Core Insights - Google has officially launched its latest foundational model, Gemini 3, which shows significant improvements in deep reasoning, multimodal understanding, and agent programming capabilities [1] - Gemini 3 Pro achieved a new state-of-the-art (SOTA) score of 71.6 on the xbench-ScienceQA leaderboard, surpassing Grok-4 and demonstrating faster response times and lower costs [1][3] Performance Metrics - Gemini 3 Pro scored an average of 71.6 with a BoN of 85, while Grok-4 scored 65.6, indicating a 6-point lead over the second-place model [5] - The average response time for Gemini 3 Pro is 48.62 seconds, significantly faster than Grok-4's 227.24 seconds and GPT-5.1's 149.91 seconds [6] - Cost analysis shows that running the ScienceQA tasks with Gemini 3 Pro costs only $3, compared to $32 for GPT-5.1, making it substantially more economical [6] Technological Advancements - Gemini 3 introduces a cognitive architecture that shifts from reactive to cautious reasoning, utilizing a "Deep Think" mode that allows for multiple reasoning pathways and self-verification [8] - The model employs a sparse MoE architecture, activating only a small subset of its vast parameters during computation, which enhances efficiency while maintaining performance [8] Developer Tools and Features - The introduction of "Vibe Coding" allows Gemini 3 to align code generation with developer intent, functioning as an autonomous agent capable of executing complex tasks within an IDE [9] - Gemini 3 Pro integrates with Google’s Antigravity platform, enabling developers to automate workflows that involve reading web pages, executing commands, and generating code seamlessly [10] Multimodal Capabilities - Gemini 3 adopts a native multimodal architecture, allowing it to process text, code, images, video, and audio using a unified world model, enhancing its perception and interaction capabilities [11] - The model can generate dynamic, interactive user interfaces in real-time based on user intent, marking a shift from static outputs to interactive experiences [12] Hardware Infrastructure - Gemini 3 is trained on Google’s proprietary TPU (Tensor Processing Unit), designed for high-bandwidth and parallel computing, facilitating efficient training and cost management [13]