second" cloud pipeline and into a real-time interactive loop. This forms a clear fork from the single-player / first-person paths of GameNGen, DIAMOND, and Oasis — multi-player adversarial scenarios have higher visual-consistency and causal-preservation difficulty, and WanToFight is the first to provide an empirical answer. Of course, 512×384 resolution, single-card dependency, and the relatively simplified discrete action space of fighting moves all mean there's still considerable distance to "true 3A real-time generation". But the direction is clear: the next phase of video diffusion won't be about who has more parameters, but who first folds generation into a 30FPS interactive loop.