Gemini 4 Argon：为解决棘手难题而生

Gemini 4 Argon 今日已面向全球开放：开发者和企业可通过 AI Studio 和 Gemini 平台中的 API 使用；Google AI Ultra 订阅用户可在 Google Antigravity 中使用；Google AI Ultra 和 Pro 订阅用户可在 Gemini 应用和搜索中的 AI Mode 使用。Gemini 4 Argon is now globally available today for developers and enterprises via the API in AI Studio and Gemini platform, for Google AI Ultra subscribers in Google Antigravity, and Google AI Ultra and Pro subscribers in the Gemini app and AI Mode in Search.

Argon 擅长深入处理跨领域的复杂现实任务，涵盖编程、金融、法律、网络安全和科学等领域。凭借在多步骤任务中的深度与精准度，Argon 在各领域的基准测试中超越其他前沿模型，在 Vals Index 上排名第一。该指数衡量模型在金融、编程、法律和税务等关键经济领域的表现。Argon excels at deep work in complex, real-world tasks across domains including coding, finance, legal, cybersecurity, and science. Its depth and precision across multi-step tasks leads Argon to outperform other frontier models on benchmarks across domains, ranking #1 on the Vals Index, which measures model performance across critical economic sectors like finance, coding, legal, and tax work.

该模型今日推出，入门价格 1 为每百万输入 token 2 美元、每百万输出 token 10 美元（缓存输入 token 可享受 95% 折扣）。The model launches today at an introductory price ¹ of $2 per million input tokens and $10 per million output tokens (with cached input tokens at 95% off).

谷歌内部、各类企业以及研究界的团队已在使用 Argon，并在多个领域产生了显著影响：Teams at Google, across enterprises, and in the research community have already been using Argon to land significant impact across fields:

• 解决大型代码库重构和优化等重大工程问题
  To solve major engineering problems like large codebase refactoring and optimizations
• 优化法律、金融和科学等领域的业务工作流程
  To optimize business workflows across domains like legal, finance, and science
• 查找并修补关键网络安全漏洞
  To find and patch critical cybersecurity vulnerabilities
• 推动量子计算、核聚变和生命科学领域取得突破性创新成果
  To enable novel breakthroughs in quantum computing, nuclear fusion, and life sciences

解决复杂的工程任务Solving complex engineering tasks

在 Google，我们一直在用 Argon 攻克最棘手的工程难题。过去几周，软件工程师以前所未有的速度交付高质量代码。Antigravity 中的 Argon 帮助团队将智能体代码提交量提升了 35% 以上，同时将代码回滚次数减少了近三分之一。At Google, we’ve been using Argon on our hardest engineering problems. Over the past few weeks, software engineers have been shipping high-quality code faster than ever. Argon in Antigravity has helped teams increase agentic code submissions by more than 35% while reducing code rollbacks by nearly a third.

• 梳理 Chrome 中的浏览器功能代码：Argon 帮助 Chrome 团队将网页处理核心代码与 Chromium 4000 万行代码库中一个约 600 万行的浏览器功能遗留目录分离。通过每次提交多个整洁的代码变更，Argon 帮助团队完成了一项涉及数百个文件的架构重构，将数月的工作压缩到数周内完成。对于 Chrome 全球数十亿用户而言，这将使网页能够在标签页、侧边栏和浮动窗口之间流畅切换，无需重新加载，并彻底消除一类浏览器崩溃问题。
  Untangling browser feature code in Chrome: Argon helped the Chrome team separate core webpage handling from a ~6 million line legacy folder of browser features held within Chromium’s 40 million-line codebase. Piping multiple clean code changes at a time, Argon helped the team finish an architectural refactor across hundreds of files, completing months of work in weeks. For Chrome's billions of global users, this will unlock the ability for live webpages to move fluidly between tabs, side panels, and floating windows without reloading, eliminating an entire category of browser crashes.

• 数小时内优化生产环境中的 Python 代码库：Antigravity 中的 Argon 正在帮助 Google 开源 Agent Development Kit (ADK) 团队进一步提升性能工程能力。ADK 是一个为企业级智能体提供支持的框架。团队向 Argon 提供了 .agents/skills 规则手册，以及一段简短目标说明：消除框架开销，同时不破坏现有应用。Argon 在夜间自主运行，找出了多项优化方案；这些方案现已应用于 google/adk-python，使长会话中的内存会话准备时间缩短了 40%，冷启动导入速度提升了 21%。阅读工程深度解析，了解更多信息。
  Optimizing a production Python codebase in hours: Argon in Antigravity is helping the team behind Google's open-source Agent Development Kit (ADK), a framework powering enterprise agents, push their performance engineering further. The team gave Argon their .agents/skills rulebook and a one-paragraph goal to eliminate framework overhead without breaking existing apps. Working autonomously overnight, Argon surfaced optimizations, now live in google/adk-python, that cut in-memory session prep time by 40% in long sessions and sped up cold imports by 21%. Read the engineering deep dive to learn more.
• 量子化学开源软件包优化：xTB（半经验扩展紧束缚）是分子领域引用次数最多的开源量子化学软件包之一。科学家使用它来预测分子的三维形状，并筛选大量药物和材料候选物。我们的研究人员借助 Antigravity 中的 Argon，将 xTB 预测分子结构的速度提升至原来的 2.3 倍，并将构象搜索的速度提升至原来的 1.8 倍。相关更改已贡献至 GitHub 上的 xTB 官方代码仓库。
  Quantum chemistry open-source package optimization: xTB (Semiempirical Extended Tight-Binding) is one of the most-cited open-source quantum chemistry packages for molecules. Scientists use it to predict molecules' 3D shapes and to screen large numbers of drug and materials candidates. Using Argon in Antigravity, our researchers made xTB up to 2.3x faster at predicting molecular structures and 1.8x faster at conformer search. The changes have been contributed to the official xTB repository on GitHub.
• 让我们的开放 Gemma 模型快近三倍：借助 Argon，我们通过 vLLM 在 A100 上实现了端到端推理速度提升 2.85 倍（将 Gemma 4 E2B 的吞吐量从约每秒 37,900 个 token 提升至超过 108,000 个），且 token 完全一致、质量毫无下降，仅用了短短几天——这通常需要数月才能完成。欢迎查看上游拉取请求（优化内容涵盖从注意力调优到推测解码的各个方面），了解具体改动。
  Making our open Gemma models nearly three times as fast: Using Argon, we achieved a 2.85x end-to-end inference speedup on an A100 via vLLM (accelerating throughput from ~37,900 to over 108,000 tokens per second on Gemma 4 E2B) with 100% token parity and zero quality drop in just a few days, a process that would usually take months. Check out the upstream pull requests (optimizing everything from attention tuning to speculative decoding) to see the exact changes.
• 交付复杂的 3D 可视化效果：与之前的 Gemini 模型相比，Argon 在空间推理、数学精度和视觉编程方面都有显著提升。通过使用 /goal 等斜杠命令，并在 Antigravity 中提示多智能体循环搭配自定义技能，Google 员工正使用 Argon，以原生代码构建复杂的 3D 可视化效果、高保真游戏和交互式动画原型，这些内容可直接在浏览器中渲染。
  Delivering complex 3D visualizations: Argon brings major improvements in spatial reasoning, mathematical precision, and visual coding compared to previous Gemini models. Using slash commands like /goal and prompting for multi-agent loops with custom skills in Antigravity, Googlers are using Argon to prototype complex 3D visualizations, high-fidelity games, and interactive animations in vanilla code that can be rendered directly in the browser.

改造关键业务和专业工作流程Transforming critical business and professional workflows

Argon 融合了前沿推理能力、深度视觉感知、拓展的领域知识以及更强的写作能力，覆盖法律、金融、科学和编程领域，助力处理高风险的专业工作流程。它表达清晰，让你随时了解进展，并且比我们此前的任何 Gemini 模型都更能遵循风格指示。Argon 回答问题更加直接，较少使用模棱两可的措辞，不会不必要地重复，也会避免在回复中使用陈词滥调。Argon combines frontier reasoning, deep visual perception, expanded domain knowledge, and stronger writing capabilities across legal, finance, science, and coding to help with high-stakes professional workflows. It communicates clearly, keeping you in the loop, and follows style instructions better than any of our previous Gemini models. Argon answers questions more directly with less hedging, doesn’t repeat itself more than necessary, and skips clichés throughout the responses.

我们的早期体验计划中的企业客户和初创公司已经在使用 Argon 方面取得了显著成果。Enterprise customers and startups in our early access program are already seeing strong wins with Argon.

凭借先进的推理与多模态能力，同时严格以事实为依据，Argon 在深度多模态文档理解、纵向数据分析和交互式分析沙盒方面表现出色。Using its advanced reasoning and multimodal capabilities while maintaining strict grounding, Argon excels in deep multimodal document comprehension, longitudinal data analysis, and interactive analytical sandboxes. 

与研究人员和领域专家携手，加速产生现实影响Accelerating real-world impact with researchers and domain experts

研究人员、工程师和安全专家已经在使用 Argon，推动网络防御、科学、数学和机器人技术的发展。它帮助网络防御人员和研究人员验证假设、自主审计关键代码库和形式化证明，并发现隐蔽的零日漏洞和逻辑缺陷。Researchers, engineers, and security specialists are already using Argon to push the boundaries of cyber defense, science, math, and robotics. It’s helping cyber defenders and researchers test hypotheses, autonomously audit critical codebases and formal proofs, and catch subtle zero-day vulnerabilities and logic flaws.

将最先进的网络能力赋予更多值得信赖的防御者Bringing state-of-the-art cyber capabilities to more trusted defenders

从今天起，我们将开始拓展合作伙伴网络，新增数百家 Fairwind Program 合作伙伴。Starting today, we’re beginning expansion to hundreds of additional Fairwind Program partners.

Wiz 已经在其“Scan for Good”计划中使用 Argon，该计划免费为公众利益保护关键基础设施。借助对该模型的抢先体验，Wiz 展示了 Argon 在多个高风险领域的实际影响：Wiz is already using Argon for its "Scan for Good" initiative, which protects critical infrastructure for the public good and for free. With early access to the model, Wiz has demonstrated Argon's real-world impact across multiple high-stakes sectors:

• 保护敏感政府数据：作为长期网络韧性计划的一部分，Argon 与一家联邦机构合作，主动发现并修复了一项漏洞，该漏洞可能导致敏感数据和政府基础设施暴露。此项工作有助于防止关键安全领域的开发细节泄露，并阻止未经授权访问专用模型。
  Securing sensitive government data: As part of a long-standing cyber resilience program and in collaboration with a federal agency, Argon helped to proactively identify and remediate a gap that risked exposing sensitive data and government infrastructure. This effort helped prevent against the exposure of critical security sector development details and unauthorized access to specialized models.
• 保护关键医疗基础设施：Wiz 还利用 Argon 保护重要的医疗基础设施。通过串联利用复杂漏洞，该模型帮助团队发现并迅速修复了一个公开文件下载绕过漏洞，该漏洞泄露了主密钥并授予了管理员访问权限。Argon 不仅发现了漏洞，还主动保护了数十万份患者隐私记录。
  Protecting critical healthcare infrastructure: Wiz also used Argon to protect vital healthcare infrastructure. By chaining complex vulnerabilities, the model helped the team discover and quickly fix a public file download bypass that exposed a master key and granted administrator access. Argon went beyond spotting a vulnerability to proactively safeguarding hundreds of thousands of private patient records.

解锁新的科学突破Unlocking new scientific breakthroughs

Argon 已经在整个科学界产生了实际影响，助力多个领域的科学家和专家取得新发现。Argon is already having real-world impact across the scientific community — enabling novel discovery for scientists and experts across multiple domains.

• 量子计算：Argon 正在帮助我们的研究人员加快量子纠错和算法设计两方面的进展。为了让错误解码器能够实时跟上量子硬件的步伐，Argon 将我们内部版本的 AlphaQubit（我们的机器学习量子纠错解码器）转换为一个经过高度优化的硬件内核，使其推理吞吐量几乎翻倍。这样一来，我们就能部署规模更大、能力更强的模型，并扩展到更大型的量子设备，同时继续满足严格的实时阈值要求。Argon 也在降低量子子程序的时空成本。对于 arcsin——近期量子模拟算法中的一个基础模块——由 Argon 编写并在 Lean 中经过形式化验证的一种实现，与已发表的量子 CORDIC 基准实现相比，时空成本降低了 100 倍以上。这是迈向优化量子电路标准库的一步。
  Quantum computing: Argon is helping our researchers accelerate progress across both quantum error correction and algorithm design. To help error decoders keep pace with quantum hardware in real-time, Argon translated an internal version of AlphaQubit, our ML quantum error correction decoder, into a single, highly optimized hardware kernel — nearly doubling its inference throughput so we can deploy larger, more capable models and scale to larger quantum devices, while continuing to meet strict real-time thresholds. Argon is also reducing spacetime costs for quantum subroutines. For arcsin, a building block in recent quantum simulation algorithms, an implementation written by Argon and formally verified in Lean cuts spacetime cost by more than 100x compared to a published quantum CORDIC baseline, a step toward a standard library of optimized quantum circuits.
• 核聚变：仿星器是极其复杂的装置，被视为实现无限清洁聚变能源的主要候选方案，但优化其三维磁场向来十分困难。自 1967 年以来，一项被称为“Grad 猜想”的长期假设认为，不可能找到这些磁场的精确数学解，直到近期出现了反例，其中包括马里兰大学 Matt Landreman 教授发现的反例。如今，Google 的一个团队与 Landreman 教授合作，发现了更广泛的一类反例，推翻了 Grad 猜想。这些新解为聚变领域提供了可靠的基准，可用于检验仿星器模拟代码；这些代码是未来设计的重要工具。
  Nuclear fusion: Stellarators are incredibly complex machines that represent a leading candidate for limitless clean fusion energy, but optimizing their 3D magnetic fields is famously difficult. Since 1967, a long-standing hypothesis known as “Grad’s conjecture” assumed that finding exact mathematical solutions for these fields was impossible, until recent counterexamples were found, including by Professor Matt Landreman (University of Maryland). Now, a team at Google alongside Professor Landreman has discovered a broader class of counterexamples to Grad's conjecture. These new solutions give the fusion community reliable benchmarks to test their stellarator simulations codes, which are valuable tools for future designs.
• 罕见病研究：Gamow Labs 的研究人员使用 Argon 分析了患有罕见发育性肺部疾病的新生儿的去标识化基因组。在一个案例中，Argon 精准发现了一处常规软件多年未能识别的染色体重排，并解释了它为何一直未被发现。在基于真实临床和实验室数据构建的 Gamow Labs 私有评测中，Argon 在 RareBench（罕见病诊断辅助能力得分为 57%）和 LabBench（湿实验推理能力得分为 52.2%）上均位列第一。这些进展有望帮助罕见病患儿家庭更快获得诊断。更多详情请参阅博客 2。
  Rare disease research: Researchers at Gamow Labs used Argon to analyze de-identified genomes from newborns with rare developmental lung disorders. In one case, Argon pinpointed a chromosomal rearrangement that routine software missed for years, and explained why it went undetected. On private Gamow Labs evals derived from real clinical and lab data, Argon topped on RareBench (57% on assistance with rare-disease diagnosis) and LabBench (52.2% on wet-lab reasoning). These advances point to faster diagnosis for families facing rare conditions. See blog ² for more details.
• 酶设计：设计具有精准反应性的酶一向进展缓慢，往往需要数月时间进行定制化模型调优和候选筛选。丝氨酸酯酶是一类能够切断目标分子中酯键的酶，广泛应用于回收利用，以及药品、生物燃料和洗涤剂的制造。我们的科学家与 Argon 合作设计丝氨酸酯酶，并以基准分子 4MU-乙酸酯为目标；其酯键断裂后会在紫外光下发光。短短数小时内，Argon 汇集了相关数据、完成模型调优，并确定了多种受生物化学启发的筛选条件，最终得到五种全新的设计。后续实验室测试证实，这些设计均具有稳定的催化活性。成功生成酶所展现出的速度与便捷性，彰显了在生物制造、绿色化学和药物开发等领域加速酶工程发展的潜力。
  Enzyme design: Engineering enzymes with precise reactivity is notoriously slow, often demanding months of bespoke model tuning and candidate screening. Serine esterases are a class of enzymes that cut ester bonds on targeted molecules, widely used in recycling, and the manufacture of pharmaceuticals, biofuels and detergents. Our scientists worked with Argon to design serine esterases, targeting the benchmark molecule 4MU-acetate that glows under UV light once its ester bonds are broken. In a matter of hours, Argon assembled relevant data, performed model tuning and identified multiple biochemistry-inspired filters to get to a final set of five novel designs. Subsequent laboratory testing confirmed robust catalytic activity across these designs. The speed and ease of successful enzyme generation demonstrates the potential for rapid acceleration in enzyme engineering in fields such as biomanufacturing, green chemistry, and drug development.

为进一步加快研究进程，我们将向 10,000 名科学家免费提供 Google Antigravity 最高使用等级，为期 6 个月（分批接入），但须符合资格要求，并视容量和遴选结果而定。现已开放申请。To further advance the pace of research, we’re offering 10,000 scientists the highest usage tier in Google Antigravity free of charge for 6 months (onboarded on a rolling basis), subject to eligibility, capacity, and selection. Applications are now open.

加速机器人技术开发Speeding up robotics development

通过融合先进的视觉语义推理、深层物理理解和自主代码生成能力，Argon 为机器人技术栈的各个环节解锁了全新的工作流程，并加速了迈向物理通用人工智能（AGI）的进程。Argon 在具身推理（ERQA）基准测试中的表现体现了这一能力飞跃。该基准测试考查模型理解并解决 3D 环境中物理和空间问题的能力。仅凭推理，Argon 就超越了所有其他前沿模型，得分达到 87%。By bringing together advanced visual-semantic reasoning, deep physical understanding, and autonomous code generation, Argon unlocks new workflows across the robotics stack and accelerates progress toward physical AGI. This leap in capability is reflected in Argon’s performance on the Embodied Reasoning (ERQA) benchmark, which tests a model's ability to understand and solve physical, spatial problems in 3D environments. Relying on pure reasoning, Argon outperforms all other frontier models, with an 87% score.

为展示这些能力在实际中的表现，我们测试了 Argon 仅通过观看来学习分布外物理技能的能力。在一项内部测试中，Argon 观看了一段人类玩沙包投掷游戏的原始视频，映射了环境中的空间坐标，并计算出所需的全身关节运动。随后，它自主编写了模拟代码。将其移植到 Apptronik 的 Apollo 人形机器人后，该机器人在一次真实场景测试中迅速连续投进了七个沙包。To demonstrate these capabilities in action, we tested Argon’s ability to learn an out-of-distribution physical skill simply by watching. In an internal test, Argon watched a raw video of a human playing cornhole, mapped the spatial coordinates of the environment, and calculated the required whole-body joint movements. It then autonomously built the simulation code. When transferred onto Apptronik’s Apollo humanoid, the robot quickly sank seven consecutive shots in a real-world trial.

这条“从视频到仿真再到现实”的流程，将数周的手动仿真建模工作压缩到短短几小时，把普通视频转化为可扩展、无限的机器人训练场。欢迎在我们的开发者博客中了解更多，看看它如何加快机器人技术的开发进程。This "Video-to-Sim-to-Real" pipeline compresses weeks of manual simulation modeling into a few hours, transforming ordinary videos into a scalable, infinite training ground for robotics. Learn more about how this accelerates the pace of development in robotics in our developers blog.

负责任且安全地开发 ArgonDeveloping Argon responsibly and safely

安全与安保是 Google 模型开发的基础。由于 Argon 是一款能力极强的模型，我们与多家第三方合作伙伴共同测评了模型的某些能力和安全防护措施。Gemini 4 Argon 代表了迄今为止我们最全面的安全与安保体系：Safety and security are foundational to model development at Google. Because Argon is a highly capable model, we collaborated with a variety of third-party partners on measurement of certain model capabilities and safeguards. Gemini 4 Argon represents our most comprehensive safety and security stack yet:

• 滥用与越狱防护：帮助防御者修补医院软件或加速生物工程研发的同样强大的编码和科学能力，也需要针对恶意行为者采取强有力的防护措施。根据我们的前沿安全框架，我们评估了 Argon 在多个领域增强后的能力，并部署了由越狱抵抗、监控和执行措施组成的多层防护体系。这大幅提升了我们的稳健性——例如，外部生物领域红队测试只能解锁我们测试的不到 1% 的生物子任务。此外，在应对危险请求方面——从编写漏洞利用代码到协助处理危险生物材料——Argon 拒绝满足有害请求的表现显著优于我们之前的模型。在一组旨在对模型进行压力测试的对抗性测试中，违规率降低了近一半，表现也显著优于之前的 Gemini 模型。
  Misuse & jailbreak defenses: The same coding and scientific capabilities that help defenders patch hospital software or accelerate bioengineering also require strong safeguards against malicious actors. Under our Frontier Safety Framework, we evaluated Argon’s enhanced capabilities across several domains, and deployed a multi-layer defense stack combining jailbreak resistance, monitoring, and enforcement. This greatly improved our robustness — for instance, external bio red teaming could only unlock less than 1% of bio sub-tasks we test for. Further, when it comes to dangerous requests — from writing exploit code to helping with dangerous biological materials — Argon is significantly better at not fulfilling harmful requests than our previous models. On an adversarial set meant to stress test the model, violations reduced nearly 2-fold — also significantly better than previous Gemini models.
• Agent alignment & real-time monitoring: As agents become more capable problem solvers, we have to ensure they don’t get overly eager to finish a task by taking unauthorized shortcuts when they hit a roadblock, like a permission error or a failing test.
  • First, we trained Argon to respect system boundaries, report negative findings honestly, and pause for human confirmation before taking irreversible steps. On coding benchmarks where models have no incentive to hold back, shortcut attempts dropped to just 2% on Gemini 4 Argon, our best performance compared to previous Gemini models.
  • Second, as a defense-in-depth layer, we built an automated misalignment monitor that reads the agent’s step-by-step reasoning and actions to catch and block unintended workarounds in real time. We used this monitor across internal deployments, capability evaluations, and reinforcement learning training runs — while strictly avoiding penalizing the model’s thoughts during training so its reasoning remains transparent and monitorable.
• 提示注入防护：智能体浏览网页、阅读电子邮件或检查代码时，可能会遇到旨在劫持其任务的隐藏恶意指令。通过对抗训练和自动化红队测试，Argon 在 Gray Swan 间接提示注入（IPI）基准测试中位居领先，将针对 15 次自适应攻击尝试的攻击成功率降至 0.7%。
  Prompt injection resistance: When agents browse webpages, read emails, or inspect code, they can encounter hidden malicious instructions designed to hijack their task. Through adversarial training and automated red teaming, Argon leads the Gray Swan Indirect Prompt Injection (IPI) benchmark, cutting attack success across 15 adaptive attempts to 0.7%.

如需了解更多信息，请参阅 Gemini 4 Argon 模型卡。For more information, see the Gemini 4 Argon Model Card.

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Argon 能够投入更长时间、付出更多努力，解决高度复杂的科学、编程和智能体任务。这得益于通过 Gemini API 提供的业界领先的 100 万统一输入输出 token 上限。请阅读面向开发者和企业的文档，了解全新的续接协议，并确保根据自身需求进行适当配置。Argon 今日开始在全球推出：Argon works longer and harder to solve highly complex scientific, coding, and agentic problems. This is enabled by an industry-leading 1M unified input-output token limit via the Gemini API. Read through our documentation for developers and enterprises to learn about the new continuation protocol and ensure the appropriate setup for your needs. Argon is rolling out today globally:

• 面向开发者：使用 Gemini API 付费套餐进行构建；如果您订阅了 Google AI Ultra，还可以在 Google Antigravity、AI Studio 和 Android Studio 中试用。
  For developers: Build with the Gemini API paid tier and if you’re a Google AI Ultra subscriber, you can try it in Google Antigravity, AI Studio, and Android Studio.
• For enterprises: Try it in Gemini for business, the API, and in Google Antigravity.
• 对于日常用户：如果您订阅了 Google AI Ultra 或 Pro，即日起即可在 Gemini 应用和搜索中的 AI 模式中试用。
  For everyday users: Try it starting today in the Gemini app and AI Mode in Search if you’re a Google AI Ultra or Pro subscriber.
• 面向科学家和研究人员：立即申请，有机会免费使用 Google Antigravity 最高使用等级 6 个月（将分批安排入驻），具体取决于资格、名额和遴选结果。现已开放申请。
  For scientists & researchers: Apply for a chance to get access to Google Antigravity’s highest usage tier free of charge for 6 months (onboarded on a rolling basis), subject to eligibility, capacity, and selection. Applications are now open.
• 网络安全防御人员：申请加入 Fairwind Program，即可持续获得不受网络安全防护限制的 Argon 访问权限。
  For cybersecurity defenders: Apply to join the Fairwind Program to get access to Argon without cyber guardrails on a rolling basis.

Gemini 4 Argon 只是一个开始。我们期待为你带来 Gemini 4 家族的其他成员。Gemini 4 Argon is just the beginning. We’re looking forward to bringing you the rest of the Gemini 4 family.