Google I/O 2026 深度技术分析（增强版）：Agentic Gemini 时代的全面启动

xychart-beta
    title "Google 月 Token 处理量增长（2022-2026，单位：万亿）"
    x-axis ["2022", "2023", "2024-H2", "2025-H1", "2025-I/O", "2026-I/O"]
    y-axis "月处理 Token 量（万亿）" 0 --> 3500
    line [5, 30, 120, 250, 480, 3200]

graph TB
    subgraph "基础设施层 Infrastructure"
        TPU["TPU Ironwood<br/>第8代"]
        GCP["Google Cloud<br/>Agentic Data Cloud"]
        ENERGY["数据中心<br/>~3-4 GW 电力"]
    end

    subgraph "模型层 Models"
        FLASH["Gemini 3.5 Flash<br/>Agent/Coding 核心"]
        PRO["Gemini 3.5 Pro<br/>下月发布"]
        OMNI["Gemini Omni<br/>Any→Any 多模态"]
        VEO["Veo 3.1<br/>视频生成"]
        IMAGEN["Imagen 4<br/>文生图"]
        LYRIA["Lyria 2<br/>音乐生成"]
    end

    subgraph "Agent 基座 Agent Platform"
        AG["Antigravity 2.0<br/>Desktop/CLI/SDK"]
        MAA["Managed Agents API<br/>托管沙箱"]
        SPARK["Gemini Spark<br/>24/7 个人 Agent"]
        FIREBASE["Firebase<br/>开发全链路"]
    end

    subgraph "消费入口 Consumer"
        SEARCH["Search<br/>AI Mode 10亿+ MAU"]
        GEMINI_APP["Gemini App<br/>9亿+ MAU"]
        ANDROID["Android 17<br/>Gemini Intelligence"]
        WORKSPACE["Workspace<br/>企业 AI 层"]
    end

    subgraph "硬件载体 Hardware"
        GBOOK["Googlebook<br/>Intelligence Laptop"]
        XR["Android XR 眼镜<br/>Gentle Monster/Warby Parker"]
        PIXEL["Pixel / Samsung"]
    end

    TPU --> FLASH
    TPU --> PRO
    TPU --> OMNI
    GCP --> MAA
    ENERGY --> TPU

    FLASH --> AG
    FLASH --> MAA
    OMNI --> VEO
    OMNI --> IMAGEN
    FLASH --> SPARK

    AG --> SEARCH
    MAA --> WORKSPACE
    SPARK --> GEMINI_APP
    AG --> FIREBASE

    SEARCH --> GBOOK
    GEMINI_APP --> XR
    ANDROID --> PIXEL
    WORKSPACE --> GBOOK

graph LR
    subgraph "Thinking Level"
        MIN["Minimal<br/>~1x token 成本"]
        LOW["Low<br/>~2-3x token 成本"]
        MED["Medium<br/>~5-8x token 成本<br/>【新默认】"]
        HIGH["High<br/>~15-20x token 成本"]
    end

    MIN -->|+推理| LOW
    LOW -->|+推理| MED
    MED -->|+推理| HIGH

    subgraph "输出特征"
        SPEED["速度: High > Med > Low > Min"]
        QUALITY["质量: High > Med > Low > Min"]
        COST["成本: High >> Med > Low > Min"]
    end

graph TB
    subgraph "输入管线 Input Pipeline"
        TEXT["文本输入<br/>Tokenization"]
        IMAGE["图片输入<br/>ViT Encoding"]
        VIDEO["视频输入<br/>帧采样 + ViT"]
        AUDIO["语音输入<br/>ASR + 语义编码"]
    end

    TEXT --> FUSION["多模态融合层<br/>Cross-Attention Fusion"]
    IMAGE --> FUSION
    VIDEO --> FUSION
    AUDIO --> FUSION

    FUSION --> CONTEXT["上下文管理<br/>1M Token Window<br/>+ KV Cache"]
    CONTEXT --> THINK["Thinking Engine<br/>4-Level Adaptive"]
    
    THINK --> |"Minimal"| OUT_FAST["快速输出<br/>~280+ tok/s"]
    THINK --> |"Medium（默认）"| OUT_MED["标准推理输出<br/>~150 tok/s"]
    THINK --> |"High"| OUT_DEEP["深度推理输出<br/>~50 tok/s"]

    subgraph "Thought Preservation"
        TP_STORE["思维链存储"]
        TP_COMPRESS["思维压缩"]
        TP_RETRIEVE["跨轮次检索"]
    end

    THINK <--> TP_STORE
    TP_STORE --> TP_COMPRESS
    TP_COMPRESS --> TP_RETRIEVE
    TP_RETRIEVE --> CONTEXT

graph TB
    subgraph "输入编码器 Encoders"
        I_TEXT["Text Encoder<br/>Gemini Tokenizer"]
        I_IMAGE["Image Encoder<br/>ViT + Patch Embedding"]
        I_AUDIO["Audio Encoder<br/>SoundStream/EnCodec"]
        I_VIDEO["Video Encoder<br/>时空 Tokenizer"]
    end

    subgraph "统一潜空间 Unified Latent Space"
        LATENT["多模态 Latent<br/>Diffusion Foundation<br/>+ World Model"]
    end

    subgraph "输出解码器 Decoders"
        O_TEXT["Text Decoder<br/>Gemini LM Head"]
        O_IMAGE["Image Decoder<br/>Diffusion + VAE"]
        O_AUDIO["Audio Decoder<br/>Neural Vocoder"]
        O_VIDEO["Video Decoder<br/>Temporal Diffusion<br/>+ 原生音频"]
    end

    I_TEXT --> LATENT
    I_IMAGE --> LATENT
    I_AUDIO --> LATENT
    I_VIDEO --> LATENT

    LATENT --> O_TEXT
    LATENT --> O_IMAGE
    LATENT --> O_AUDIO
    LATENT --> O_VIDEO

    subgraph "关键技术创新"
        CONSISTENCY["场景/角色一致性<br/>Identity Preservation"]
        PHYSICS["物理世界理解<br/>Physics Simulation"]
        MULTI_TURN["多轮编辑<br/>Diffusion Inversion"]
    end

    LATENT --> CONSISTENCY
    CONSISTENCY --> PHYSICS
    PHYSICS --> MULTI_TURN

graph TB
    subgraph "开发者入口 Developer Entry Points"
        DESKTOP["Antigravity Desktop<br/>Agent-first IDE<br/>对话 + Artifacts + 多Agent编排"]
        CLI["Antigravity CLI<br/>命令行 Agent 执行"]
        SDK["Antigravity SDK<br/>Python/TypeScript SDK"]
        STUDIO["AI Studio<br/>Prompt → Agent 一键导出"]
    end

    subgraph "运行时 Runtime"
        LOCAL_RT["本地运行时<br/>Desktop/CLI 内置"]
        MANAGED_RT["Managed Agents Runtime<br/>Google Cloud 托管"]
    end

    subgraph "托管沙箱 Managed Sandbox"
        SANDBOX["Linux 沙箱环境"]
        BASH["Bash 执行"]
        PYTHON["Python 运行时"]
        NODE["Node.js 运行时"]
        FILES["文件系统操作"]
        BROWSER["Headless Browser<br/>网页浏览"]
        SKILLS["自定义 Skills<br/>技能注册表"]
    end

    subgraph "编排层 Orchestration"
        ORCHESTRATOR["Agent Orchestrator<br/>单Agent/多Agent编排"]
        SINGLE["单 Agent 模式<br/>简单任务"]
        MULTI["多 Agent 协作<br/>复杂任务分解"]
    end

    subgraph "模型后端 Model Backend"
        FLASH_BE["Gemini 3.5 Flash<br/>高频推理"]
        PRO_BE["Gemini 3.5 Pro<br/>深度推理"]
        API_BE["Gemini API<br/>1M Context + Thinking"]
    end

    DESKTOP --> LOCAL_RT
    CLI --> LOCAL_RT
    SDK --> LOCAL_RT
    SDK --> MANAGED_RT
    STUDIO --> DESKTOP

    MANAGED_RT --> SANDBOX
    SANDBOX --> BASH
    SANDBOX --> PYTHON
    SANDBOX --> NODE
    SANDBOX --> FILES
    SANDBOX --> BROWSER
    SANDBOX --> SKILLS

    LOCAL_RT --> ORCHESTRATOR
    MANAGED_RT --> ORCHESTRATOR

    ORCHESTRATOR --> SINGLE
    ORCHESTRATOR --> MULTI

    SINGLE --> FLASH_BE
    MULTI --> FLASH_BE
    SINGLE --> PRO_BE

graph TB
    subgraph "安全边界 Security Boundary"
        API_GATEWAY["API Gateway<br/>认证 + 限流"]
        ORCHESTRATOR_S["Agent Orchestrator<br/>任务调度"]
    end

    subgraph "沙箱选项（推演）"
        OPT1["选项1: gVisor<br/>用户态内核<br/>系统调用过滤<br/>★★★☆☆ 隔离性"]
        OPT2["选项2: Firecracker microVM<br/>轻量虚拟机<br/>硬件级隔离<br/>★★★★★ 隔离性"]
        OPT3["选项3: Linux Namespace<br/>+ cgroup + seccomp<br/>容器级隔离<br/>★★★☆☆ 隔离性"]
    end

    subgraph "安全控制"
        NETWORK["网络隔离<br/>出站白名单"]
        STORAGE["存储隔离<br/>临时文件系统"]
        RESOURCE["资源限制<br/>CPU/Mem/Time"]
        AUDIT["审计日志<br/>所有操作记录"]
    end

    API_GATEWAY --> ORCHESTRATOR_S
    ORCHESTRATOR_S --> OPT1
    ORCHESTRATOR_S --> OPT2
    ORCHESTRATOR_S --> OPT3

    OPT1 --> NETWORK
    OPT2 --> NETWORK
    OPT3 --> NETWORK
    OPT1 --> STORAGE
    OPT2 --> STORAGE
    OPT3 --> STORAGE
    OPT1 --> RESOURCE
    OPT2 --> RESOURCE
    OPT3 --> RESOURCE

    NETWORK --> AUDIT
    STORAGE --> AUDIT
    RESOURCE --> AUDIT

stateDiagram-v2
    [*] --> Created: API 调用 / CLI 启动
    Created --> Initializing: 分配沙箱 + 加载 Skills
    Initializing --> Ready: 环境就绪
    Ready --> Executing: 接收任务
    Executing --> Thinking: 推理中
    Thinking --> Acting: 生成动作
    Acting --> Observing: 执行动作 + 获取结果
    Observing --> Thinking: 继续推理
    Thinking --> WaitingConfirm: 需要用户确认
    WaitingConfirm --> Executing: 用户批准
    WaitingConfirm --> Aborted: 用户拒绝
    Executing --> Completed: 任务完成
    Executing --> Failed: 错误/超时
    Failed --> Retrying: 自动重试
    Retrying --> Executing: 重试成功
    Retrying --> Failed: 重试耗尽
    Completed --> Cleanup: 回收资源
    Failed --> Cleanup: 回收资源
    Aborted --> Cleanup: 回收资源
    Cleanup --> [*]: 沙箱销毁

graph TB
    subgraph "单 Agent 模式"
        SA_TASK["任务"] --> SA_AGENT["Agent<br/>+ 全部 Skills"]
        SA_AGENT --> SA_RESULT["结果"]
    end

    subgraph "多 Agent 编排模式"
        MA_TASK["复杂任务"] --> MA_ORCH["Orchestrator<br/>任务分解 + 分配"]
        MA_ORCH --> MA_A1["Agent 1<br/>编码"]
        MA_ORCH --> MA_A2["Agent 2<br/>测试"]
        MA_ORCH --> MA_A3["Agent 3<br/>文档"]
        MA_A1 -->|代码| MA_A2
        MA_A2 -->|测试结果| MA_A1
        MA_A1 --> MA_ORCH
        MA_A2 --> MA_ORCH
        MA_A3 --> MA_ORCH
        MA_ORCH --> MA_RESULT["整合结果"]
    end

gantt
    title 93 Agent OS 构建 Demo 调度推演
    dateFormat X
    axisFormat %H

    section 阶段1: 架构设计
    Master Agent 架构规划     :a1, 0, 3600
    子系统划分               :a2, 3600, 7200

    section 阶段2: 核心模块 (并行)
    内核 Agent (×5)          :b1, 7200, 18000
    驱动 Agent (×8)          :b2, 7200, 21600
    文件系统 Agent (×6)      :b3, 7200, 25200
    内存管理 Agent (×4)      :b4, 7200, 18000

    section 阶段3: 用户空间 (并行)
    Shell Agent (×3)         :c1, 18000, 28800
    工具链 Agent (×10)       :c2, 18000, 32400
    UI Agent (×8)            :c3, 21600, 36000
    网络栈 Agent (×6)        :c4, 18000, 32400

    section 阶段4: 集成测试
    集成 Agent (×15)         :d1, 32400, 39600
    测试 Agent (×20)         :d2, 36000, 43200

    section 阶段5: 调试修复
    修复 Agent (×8)          :e1, 39600, 43200

graph LR
    subgraph "用户接口 User Interface"
        EMAIL["Gmail<br/>任务邮件"]
        VOICE["Gemini Voice<br/>语音指令"]
        APP["Gemini App<br/>对话接口"]
    end

    subgraph "Spark 引擎 Spark Engine"
        PARSER["任务解析器<br/>Intent + Entity Extraction"]
        QUEUE["任务队列<br/>优先级 + 调度"]
        EXECUTOR["执行引擎<br/>Antigravity Runtime"]
        NOTIFIER["通知引擎<br/>Email / Push"]
    end

    subgraph "Google Workspace 集成"
        G_GMAIL["Gmail API<br/>读写邮件"]
        G_CAL["Calendar API<br/>日程管理"]
        G_DRIVE["Drive API<br/>文件操作"]
        G_DOCS["Docs API<br/>文档编辑"]
        G_CHROME["Chrome<br/>Autobrowse<br/>网页操作"]
    end

    subgraph "安全层 Security"
        CONFIRM["确认机制<br/>高风险操作"]
        AUDIT_S["审计日志"]
        ISOLATION["数据隔离"]
    end

    EMAIL --> PARSER
    VOICE --> PARSER
    APP --> PARSER
    PARSER --> QUEUE
    QUEUE --> EXECUTOR
    EXECUTOR --> G_GMAIL
    EXECUTOR --> G_CAL
    EXECUTOR --> G_DRIVE
    EXECUTOR --> G_DOCS
    EXECUTOR --> G_CHROME
    EXECUTOR --> CONFIRM
    CONFIRM -->|批准| EXECUTOR
    CONFIRM --> NOTIFIER
    G_GMAIL --> AUDIT_S
    G_CAL --> AUDIT_S
    EXECUTOR --> ISOLATION

sequenceDiagram
    participant User as 用户
    participant Spark as Spark Engine
    participant Gmail as Gmail API
    participant Calendar as Calendar API
    participant Drive as Drive API
    participant Chrome as Chrome Autobrowse
    participant Gemini as Gemini 3.5 Flash

    User->>Spark: 发邮件 "帮我安排下周会议"
    Spark->>Gemini: 解析任务意图
    Gemini-->>Spark: 任务拆解：1.查看日程 2.联系参会者 3.创建邀请

    loop 查看已有日程
        Spark->>Calendar: 获取下周日程
        Calendar-->>Spark: 返回日程数据
    end

    loop 搜索可用时间
        Spark->>Gmail: 检查相关邮件线程
        Gmail-->>Spark: 返回邮件内容
    end

    Spark->>Gemini: 综合分析 + 生成会议方案
    Gemini-->>Spark: 会议方案（3个选项）

    Spark->>User: 推送确认请求
    User->>Spark: 确认方案A

    Spark->>Calendar: 创建会议邀请
    Calendar-->>Spark: 创建成功

    Spark->>Gmail: 发送邀请邮件
    Gmail-->>Spark: 发送成功

    Spark->>User: 通知完成

graph TB
    subgraph "Search 1.0（1998-2023）<br/>检索引擎"
        S1_CRAWL["爬虫<br/>Web Index"]
        S1_RANK["PageRank + ML 排序"]
        S1_RESULT["蓝色链接<br/>10 条结果"]
    end

    subgraph "Search 2.0（2023-2025）<br/>AI 摘要引擎"
        S2_CRAWL["爬虫 + 实时索引"]
        S2_RAG["RAG<br/>检索 + 生成"]
        S2_RESULT["AI Overview<br/>摘要 + 来源链接"]
    end

    subgraph "Search 3.0（2026-）<br/>Agent 监控平台"
        S3_AGENT["Information Agents<br/>持久监控"]
        S3_GENUI["Generative UI<br/>动态交互工具"]
        S3_RESULT["定制化信息流<br/>+ 交互工具"]
    end

    S1_CRAWL --> S1_RANK --> S1_RESULT
    S2_CRAWL --> S2_RAG --> S2_RESULT
    S3_AGENT --> S3_GENUI --> S3_RESULT

sequenceDiagram
    participant User as 用户
    participant Search as Search AI Mode
    participant Agent as Antigravity Agent
    participant GenUI as Generative UI Engine
    participant Render as 前端渲染

    User->>Search: "比较 Sony A7IV 和 Canon R6II"
    Search->>Agent: 解析意图 → 对比工具需求
    Agent->>Agent: 调用 Gemini 3.5 Flash<br/>提取参数 + 生成 UI 描述
    Agent->>GenUI: UI 规格描述<br/>（结构化 JSON）
    GenUI->>GenUI: 安全沙箱生成<br/>React/Svelte 组件
    GenUI->>Render: 编译后的 UI 组件
    Render->>User: 渲染交互式对比工具

    User->>Render: 拖动滑块调整 ISO
    Render->>Agent: 参数变更请求
    Agent->>Agent: 重新计算对比结果
    Agent->>Render: 更新数据

graph TB
    subgraph "应用层 Applications"
        APP_3RD["第三方应用"]
        APP_GOOGLE["Google 应用<br/>Gmail/Maps/Chrome/..."]
        APP_SYSTEM["系统应用<br/>设置/电话/消息"]
    end

    subgraph "Gemini Intelligence Layer"
        GI_API["Gemini API<br/>开发者接口"]
        GI_SERVICE["Gemini System Service<br/>核心调度服务"]
        GI_ONDEVICE["设备端模型<br/>Gemini Nano"]
        GI_CLOUD["云端模型<br/>Gemini 3.5 Flash"]
        GI_AGENT["Agent Runtime<br/>任务编排引擎"]
    end

    subgraph "系统能力 System Capabilities"
        SCREEN_READ["屏幕理解<br/>UI Element Tree"]
        ACTION_EXEC["动作执行<br/>Accessibility API"]
        NOTIF_CTRL["通知管理"]
        WIDGET_GEN["Widget 生成引擎"]
        AUTO_FILL["智能填充"]
    end

    subgraph "Android Framework"
        FRAMEWORK["Android 17 Framework<br/>Activity Manager / Window Manager"]
        LINUX_KERNEL["Linux Kernel"]
    end

    APP_3RD --> GI_API
    APP_GOOGLE --> GI_SERVICE
    APP_SYSTEM --> GI_SERVICE

    GI_API --> GI_SERVICE
    GI_SERVICE --> GI_ONDEVICE
    GI_SERVICE --> GI_CLOUD
    GI_SERVICE --> GI_AGENT

    GI_AGENT --> SCREEN_READ
    GI_AGENT --> ACTION_EXEC
    GI_AGENT --> NOTIF_CTRL
    GI_AGENT --> WIDGET_GEN
    GI_AGENT --> AUTO_FILL

    SCREEN_READ --> FRAMEWORK
    ACTION_EXEC --> FRAMEWORK
    NOTIF_CTRL --> FRAMEWORK
    WIDGET_GEN --> FRAMEWORK
    AUTO_FILL --> FRAMEWORK

    FRAMEWORK --> LINUX_KERNEL

graph TB
    subgraph "用户交互层"
        MAGIC_PTR["Magic Pointer<br/>AI 光标"]
        WIDGET_G["AI 生成 Widget"]
        GLOWBAR["Glowbar<br/>硬件交互"]
    end

    subgraph "Gemini Intelligence Layer"
        GI_DESKTOP["Gemini Desktop Service<br/>笔记本优化版"]
        GI_AGENT_D["Desktop Agent Runtime<br/>桌面任务编排"]
    end

    subgraph "融合 OS 层 Fusion OS"
        ANDROID_RUNTIME["Android Runtime<br/>ART + App 兼容层"]
        CHROME_RUNTIME["Chrome Runtime<br/>浏览器引擎"]
        CAST_ENGINE["Cast My Apps<br/>手机应用投射引擎"]
        FILE_SYNC["文件同步引擎<br/>手机 ↔ 笔记本"]
    end

    subgraph "Linux 内核层"
        KERNEL["Linux Kernel<br/>桌面优化配置"]
        DRIVER["硬件驱动<br/>笔记本外设"]
        GPU_ACCEL["GPU 加速<br/>AI 推理"]
    end

    MAGIC_PTR --> GI_DESKTOP
    WIDGET_G --> GI_DESKTOP
    GI_DESKTOP --> GI_AGENT_D
    GI_AGENT_D --> ANDROID_RUNTIME
    GI_AGENT_D --> CHROME_RUNTIME
    CAST_ENGINE --> ANDROID_RUNTIME
    FILE_SYNC --> KERNEL
    ANDROID_RUNTIME --> KERNEL
    CHROME_RUNTIME --> KERNEL
    KERNEL --> DRIVER
    KERNEL --> GPU_ACCEL

graph LR
    subgraph "Google"
        G_FREE["AI Free<br/>$0/月"]
        G_PLUS["AI+<br/>$100/月"]
        G_ULTRA["AI Ultra<br/>$200/月<br/>含 Spark + Omni"]
    end

    subgraph "OpenAI"
        O_FREE["Free<br/>$0/月"]
        O_PLUS["Plus<br/>$20/月"]
        O_PRO["Pro<br/>$200/月<br/>含 Operator"]
    end

    subgraph "Anthropic"
        A_FREE["Free<br/>$0/月"]
        A_PRO["Pro<br/>$20/月"]
        A_MAX["Max<br/>$100-200/月<br/>含 Computer Use"]
    end

    G_FREE -.->|"竞争"| O_FREE
    G_PLUS -.->|"竞争"| O_PRO
    G_ULTRA -.->|"竞争"| O_PRO

graph TB
    subgraph "全栈能力对比"
        direction TB

        subgraph "Google — 全栈最完整"
            G_MODEL["✅ 顶级模型<br/>Gemini 3.5 Flash/Pro"]
            G_SEARCH["✅ 搜索引擎<br/>AI Mode 10亿+"]
            G_OS["✅ 操作系统<br/>Android 17"]
            G_CLOUD["✅ 云基础设施<br/>TPU + GCP"]
            G_HW["⚠️ 硬件<br/>Pixel/XR/Googlebook"]
            G_AGENT["✅ Agent 平台<br/>Antigravity + Spark"]
            G_MEDIA["✅ 媒体生成<br/>Omni + Veo + Imagen"]
            G_WORKSPACE["✅ 生产力工具<br/>Workspace"]
        end

        subgraph "OpenAI — 模型+应用最强"
            O_MODEL["✅ 顶级模型<br/>GPT-5.5"]
            O_SEARCH["⚠️ SearchGPT<br/>规模有限"]
            O_OS["❌ 无操作系统"]
            O_CLOUD["⚠️ Azure 合作<br/>无自有基础设施"]
            O_HW["❌ 无硬件"]
            O_AGENT["✅ Agent 平台<br/>Codex + Operator"]
            O_MEDIA["⚠️ Sora<br/>仅视频"]
            O_WORKSPACE["❌ 无生产力工具"]
        end

        subgraph "Anthropic — 安全+研究最强"
            A_MODEL["✅ 顶级模型<br/>Claude Opus 4"]
            A_SEARCH["❌ 无搜索引擎"]
            A_OS["❌ 无操作系统"]
            A_CLOUD["⚠️ AWS 合作<br/>无自有基础设施"]
            A_HW["❌ 无硬件"]
            A_AGENT["✅ Agent 平台<br/>Claude Code + Computer Use"]
            A_MEDIA["❌ 无媒体生成"]
            A_WORKSPACE["❌ 无生产力工具"]
        end
    end