内容来源：https://aibusiness.com/generative-ai/google-aims-enterprise-cost-efficiency-with-gemini-3-5-flash

内容总结：

谷歌云I/O大会发布新一代AI模型，大幅降低企业使用成本

在周二举行的I/O 2026开发者大会上，谷歌云正式推出面向企业的全新AI模型Gemini 3.5 Flash，直击当前企业用户面临的核心痛点——高昂的令牌（Token）成本。谷歌CEO桑达尔·皮查伊在主题演讲中透露，许多公司今年尚未过半就已耗尽年度令牌预算，而新模型的使用成本仅为每百万令牌1.5美元，是目前市面上最经济的专有前沿模型。

此举被视为对行业价格战的有力回应。此前，Anthropic的Claude Opus 4.6已将成本降至每百万输入令牌5美元、输出令牌25美元。分析人士指出，随着企业AI代理使用量激增，令牌费用正成为企业难以承受的负担，谷歌、Anthropic等模型厂商承受着来自客户和开源模型（如阿里Qwen）的双重价格压力。

除降低成本外，谷歌还推出多模态模型Gemini Omni Flash及多款AI代理产品。其中，个人AI代理Gemini Spark备受关注——它运行于谷歌云专属服务器，可跨Gmail、文档、表格、幻灯片及第三方工具运作，自动整合邮件、聊天和文档信息，管理活动回复并发送跟进提醒。这一产品被视为对标OpenAI旗下开源代理框架OpenClaw的竞品。

此外，谷歌还升级了其AI代理开发平台AntiGravity 2.0，宣称新平台可在12小时内从零构建完整操作系统，且API消耗成本不足1000美元。在搜索领域，谷歌推出智能搜索框，并计划今夏上线可监控特定话题、跨网站和社交媒体扫描的信息代理。

分析人士认为，谷歌正通过全链条产品展示生成式AI从浏览器到原生应用的无缝渗透，但也指出行业竞争已白热化——每款新品几乎都是对竞争对手的回应。对企业而言，这种快速迭代虽带来创新，却也增加了系统标准化和持续维护的难度。

中文翻译：

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新模型让企业在此前基础上大幅降低了令牌消耗成本，而同时发布的一款新智能体正与OpenClaw展开竞争。
谷歌表示，其致力于帮助企业客户在使用AI智能体时减少令牌消耗。
在周二举行的开发者大会I/O 2026上，这家科技巨头推出了面向企业的全新AI模型Gemini 3.5 Flash，直指成本问题。

谷歌还发布了多模态新模型Gemini Omni，以及包括Daily Brief和Gemini Spark在内的新智能体。该云服务商还对其Antigravity智能体AI平台进行了升级。
通过这些举措，谷歌力图在竞争激烈的生成式AI市场中重振其领先地位，并利用自身作为少数成功实现AI产品变现的模型厂商之一的优势——这与Anthropic和OpenAI等竞争对手形成对比。

Gemini Flash 3.5精准切入企业使用AI智能体时面临的主要障碍之一。随着AI智能体的应用日益广泛，企业对驱动它们所需的令牌数量愈发敏感。面对企业对令牌成本的敏感度，供应商正通过降低成本来满足企业需求。例如，Anthropic新推出的Claude Opus 4.6模型将成本降至每百万输入令牌5美元、每百万输出令牌25美元，相较此前的每百万输入令牌15美元、每百万输出令牌75美元大幅下降。Gemini Flash 3.5延续了这一趋势，谷歌宣称该模型是使用成本最低的专有前沿模型，每百万令牌仅需1.50美元。

“我们听说许多公司已经用完了年度令牌预算，而这才刚五月，”谷歌CEO桑达尔·皮查伊在大会主题演讲中表示，“如果企业混合使用Flash和其他前沿模型，可以节省大量成本。”

谷歌大幅削减令牌成本是一项重大举措，Omdia（Informa TechTarget旗下公司）分析师马克·贝库表示。
“追求更便宜、更快、更好，”贝库说，“[这]一直是合乎逻辑的进程，尤其是对谷歌的这些模型而言。”
关注令牌成本敏感性不仅是自然演进，也是谷歌、Anthropic及其他生成式AI供应商的必由之路。

“考虑到当前企业对令牌的焦虑，以及客户意识到其支出实际上已失控……像谷歌、Anthropic这样的模型制造商面临压力，必须提供更具成本效益的解决方案，”Futurum Group分析师布拉德利·希米恩表示。
他补充道，关注成本至关重要，因为大多数非专有模型（如阿里巴巴的Qwen及其他开源模型）的性能已与前沿模型不相上下。除非具备某种专业化优势，否则它们之间差异不大。
“仅就原始AI智能而言……结果没有太大不同，进入和退出的门槛可能相当低，”希米恩说。

谷歌发布了一款全新的专业化模型Gemini Omni Flash，并已在其所有产品中部署。Omni Flash能从任何输入（无论是文本、图像还是视频）生成任意模态的输出。
谷歌还利用Gemini 3.5推动其最新的智能体AI应用，包括Gemini Spark——一款谷歌称可代表用户和开发者工作的个人AI智能体。Spark运行于谷歌云中的专用机器上，并使用模型上下文协议标准，可跨Gmail、Docs、Sheets、Slides及第三方工具工作。它能整合邮件、聊天记录和文档中的信息，通过实时更新电子表格管理活动回复，并自动发送后续提醒。

“它是你的个人AI智能体，帮助你驾驭数字生活，在你指导下代表你采取行动，”皮查伊开玩笑说，即使Spark全天运行，用户也可以合上笔记本电脑。

这款新智能体是谷歌对OpenClaw的回应——后者是流行的开源智能体框架，现已成为OpenAI的一部分。与OpenClaw类似，Gemini Spark可在后台运行，并内置对Google Workspace的访问权限，无需使用API。谷歌表示，由于Gemini 3.5已深度集成，因此无需像使用Claude 3.5 Sonnet那样通过API产生高昂令牌成本。

“我有一种感觉，他们在开发Spark时就已经考虑到了这个模型，考虑到Spark声称的工作方式，”希米恩在提及Claude 3.5 Sonnet时表示。

Gemini 3.5 Flash还为谷歌的AntiGravity 2.0提供支持，这是该供应商智能体开发平台的升级版。AntiGravity的功能包括完全以智能体优先的桌面应用程序。这家科技巨头表示，该平台在12小时内从零构建了一个完整操作系统，且API信用额度消耗不到1000美元。

凭借所有这些新工具和应用，谷歌直接展示了智能体AI如何不仅能响应查询，还能代表用户工作。在搜索领域，谷歌推出了新的智能搜索框。新的信息智能体将监控特定话题并扫描网站及社交媒体，于今年夏季上线。

“他们真正向我们展示了在企业环境中，将AI用于个人追求是一个完整的连续体……无论是在浏览器中使用，还是在原生应用中使用，”希米恩说。

不过，尽管取得了这些进展，谷歌仍是在应对竞争对手，每款新产品都是对其他供应商的回应，Gartner分析师斯维特拉娜·西库拉表示。
“我们正处于企业试图超越彼此的阶段，”西库拉说。“这场……竞争已经白热化。”

然而，顶级生成式AI供应商之间的激烈竞争可能会影响企业，因为它们必须随着每次模型更新不断调整自身软件栈。
“这种创新的快速迭代可能使企业难以在高级概念验证之外真正实现标准化，除非它们愿意投入时间和精力持续监控、修订、测试并治理这些动态系统，”希米恩说。

英文来源：

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The new model allows enterprises to spend less on tokens than they would previously, while one of the newly released agents competes against OpenClaw.
Google says it’s looking to help its enterprise customers use fewer tokens when using AI agents.
At I/O 2026, its developer conference on Tuesday, the tech giant rolled out a new enterprise AI model, Gemini 3.5 Flash, which is aimed directly at the cost problem.
Google also introduced Gemini Omni, a new multimodal model, and new agents, including Daily Brief and Gemini Spark. The cloud vendor also revamped its Antigravity agentic AI platform.
With these moves, Google sought to reassert its prominence in the highly competitive generative AI market and capitalize on its position as one of the few model makers to have successfully monetized its AI offerings, unlike competitors such as Anthropic and OpenAI.
Gemini Flash 3.5 homes in on one of the major hurdles enterprises face when using AI agents. As the use of AI agents grows, enterprises are becoming more sensitive to the number of tokens required to power them. With enterprises sensitive to token costs, vendors are catering to enterprise needs by lowering costs. For example, Anthropic's new Claude Opus 4.6 model reduced costs to $5 per million input tokens and $25 per million output tokens, a significant drop from $15 per million input tokens and $75 per million output tokens. Gemini Flash 3.5 follows that trend, with Google touting the model as the least expensive to use proprietary frontier model, costing $1.50 per million tokens.
“We’ve heard that many companies are already blowing through their annual token budgets, and it's only May,” said Sundar Pichai, Google CEO, during a conference keynote. “If companies used a mix of Flash and other frontier models, they could save a lot of money.”
That Google is slashing token costs is a big move, said Mark Beccue, an analyst at Omdia, a division of Informa TechTarget.
“Thinking cheaper, faster, better,” Beccue said. “[This] has been this logical progression over time, particularly for Google on these models.”
Not only has paying attention to token cost sensitivity been a natural progression, but it has also been something that Google, Anthropic and other generative AI vendors have been forced to do.
“With token anxiety being what it is right now in the enterprise, and how much customers are realizing that their expense is really unbridled right now … there is some pressure on the model makers like Google, Anthropic … to give you a much more cost-effective solution,” said Bradley Shimmin, an analyst at Futurum Group.
The focus on cost is much needed because most non-proprietary models, such as Alibaba Qwen and other open source models, boast similar performance to frontier models, he added. There is not much that differentiates them, barring specialization of some sort.
“When you’re just talking about raw AI intelligence … the outcome is not that different, and the barrier to entry and exit can be quite low,” Shimmin said.
Google revealed a new specialized model, Gemini Omni Flash, which it launched across all products. Omni Flash can generate outputs in any modality from any input, whether text, images or video.
Google is also using Gemini 3.5 to push its latest agentic AI applications, including Gemini Spark, a new personal AI agent that Google said works on behalf of users and developers. Spark runs on dedicated machines in Google Cloud and works across Gmail, Docs, Sheets, Slides and third-party tools using the Model Context Protocol standard. It can compile information across emails, chats and documents, manage RSVPs with live updating spreadsheets and send follow-up reminders automatically.
“It’s your personal AI agent that helps you navigate your digital life, taking action on your behalf and under your direction,” Pichai said, joking that even though Spark runs all day, users can close their laptops.
The new agent is Google’s response to OpenClaw, the popular open source agent framework that is now part of OpenAI. Like OpenClaw, Gemini Spark can run in the background and comes with built-in permission to Google Workspace without an API. It is also cost-efficient because Gemini 3.5 is already deeply integrated, so there is no need to incur deep token costs by accessing APIs like with Claude 3.5 Sonnet, according to Google
“I have a feeling that when they made Spark, it was with this model in mind, given how Spark purports to work,” Shimmin said, referring to Claude 3.5 Sonnett.
Gemini 3.5 Flash also powers Google’s AntiGravity 2.0, a revamp of the vendor’s agentic development platform. AntiGravity capabilities include a fully agent-first desktop application. The tech giant said the platform built a complete OS from scratch in 12 hours and consumed less than $1,000 in API credits.
With all its new tools and applications, Google is directly showing how agentic AI does more than respond to queries; it works on behalf of users. In Search, Google launched a new intelligent search box. New information agents that monitor specific topics and scan across websites and social media will launch this summer.
“They're really showing us that using AI for personal pursuit in the enterprise is a full continuum … whether you're using it in the browser, whether you're using it in a native app,” Shimmin said.
Despite these advances, though, Google is responding to competitors, and each new product release is a response to another vendor, said Svetlana Sicular, an analyst at Gartner.
“We're in the middle of companies trying to outdo each other,” Sicular said. “The … competition is overheated.”
The dramatic rivalry among the top generative AI vendors, though, can affect enterprises because they must constantly update their software stacks with each new model update.
"That rapidity of innovation can make it hard for companies to really sort of standardize beyond advanced proof of concepts, unless they're willing to spend the time and energy to keep monitoring and keep revising and testing and governing these living systems,” Shimmin said.