When Google unveils a new innovation, tech enthusiasts everywhere can’t help but feel a tinge of excitement tinged with curiosity. The latest in this roster is Gemini 3, a model hailed as probably the best on earth, launched on November 18, 2025, as detailed by Matthew Berman on his YouTube channel. What makes this model stand out? For starters, its exceptional benchmarks that put earlier models in the shade. For instance, on Humanity’s last exam, it scored an impressive 37.5% without external tools, and dramatically rose to 45.8% with code execution and search functions. Meanwhile, Gemini 2.5 Pro lagged behind at 21%. This displays a quantum leap in AI capabilities, confirming the tussle for supremacy in AI innovation is far from over.
Google’s strategic integration of Gemini 3 across its products isn’t merely a future possibility; it’s a current reality. Product renditions like Gemini 3 Pro Preview and Gemini 3 Deep Think are meticulously designed to cater to varied computational needs. While Gemini 3 Deep Think pushes the boundaries with advanced reasoning—as observed when it scored highest in visual reasoning puzzles—it also supports multiple modalities including text, image, and notably, video comprehension. This sophisticated feature allows the model not only to understand the video’s transcript but to analyze it frame by frame, transforming how digital media can be interpreted by AI.
Another standout feature is Gemini 3’s incorporation into Box.com’s platform, where its prowess in multifaceted reasoning truly shines. Gemini 3’s stellar performance in complex multi-step logic and document extraction tasks, benchmarked by Box, underscores its immense potential in enhancing enterprise functionality. It demonstrates a noticeable leap from 63% to 85% in Box’s evaluation, solidifying its role in sectors like healthcare and finance. Beyond a simple AI tool, Gemini 3 emerges as a pivotal component in navigating complex data landscapes in real-time business operations.
However, all that glitter is not gold. Despite its virtues, areas like the SWEBench verified ranking show room for improvement, where it plays second fiddle to Claude Sonnet 4.5. Moreover, it raises questions about whether an over-reliance on benchmark performance might overshadow nuanced real-world applications that demand more than numerical box-ticking.
Moreover, Google’s strategic introduction of the Gemini agent exhibits a leap toward increased AI autonomy. The ability for this agent to conduct tasks such as organizing email contents autonomously indicates a push towards integrating AI into personal and business day-to-day chores. Dynamic user interfaces that generate based on user queries within Google Search further enhance its practical usability and contextual relevance. This correlation with VS Code fork ‘Anti-gravity’, a new coding platform, showcases Google’s diversifying avenues in AI synergy.
Kudos to Google for pushing the envelope with their custom TPU architecture, sparking both admiration and curiosity about future hardware innovations. Yet, growth comes with an inherent challenge: ensuring equitable access and understanding of such technology by a broad audience—to prevent it becoming an elitist tool reserved for only those who can afford or fully comprehend its intricacies.
In Matthew Berman’s enlightening presentation, Gemini 3 shines as a spectacular advancement in AI, casting its predecessors into relative obscurity while raising questions about the ethical paths AI might take. Perhaps as we embark on this AI revolution, how we choose to harness these advancements will define not just corporate profits, but the broader lens of human interaction with AI.