In the booming era of AI video generation, we are witnessing history almost every month. Judging by the recent buzz around Kling 2.6, Wan 2.6, and Sora 2, the field of video generation has entered a white-hot "frame-level war." In this race, there is a name that entered early but has remained relatively quiet—Google's Veo.
As people have grown accustomed to referring to its iterations as "Veo 1.0" and "Veo 2.0," industry observers have begun anticipating the version that could reshape the landscape: Veo 4.0. Behind this unannounced naming lies the full expectation that Google will regain dominance in video generation.
Its key strengths lie in physics-level realistic world simulation, immersive audio-visual integrated experience, and an efficient, low-cost creative process. Through a groundbreaking physics engine, it accurately simulates Newtonian mechanics and fluid dynamics, perfectly replicating Olympic-level gymnastics movements and complex object dynamics. It pioneered the "soundscape pre-training + dynamic alignment" mechanism, synchronously generating multilingual dialogue and environmental sound effects with a lip-sync accuracy of 91.3%. Supporting 120-second coherent multi-shot storytelling, characters and scenes remain consistent across shot transitions. Meanwhile, it shortens the content production cycle from "month-level" to "minute-level" and reduces costs by over 95%, completely breaking professional creation barriers and enabling everyone to become a video creator.
The newly released Kling 2.6 brings two key advantages: first, the ability to generate videos up to 3 minutes long, far exceeding the duration limits of most current models; second, the introduction of more refined dynamic control and camera movement editing functions. Users can more directly control shot movement, character actions, and scene transitions, opening up new possibilities for professional-level content creation.
Wan 2.6 has made significant progress in the accuracy of physical simulation and micro-detail performance. Its reproduction of fluid mechanics, light and shadow interaction, and material textures is outstanding in specific test scenarios. For application scenarios pursuing physical authenticity and perfect details, Wan 2.6 has become a powerful choice.
Facing the three-way encirclement, Google Veo 's new model (speculated to be Veo 4.0) will inevitably focus on "addressing shortcomings and expanding advantages." Based on Veo 3.1's technical foundation, the predicted upgrade directions are as follows:
Resolution will jump from 1080p to 4K, and frame rate will increase to 60fps, catching up to Sora 2's image quality benchmark;
Optimize the hierarchical diffusion model architecture, with keyframe generator parameters possibly increasing from 12 billion to 200-billion scale. Meanwhile, introduce Kling-style "draft/high-definition" dual modes to balance speed and quality.
Add 16-bit HDR export and EXR format support to enter the film and television post-production market, competing against Kling 2.6's professional advantages;
Upgrade the V2A audio synthesis engine (currently 9 billion parameters) to enhance synchronized physical sound effects (such as distinguishing material characteristics of object collision sounds and environmental sounds), addressing Sora 2's shortcomings in physical simulation.
The scene extension function will be upgraded from 148 seconds to over 3 minutes, solving the character consistency issue through optimized spatiotemporal interpolation algorithms;
Refer to Kling 2.6's multi-image reference mechanism, supporting the import of up to 5 reference images to ensure consistent characters and scene styles across segments.
May partially open model weights to attract adeveloper ecosystems, competing against Wan 2.6's open-source advantages;
Launch industry-specific customized versions (such as exclusive models for advertising and education), leveraging Veo 3.1's enterprise-level deployment experience on Vertex AI to strengthen competitiveness in the B2B market.
The launch of Veo's new model marks that competition has evolved from a contest of single functional points to a comprehensive contest involving system architecture, creative paradigms, and even ecological construction.
Innovation driven by such top-tier pressure will accelerate:
Technological Democratization: Top-tier capabilities (such as long videos and strong consistency) will quickly become industry standards.
Application Explosion: Rapidly move from proof-of-concept to large-scale practical scenarios such as film and television previsualization, personalized content generation, and dynamic interactive experiences.
Role Reconstruction: AI will evolve from a "generation tool" to a creative partner with certain "world simulation" and "narrative collaboration" capabilities.
For Veo, the launch of the new model is not only an unprecedented pressure but also an excellent opportunity to clarify directions and achieve a leap forward. Its next appearance will be more than just a version update; it will be a direct answer to the core question of "how to define the next generation of AI video models." Regardless of the answer, this technological leap driven by top-tier competitive pressure will ultimately push the entire field toward a new era that is more powerful, controllable, and creative.
The future of video generation is being written at a competitive pace, and the new chapter of Veo is worth waiting for with bated breath.