Gemini 4 碳:我们的下一个前沿模型
今天,我们宣布下一个前沿模型:Gemini 4 Carbon,我们拥有最先进网络安全和长视野能力的最强模型。
在最近更新的人工分析智能指数v5.0中,碳排名第1位为59位。 显示在编码和代理任务以及网络安全防御的关键能力方面都取得了重大收益,在SEC-bench Pro(88.2%)中发现弱点、开发Gym(54.8%)和CWE-bench(71.0%)进行补丁。 在内部的基准测试上,Carbon在生成安全代码方面推动强大的提升,在与我们自己的团队的现场编码环境中,显示降低了错配率和制造率。
以两星期前的Gemini 4 Argon为基础,我们的研究人员和模型正在携手努力,以更快地提高能力,同时同时加强我们的保障。
我们正在采取审慎的推出方法,并积极参与美国政府的自愿程序,进行释放前模型测试。 从本周开始,我们将向一些网络维权者提供Carbon,并将通过我们的Fairwind方案逐步逐步接触更多的值得信任的伙伴。 我们继续收集反馈,在护栏上传播,然后尽快通过产品表面向开发商、企业和消费者提供碳。
Gemini 4 Carbon将以与Argon相同的引入价格1,每百万输入令牌2美元,每百万输出令牌10美元,缓存输入令牌以95%的输入令牌价格定价。
改进具有挑战性的长期任务编码和推理
碳设计是为了承担更难,更远的工程问题,碳建设是为了持续的代理工作流程。 在内部,我们的团队已经看到碳运行持续数天通过死端解决复杂的,多步骤的工程任务,如根-诱发和补合微妙的bug 跨越大代码库和低层系统。
根据用户的反馈,我们着重改进各种领域的模型性能,包括编码、代理和科学任务,以及全网开发和多式联运。 随着网络开发中产出和文物质量的提高,Carbon jump + 89 elo在WebDev Arena上指向土地4号(1768年).
最先进网络安全性能帮助构建安全系统。
Gemini 4 Carbon实现了网络安全能力的重大飞跃。 它实现了整个网络安全防御生命周期的最先进性能——脆弱性检测,验证,以及补救。
我们的团队已经看到网络防御的强大进展。 在内部的基准测试上,Carbon在生成安全码在Argon上取得了2x以上的成功率提升。 另一个例子是,Chrome团队报告说,Carbon在生成高质量的补丁时,比另一个实验室的大型前沿模型更好的表现超过10X. Wiz,我们领先的云安全平台,也观测到Carbon在基准测试上领先进行网络渗透测试,这是Wiz的Scan for Good倡议的核心能力。
跨越关键外部基准测试(在没有护栏的情况下评估)的碳:
- 找出真正的弱点:网络安全防御的核心是找出真正的弱点。 Carbon在SEC-bench Pro上实现了88.2%的最先进,自主地揭示了隐藏在现实世界软件中的复杂缺陷。
- 通过剥削验证风险:为了优先确定哪些脆弱性可以首先得到补救或补救,网络维权者越来越多地依靠模型来检查哪些脆弱性是可以利用的。 碳在大众开发上设置了新的最先进基准测试 ExplitGym(54.8%).
- 找出根源:最终在查明脆弱性后,找出根源是网络安全防御生命周期的关键一步。 碳在Collinear的CWE-bench上达到了71.0%,将经验证的结论直接转化为工作代码修正。
推进前沿示范安全保障。
Gemini 4 Carbon基于相同的多层安全和安保堆积的Argon——结合模型训练,实时滥用防御,即时注射韧性,以及思维链监测。 尤其是,我们在与Argon进行模式调整方面取得了显著进展,并在我们的安全和安保报告中报告了它以一致方式行事的倾向。 与Carbon一起,我们挑战自己在对齐方面更进一步,并训练模型以正确的方式应对复杂或高压的任务。
- 减少捷径和漏洞开发:通过Carbon,我们在确保高质量编码性能的同时,进一步减少在培训方面的捷径尝试。 碳将终端-奔驰4.0%至0.0 %的成功作弊率降低到0.4%——所有这一切都提高了总体准确度。 在与我们内部团队的直播编码环境中,我们观察到高高度错配警报下降了近80%.
- 提高透明度和诚实度:在我们的内部测试中,Carbon 削减没有支持的声称在Argon上空大约2x. 它直接向交付品提出方法上的告诫,或扣压被封锁的行动,明确列出仍然需要什么,而不是围绕缺失的证据捏造或套用。
- 面对含糊不清的问题,改进与用户的协作:Carbon在采取行动之前,不应猜测或强迫前进的道路,而应先向用户检索相关来源和显示差异,因此,用户应看到与Carbon更好的协作经验。
- 在不越轨的情况下进行跟踪:碳同时将超覆盖减少26%,服务不足减少29%,从而更可靠地执行多步骤计划,同时尊重项目限制并严格在范围之内。
- 抵制提示词注入:Argon之前曾领导过灰天鹅的间接提示词注入(IPI)基准测试在提示词注入的抵抗力,攻击成功率非常低,只有0.7%,Carbon达到了0.0 % ——抵制每一次评估的攻击尝试。
很快会来到开发商、企业和消费者那里
推进边界需要迅速前进,同时继续考虑部署。 有了Gemini 4 Carbon,我们的目标是在软件工程和网络安全防御方面实现有意义的飞跃,同时不损害安全或可靠性。 我们渴望看到最初的网络维权者如何使用这个模式
本文由 AI图鉴自动抓取并翻译,版权归原作者所有;如需查看原文请点下方链接。
Gemini 4 Carbon: our next frontier model
Today, we’re announcing the next frontier model: Gemini 4 Carbon, our strongest model with state-of-the-art cybersecurity and long horizon capabilities.
Carbon ranks #1 on the recently updated v5.0 of Artificial Analysis Intelligence Index at 59. It shows significant gains across coding and agentic tasks as well as across key capabilities critical for cybersecurity defense, landing a firm lead in SEC-bench Pro (88.2%) for finding vulnerabilities, ExploitGym (54.8%) for exploitation, and CWE-bench (71.0%) for patching. On internal benchmarks, Carbon drives a strong uplift in generating secure code, and in live coding environments with our own teams it shows reduced misalignment and fabrication rates.
Building on Gemini 4 Argon, which was launched two weeks ago, Carbon illustrates the pace at which we’re pushing the frontier forward. Our researchers and models are working hand in hand to advance capabilities faster, while strengthening our safeguards in tandem.
We're taking a deliberate approach to rollout and are actively engaged in the U.S. government’s voluntary process for pre-release model testing. Starting this week, we will make Carbon available to a subset of cyber defenders and will gradually phase access to additional trusted partners through our Fairwind Program. We’re continuing to gather feedback and iterate on guardrails before making Carbon available to developers, businesses, and consumers via our product surfaces as soon as possible.
Gemini 4 Carbon will launch at the same introductory price 1 as Argon at $2 per million input tokens and $10 per million output tokens, with cached input tokens priced at 95% off input token price.
Improving coding and reasoning for challenging, long-horizon tasks
Designed to take on much harder, long-horizon engineering problems, Carbon is built for sustained agentic workflows. Internally, our teams have seen Carbon run for days to persist through dead ends to tackle complex, multi-step engineering tasks like root-causing and patching subtle bugs across large codebases and low-level systems.
Building on user feedback, we focused on improving model performance across a variety of domains, including coding, agentic, and scientific tasks, as well as full-stack web development and multimodal understanding. With improved quality of output and artifacts in web development, Carbon jumps +89 elo points to land at #4 (1768) on WebDev Arena.
State-of-the-art cybersecurity performance to help build secure systems
Gemini 4 Carbon delivers a significant leap in cybersecurity capabilities. It achieves state-of-the-art performance across the cybersecurity defense lifecycle — vulnerability detection, validation, and remediation.
Our teams are already seeing strong gains in cyberdefense. On internal benchmarks, Carbon achieves more than 2x uplift in success rate for generating secure code over Argon. As another example, the Chrome team has reported that Carbon performed more than 10X better than another lab's large frontier model when generating high quality patches. Wiz, our leading Cloud security platform, also observes Carbon leading on benchmarks for web penetration testing, a core capability for Wiz's Scan for Good initiative.
Carbon excels across key external benchmarks (evaluated without guardrails):
- Finding real vulnerabilities: Core to cybersecurity defense is finding real vulnerabilities. Carbon achieves a state-of-the-art 88.2% on SEC-bench Pro, autonomously uncovering complex flaws buried in real-world software.
- Validating risk through exploitation: To prioritize which vulnerabilities to remediate first or remediate at all, cyber defenders increasingly rely on models to check which vulnerabilities are exploitable. Carbon sets a new state-of-the-art on the popular exploitation benchmark ExploitGym (54.8%).
- Patching at the root cause: Ultimately after identifying the vulnerabilities, fixing the root cause is a critical step in the cybersecurity defense lifecycle. Carbon reaches 71.0% on Collinear’s CWE-bench, turning validated findings directly into working code fixes.
Advancing frontier model safety & security
Gemini 4 Carbon builds on the same multi-layered safety and security stack of Argon — combining model training, real-time misuse defenses, prompt-injection resilience, and chain-of-thought monitoring. In particular, we made significant strides in model alignment with Argon, and reported its propensities to behave in an aligned way in our Safety and Security report. With Carbon, we challenged ourselves to go a step further on alignment, and trained the model to respond to complex or high-pressure tasks in the right way.
- Reducing shortcuts and loophole exploitation: With Carbon, we further mitigated shortcut attempts in training while ensuring high-quality coding performance. Carbon reduced successful cheating on Terminal-Bench 4.0 to 0.0%, with attempts to cheat dropping to 0.4% — all while improving overall accuracy. In live coding environments with our internal teams, we observed that high-severity misalignment alerts dropped by almost 80%.
- Greater transparency and honesty: In our internal testing, Carbon cuts unsupported claims by approximately 2x over Argon. It puts methodological caveats directly into the deliverable or withholds blocked actions with a clear list of what remains required, rather than fabricating or hedging around missing evidence.
- Improved collaboration with the user in the face of ambiguity: Rather than guessing or forcing a path forward, Carbon retrieves the relevant sources and surfaces discrepancies to the user before acting — as a result, users should observe a much better collaborative experience with Carbon.
- Following through without overstepping: Carbon simultaneously reduced overreach by 26% and under-service by 29% resulting in much more reliable execution of multi-step plans end-to-end while respecting project constraints and staying strictly within scope.
- Resisting prompt injection: While Argon previously led the Gray Swan’s Indirect Prompt Injection (IPI) Benchmark in prompt injection resistance with a very low 0.7% attack success rate, Carbon achieves 0.0% — resisting every evaluated attack attempt.
Coming soon to developers, businesses, and consumers
Pushing the frontier forward requires moving fast while remaining deliberate about deployment. With Gemini 4 Carbon, our goal is to deliver meaningful leaps in software engineering and cybersecurity defense without compromising on safety or reliability. We’re eager to see how the initial cohort of cyber defenders use this model and we look forward to bringing Carbon to developers, businesses, and consumers soon.
Auto-fetched and translated by AI Atlas. All rights belong to the original author.