On July 15, Tsinghua-spinout Xmax AI released its general-purpose real-time interactive AI video model Xmax X2.0 and simultaneously opened its API. Unlike cloud-only real-time routes such as Vidu S1 and Alibaba's Wan-Streamer, X2.0 puts real-time and on-device into the same model weights. The core technology is a per-frame autoregressive generation architecture — traditional diffusion models need to wait for the entire segment to finish before delivering, but X2.0 instead pushes each generated frame to the front end immediately, splitting batch rendering into streaming output. Combined with inference optimization and model compression, response is compressed to near-zero millisecond-level latency, and resolution goes from the X1's 480p to 960p@24fps, with latency and image quality moving in opposite directions at the same time. On the feature side, X2.0 integrates CharX real-time face swap, ClothX real-time clothing swap, VibeX style transfer, and MoX touch-screen interaction into a unified architecture, with camera movement, gestures, and prompts all acting as control signals. More noteworthy is the on-device landing. X2.0 has already run 384@16fps local streaming inference on the latest iPhone, and runs stably on consumer-grade GPUs. Real-time interactive video has advanced from a capability that requires data-center GPU clusters to a tool readily available on phones and smart glasses. This fills in the key low-latency, on-device-deployable piece for travel-and-tourism digital guides, e-commerce real-time try-on, short-drama interactivity, and AR filters. But X2.0 leans more toward application and engineering rather than frontier architectural breakthrough: per-frame autoregression isn't a new paradigm — what really tests its long-term value is on-device image quality and consistency, and SDK stability in production. Whether this path can hold depends on real-world feedback in subsequent business scenarios.