Gemini 3's "Key Leap" -- A "Major Breakthrough" Driving the Implementation of AI Applications?

Core Insights Gemini 3 released, model capabilities have made comprehensive breakthroughs. Google has recently launched the Gemini 3 series models, Nano Banana Pro image model, and the newly developed platform Antigravity, marking a comprehensive leap in multimodal understanding, reasoning, and agent capabilities. 1) Gemini 3 Pro's multimodal understanding capabilities, especially its Screen Understanding ability, have reached the top; reasoning and long-term planning capabilities have significantly improved, performing best in the Vending-Bench 2 long-term task test; Deep Think mode has broken through AGI-related reasoning: ARC-AGI evaluation reached 45.1%; Agentic capabilities: enhanced programming and tool usage abilities, more reliably executing multi-step tasks. 2) Nano Banana Pro: capable of image generation with physical logic, perfectly addressing the pain point of text rendering errors in image generation, integrating with real-world knowledge, and supporting professional visual content production. 3) Antigravity: Smart Workbench: provides an AI-driven IDE and multi-agent management interface, with agents having dedicated workspaces. Screen Understanding is the key to this leap. We believe that the significant improvement in Gemini 3's multimodal understanding capabilities, especially its Screen Understanding ability, is a key breakthrough driving the implementation of AI applications. Gemini 3 Pro significantly outperforms Claude Sonnet 4.5 and GPT 5.1 in the ScreenShot-Pro evaluation benchmark. Gemini 3 Pro can accurately interpret structured/unstructured documents, which is significant for scenarios such as invoices, contracts, and research documents. Screen Understanding has milestone significance for the further development of AI: (1) Directly operating GUI through screen understanding without relying on APIs. This means AI can operate software without APIs, and agents can truly execute human workflows that involve looking at screens and clicking buttons, greatly expanding automation scenarios. (2) A bridge to physical robot capabilities: the model learns to understand buttons on screens and click them, which is highly isomorphic to how robots understand the world and act, allowing for natural migration in the future to robots recognizing and operating device panels, instruments, and tool interfaces. Prospects for Custom Agents, personal work and life assistants for everyone. The rapid iteration of large models and the continuous enhancement of reasoning and tool invocation capabilities have given rise to increasingly strong prospects for custom agent applications. For financial institutions, especially secondary buy-side and sell-side firms, we foresee exploring the following directions in the future: 1) Building personal investment research knowledge bases to support data retrieval, analysis, and report sharing; 2) Creating intelligent mass messaging assistants to achieve differentiated mass messaging with salutations and subsequent automated reply loops; 3) Utilizing agents to organize massive amounts of information from WeChat messages, research reports, public accounts, etc., and extract key points according to personalized rules; 4) Personalized research assistants, specifying the output style of large models, such as requiring authoritative information sources during analysis; 5) Creating practical tools like data analysis, compliance documentation assistants, and reimbursement assistants through simple conversations leveraging AI programming capabilities; 6) A lifestyle assistant similar to Meituan's "Xiao Mei," while also integrating with competing platforms to achieve various life service integrations. Report Body 01 Gemini 3 Released, Comprehensive Breakthrough in Model Capabilities Google has recently launched its flagship model Gemini 3 series, the image model Nano Banana Pro, and the innovative development platform Antigravity. We believe this marks a key leap in the capabilities of large models. These releases not only set new benchmarks in multimodal understanding and reasoning capabilities but also demonstrate significant potential for future applications in Agent and robotics technology: Gemini 3 Pro: Multimodal Reasoning and Outstanding Agent Capabilities The core breakthroughs of Gemini 3 Pro are reflected in several aspects: World-leading multimodal understanding: The model can process and understand data across various modalities, including text, images, videos, audio, and even code, and reason between these complex data types with unprecedented detail. Gemini 3 Pro performs exceptionally well in the Screen UnderStanding task, scoring 72.7% on the ScreenShot-Pro evaluation benchmark, significantly ahead of Claude Sonnet 4.5 (36.2%) and GPT 5.1 (3.5%). Outstanding reasoning and planning capabilities: Since the launch of Gemini 2, which initiated the Agent era, Google has made significant progress, enhancing Gemini's coding agent capabilities and improving its reliable planning abilities over longer time spans. Gemini 3's top performance on Vending-Bench 2 proves this point, as the test assesses long-term planning capabilities by managing a simulated vending machine business. Gemini 3 Pro maintained consistent tool usage and decision-making abilities throughout a full year of simulated operations, yielding higher returns without deviating from the task: The Gemini 3 Deep Think mode further pushes the boundaries of intelligence. In testing, Gemini 3 Deep Think scored 41.0% on Humanity’s Last Exam (without using tools) and 93.8% on GPQA Diamond, even surpassing the already impressive results of Gemini 3 Pro. It also achieved an unprecedented 45.1% on ARC-AGI (including code execution, ARC Prize Verified), demonstrating its ability to tackle novel challenges Enhanced Agent Capabilities: Gemini 3 brings exceptional command execution abilities, significantly improving tool usage and intelligent coding. More efficient tool usage: executing multi-step tasks simultaneously. The agent capabilities of Gemini 3 can build more practical and intelligent personal AI assistants. Nano Banana Pro (Gemini 3 Pro Image): The Logic and Physics of the Visual World Physical Perception Reasoning: According to the official website of the video generation platform Higgsfield, Nano Banana Pro goes beyond simple diffusion models. It plans scenes before rendering field quantities, providing native 2K resolution, physically accurate lighting, and perfect text rendering. Generating Clear Text: Nano Banana Pro addresses a major pain point in image generation—text errors. Clear and readable text aids in creating posters, complex charts, and detailed product models. Users can describe the desired font type or simulate different handwriting styles. Understanding Knowledge of the Real World: Utilizing the Gemini model's understanding of the real world and powerful reasoning capabilities, Nano Banana Pro can generate precise, detailed, and rich image results. It can annotate images, convert data into infographics, or transform handwritten notes into charts: Antigravity: A New Intelligent Development Platform If Gemini 3 is the "brain," Antigravity is the "workbench" that allows the brain to use its hands and feet. The original intention of Antigravity's development is that agents should not just be chatbots in a sidebar; they should have their own dedicated workspace. The platform offers two unique ways to interact with code: Editor View: When users need to take hands-on action, they will receive a state-of-the-art, AI-driven IDE equipped with tab key auto-completion and inline commands to support the synchronous workflows users are already familiar with. Management Interface: This is a dedicated interface where users can create, coordinate, and observe multiple agents working asynchronously in different workspaces. 02 Screen Understanding is the key to this leap We believe that the significant improvement in Gemini 3's multimodal understanding capabilities, especially its Screen Understanding ability, is a key breakthrough driving the implementation of AI applications. Gemini 3 Pro significantly outperforms Claude Sonnet 4.5 and GPT 5.1 in the ScreenShot-Pro evaluation benchmark. According to Squared, Gemini 3 Pro excels in document understanding. It can clearly read and interpret both structured and unstructured content, and can reason about documents rather than just extracting information. We believe this is a significant advantage for companies dealing with invoices, contracts, and data research. In the demonstration example, the model converts images into an interactive web experience. Before generating functional code, Gemini 3 Pro analyzes objects, layouts, and meanings. This level of transformation marks a shift in how AI participates in interface design and functional development. The enhancement of spatial reasoning capabilities enables the model to support tasks in autonomous vehicles, robotics, augmented reality hardware, and smart device systems. Gemini 3 Pro can predict trajectories, recognize object relationships, and analyze task progress. We believe this lays the foundation for the next generation of automation solutions. The model's screen understanding capabilities demonstrate exceptional performance on both desktop and mobile systems. It can read interface elements, detect user intent through mouse movements, and translate annotations into actions. Demonstrations show that AI can execute tasks based on simple hand-drawn instructions. This marks a significant shift in how users interact with digital environments. Video reasoning further expands these capabilities. Gemini 3 Pro can handle fast motion, identify key events, and maintain contextual relevance in long video footage. This helps developers generate detailed summaries, extract key frames, and build video analysis agents. This feature is crucial for monitoring analysis, sports analysis, training systems, and creative video production. The significant implications of Screen Understanding for the further implementation of future AI applications include: 1. Breaking down the barriers of API openness for Agent interaction with the digital world: We believe that using tools through API calls (Function Calling) is limited by the openness of software interfaces. Models with Screen Understanding can directly operate any graphical user interface (GUI) designed for humans. This means Agents can operate tools without APIs, greatly expanding the various application scenarios for AI AI can officially evolve from an auxiliary tool to a digital employee. It no longer requires humans to translate tasks into code, but instead operates directly like human employees, looking at the screen, operating software, and completing work. 2. A Bridge to Physical World Robots: We believe that the screen is essentially a high-dimensional, dynamic visual environment. The perception-decision-action loop required for models to "understand buttons on the screen and click" is highly isomorphic to the underlying logic of robots "understanding cups on the table and grabbing them." Moreover, for physical robots, this capability can extend to recognizing and operating real-world environments (such as control panels, device gauges, and complex tool interfaces). 03 Custom Agent Outlook, Everyone's Personal Work and Life Assistant Current large models are continuously iterating, with reasoning capabilities and tool usage abilities constantly upgrading. The capabilities of Agents created based on large models are becoming increasingly powerful. As professionals in financial institutions, we envision the following potential custom Agents that could be created using large models, especially applications that may be more practical for secondary buy-side and sell-side professionals: 1. Personal Investment Research Knowledge Base Many current large models or native AI applications already possess knowledge base capabilities. For example, Tencent's work assistant ima can easily save personal data and subsequently conduct Q&A. We envision that in the future, for professionals in financial institutions, core materials such as daily accumulated research minutes on listed companies, records of industry expert interviews, and insights from internal strategy meetings can be imported into a knowledge base, with the Agent assisting in information retrieval and analysis. In collaborative scenarios, researchers do not need to transfer massive files; they only need to grant colleagues access to specific topic retrieval permissions (such as "shared policy interpretation materials for the semiconductor industry"), and can track the citation trail and feedback through the Agent. When reporting to clients, the Agent can quickly aggregate relevant research findings based on the reporting theme, automatically generating data-supported summary viewpoints, significantly reducing material preparation time. 2. Smarter Mass Messaging Assistant Currently, WeChat has a mass messaging function. We envision that in the future, if WeChat can analyze chat records for each friend with user permission, it could achieve more intelligent mass messaging, such as automatically adding differentiated greetings and attaching opening remarks that align with the recipient's interests. Furthermore, the Agent may achieve a closed-loop process of intelligent replies after mass messaging: upon receiving immediate inquiries from clients, it can automatically extract the core of the question, analyze the mass messaging content, and generate preliminary replies based on its personal knowledge base. 3. Organizing Massive Information like WeChat Messages For many professions, such as financial practitioners, if there is an overload of information from WeChat messages, emails, and other content, information overload becomes a core pain point affecting decision-making efficiency. We envision that user-defined Agents can quickly distill key points using large models. There are already cases in the Tencent Cloud Developer Community where AI has transformed WeChat chat records into visual reports In addition, other information such as daily updated brokerage research reports and followed public accounts can also be summarized using AI. Practitioners can preset personalized extraction rules for the Agent: for example, setting priorities to extract AI-related information; for multiple research reports, implementing frequency statistics for recommended targets, etc. 4. Personalized Work Assistant Many large models can now save custom personalized settings without needing to adjust requirements in each new conversation, such as ChatGPT. For example, when used as an investment research assistant Agent, one can request the large model to output answers in a specific style, and any answers that reference online materials automatically provide authoritative source links. 5. AI Programming for Data Analysis Code Creation For some clearly defined tasks such as data analysis and chart visualization, using code to build a workflow can significantly reduce repetitive workload. For users lacking professional programming skills, the programming capabilities of large models can effectively fill this gap, allowing practical tools to be created through simple dialogues. For instance, when there is a need to create a draft for brokerage research reports, one can write the document while simultaneously inputting the draft content into Word comments, and then use code to extract the comment content to generate the draft file. For jobs that frequently require submitting complex reimbursement materials, if various ticket booking applications open their interfaces in the future, a reimbursement assistant that aligns with the company's processes can also be created. 6. Life Assistant Recently, Meituan has begun testing its life assistant "Xiao Mei." Functions include ordering food, etc. We believe that many companies involved in e-commerce and local life will launch similar products in the future, but these AI assistants are expected to generally only connect with their internal applications, for example, "Xiao Mei" will call upon Meituan during service. Ideally, users should be able to customize an Agent that suits their preferences and can query and compare different competing applications, such as checking takeout options across Meituan, Taobao, JD.com, etc. Risk Warning and Disclaimer The market has risks, and investment requires caution. This article does not constitute personal investment advice and does not consider individual users' specific investment goals, financial situations, or needs. Users should consider whether any opinions, views, or conclusions in this article align with their specific circumstances. Investment based on this is at one's own risk