Enterprise AI Analysis

Visual Trace Reasoning

Takeaway 2: Veo-3 can produce locally coherent, short-horizon trace animations in simple, low-branching scenarios, but it does not reliably execute long-horizon plans or rule-grounded sequences.

Enterprise Application: Suitable for short-sequence process visualization, but requires human oversight for multi-step or rule-based workflows.

Real-world Spatial Reasoning

Takeaway 3: While Veo-3 exhibits an emerging ability for simple real-world spatial reasoning, its capability remains insufficient for handling more complex spatial understanding tasks.

Enterprise Application: Can assist with basic scene understanding, but struggles with advanced 3D interpretation, perspective changes, or depth reasoning critical for robotics or complex simulations.

3D Geometry Reasoning

Takeaway 4: Veo-3 exhibits emerging reasoning potential on basic 3D transformations but breaks down on complex or multi-step geometry, often yielding misaligned or self-intersecting structures.

Takeaway 5: 3D geometric reasoning remains fragile, revealing substantial gaps in its ability to function as a reliable 3D geometry reasoner.

Enterprise Application: Limited to very basic 3D visualization; not suitable for precise CAD, engineering, or detailed structural analysis.

2D Geometry Reasoning

Takeaway 6: Veo-3 shows initial 2D geometric reasoning ability but still falls short of consistent, constraint-aware geometric understanding, remaining far from a robust geometric reasoner.

Enterprise Application: Can generate simple 2D illustrations but lacks the precision and constraint adherence for design, drafting, or any task requiring accurate geometric manipulation.

Physics-based Reasoning

Takeaway 7: Veo-3 often generates visually plausible short-term dynamics, but it systematically fails to preserve quantitative physical constraints (energy, momentum), causal ordering, and contact mechanics in frictional, force-driven, or mechanically constrained scenarios.

Enterprise Application: Outputs are useful for qualitative illustration but are not reliable for quantitative physics inference or causal prediction in fields like engineering or simulation.

Rotation Reasoning

Takeaway 8: Veo-3 exhibits only a superficial understanding of rotation reasoning. While it can approximate small planar rotations, it fails to preserve geometric consistency under larger or compound transformations.

Enterprise Application: Can assist with simple 2D object rotation for visual tasks, but not reliable for tasks requiring precise angular control or 3D rotational understanding.

Table and Chart Reasoning

Takeaway 9: Veo-3 demonstrates emerging competence and potential in structured visual understanding, but still falls short of functioning as a precise and reliable chart-table reasoner.

Enterprise Application: Can highlight general areas of interest in charts/tables, but lacks the precision for accurate data extraction, analysis, or automated reporting.

Object Counting Reasoning

Takeaway 10: Veo-3 demonstrates basic counting capability but lacks the spatial control and robustness required for reliable object enumeration in dynamic or complex scenes.

Enterprise Application: Suitable for very simple, clear counting tasks, but unsuitable for automated inventory, quality control, or surveillance where precision and robustness are critical.

GUI Reasoning

Takeaway 11: Veo-3 demonstrates a limited awareness of GUI click actions, imitating interaction behaviors without fully grasping the underlying functional logic.

Enterprise Application: Can simulate basic GUI interactions for demonstration purposes, but not reliable for automated UI testing, robotic process automation (RPA), or agentic control.

Embodied Reasoning

Takeaway 12: Veo-3's capabilities are currently limited to basic object recognition rather than true embodied reasoning. It lacks the necessary planning and stability to reliably interpret and act upon dynamic or spatially constrained instructions, indicating its limitations in understanding and reasoning of real-world interactions.

Enterprise Application: Can generate plausible object manipulations in simple contexts, but lacks the planning depth and reliability for advanced robotics, interactive simulations, or training physical agents.

Medical Reasoning

Takeaway 13: Veo-3's failure to handle the reasoning in the medical domain, causing distortion even on simple zoom-ins, highlights its limited grasp of specialized, non-general knowledge.

Enterprise Application: Currently unsuitable for medical image analysis, diagnosis support, or any clinical application due to lack of domain knowledge and propensity for distortion.