Google DeepMind拥有推出 Gemini 4 Carbon，是其迄今为止最强的模型。 Gemini 4 Carbon是Google为长相代理编码和网络安全防御而建造的前沿模型。 它在更新的v5.0人工分析智能指数上排名第1位，得分为59分。 对于开发者来说，捕获就是访问。 Carbon从一个经过审查的网络维权者团体开始，而不是公众API.
TL; DR 数据
- 大小：未披露参数计数和上下文窗口。 其前身Gemini 4 Argon有1,048,576个托肯语境。
- 仅Google主持。 无克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克克。
- 性能：17个公布的基准测试对Argon,GPT-6 Astra,Opus 5.5和Fable 5.1中的15个领先者。
- 最佳：在GraphWalks(256K至1M令牌)上为96.2%的BFS F1，而Argon为84.2%.
- 最差：OSWorld-2 1 81.5%，以87.2%的成绩落后于Claude Opus 5.5.
- 底线：最佳：最先进弱点发现、开发和补丁。 最糟的是你可能还不能叫它
Gemini 4"碳"是什么？.
碳是继Gemini 4 Argon之后的第二个Gemini 4型。 Google团队表示，模型的目标是艰苦，长期运行的工程工作。 内部团队看到Carbon在单项任务上跑了好几天。 例子包括：从大代码库和低等系统中取出取根和补丁微妙的bug.
Google还调制了Carbon，用于全网开发和多模式理解。 在WebDev Arena上，Carbon获得了89个埃洛分，在1769年达到4分。
Gemini 4 Carbon在基准测试上的表现如何？.
Google在其发布的帖子上公布了17行的比较。 碳在最高的思维环境运行。 按Google的评价方法，大多数竞争者的数字是每个提供者自行报告的。
代理编码：碳在终端-Bench 4.0(AA)上得分65.2%，以59.6%的成绩领先于Opus 5.5. 它在SWE-sweep上为达到 9.6%，以9.5%的成绩在GPT-6 Astra上略为领先。 GPT-6 Astra领先65.5%
计算机使用和知识工作：碳在Agents ' s Last Exam v1.1上达到77.4%. 在Vending-Bench 2上，它以16,484美元的银行结存结束，这是上市最高的。
长背景与科学：GraphWalks差距最大：GPT-6 Astra的比分为96.2%与71.8%. Carbon在Riemann Bench上也贴出80.0%.
为什么碳与网络安全相关？
Google帧碳环绕整个防御生命周期：找到，验证，再固定。 网易基准测试的评价没有护栏。
- 调查结果：88.2%的SEC-bench Pro，而85.4%的GPT-6 Astra。
- 剥削：54.8%在受剥削基姆，42.4%在GPT-6 Astra,34.5%在Opus 5.5。
- 补丁：71.0%在Collinear的CWE-bench上，对68.0%在Argon和GPT-6 Astra上。
Google用它的反重力带计算了SEC-bench Pro和OptitGym本身的得分。 利用Gym 运行与缓解关闭。 在内部，Carbon在生成安全代码方面表现出比Argon更高的2x以上成功。 Google团队表示，克罗姆团队在高品质补丁中发现"碳"超过10x，优于另一个实验室的模型。 Wiz报道了Carbon领导其网络渗透测试基准测试。
和Carbon有什么安全改变？
碳保持了Argon的分层堆积：训练，实时滥用防御，即时注射韧性和思维链监测。 Google报告了若干调整收益：
- 在Bench4.0终端成功作弊率降至0.00%，作弊未遂率为0.4%。
- 现场内部编码中的高度错位警报下降了近80%。
- 不支持的声称大约2x对Argon。
- 超覆盖率下降26%，服务不足率下降29%。
- 从Argon的0.7%下降到0.0 %。
这些是Google的内部或自营人物。 目前尚无法独立复制。
开发者如何访问 Gemini 4 Carbon?.
还没有，对于大多数。 Google正参与美国政府的自愿放行前测试过程。 本周，一部分网络维权者可以访问。 更受信任的合作伙伴通过Fairwind方案采取行动，该方案优先考虑政府、关键基础设施运营商和核心技术平台。 开发者，企业和消费者后来获得"碳"，没有给出日期。
定价符合Argon的入门率：每百万美元输入令牌2美元，每百万产出令牌10美元。 缓存输入值为95%。 引进期后，物价上涨至4元和20元。
Gemini 4 碳对竞争对手
基准测试行：Google 发布出站；对手分数大多按方法自报。
关键外卖
- Gemini 4 碳在人工分析指数v 5.0上排行第1,59.
- 领导SEC-bench Pro(88.2%)、ExpotitGym(54.8%)和CWE-bench(71.0%)。
- GraphWalks 长上下文达到 96.2%，最宽边距。
- Claude Opus 5.5仍然取胜OSWorld-2.1;GPT-6 Astra取胜FrontiersSWE.
- 从网络维权者开始进入，每百万信使2美元/10美元。
请检查access-date=中的日期值 (帮助) Google的发布帖子，评价方法和Fairwind Program页面。 并加入我们的通讯。 等等，你在电报里吗？现在你也可以加入我们的电报。
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Asif Razzaq是Marktechpost AI Media Inc.的首席执行官。 作为一个有远见的企业家和工程师，阿西夫致力于利用人工智能的潜力为社会造福。 他最近的努力是人工智能媒体平台的发布，该平台以深入报道机器学习和深层学习新闻而出名，这些新闻在技术上既可靠又为广大观众所容易理解。 该平台每月有超过200万次观看，表明其受观众欢迎。
本文由 AI宝库自动抓取并翻译，版权归原作者所有；如需查看原文请点下方链接。
Google DeepMind has introduced Gemini 4 Carbon, its strongest model to date. Gemini 4 Carbon is a frontier model from Google built for long-horizon agentic coding and cybersecurity defense. It ranks #1 on the updated v5.0 Artificial Analysis Intelligence Index with a score of 59. For developers, the catch is access. Carbon starts with a vetted group of cyber defenders, not the public API.
TL;DR
- Size: Parameter count and context window not disclosed. Its predecessor, Gemini 4 Argon, has a 1,048,576-token context.
- Runs on: Google-hosted only. No open weights, no self-hosting, no quantized variants.
- Performance: Leads 15 of 17 published benchmarks versus Argon, GPT-6 Astra, Opus 5.5 and Fable 5.1.
- Best: 96.2% BFS F1 on GraphWalks (256K to 1M tokens), versus 84.2% for Argon.
- Worst: 81.5% on OSWorld-2.1, trailing Claude Opus 5.5 at 87.2%.
- Bottom line: Best: state-of-the-art vulnerability finding, exploitation and patching. Worst: you probably cannot call it yet.
What is Gemini 4 Carbon?
Carbon is the second Gemini 4 model, following Gemini 4 Argon. Google team states that the model targets hard, long-running engineering work. Internal teams saw Carbon run for days on single tasks. Examples include root-causing and patching subtle bugs across large codebases and low-level systems.
Google also tuned Carbon for full-stack web development and multimodal understanding. On WebDev Arena, Carbon gained 89 Elo points to reach #4 at 1769.
How does Gemini 4 Carbon perform on benchmarks?
Google published a 17-row comparison in its launch post. Carbon was run at the highest thinking setting. Most rival numbers are self-reported by each provider, per Google’s evaluation methodology.
Agentic coding: Carbon scores 65.2% on Terminal-Bench 4.0 (AA), ahead of Opus 5.5 at 59.6%. It hits 9.6% on SWE-sweep, narrowly ahead of GPT-6 Astra at 9.5%. On FrontierSWE, GPT-6 Astra leads at 65.5% versus Carbon’s 61.2%.
Computer use and knowledge work: Carbon reaches 77.4% on Agents’ Last Exam v1.1. On Vending-Bench 2, it ends with a $16,484 bank balance, the highest listed.
Long context and science: GraphWalks is the widest gap: 96.2% versus 71.8% for GPT-6 Astra. Carbon also posts 80.0% on RiemannBench.
Why does Carbon relevant for cybersecurity?
Google frames Carbon around the full defense lifecycle: find, validate, then fix. Cyber benchmarks were evaluated without guardrails.
- Finding: 88.2% on SEC-bench Pro, versus 85.4% for GPT-6 Astra.
- Exploiting: 54.8% on ExploitGym, versus 42.4% for GPT-6 Astra and 34.5% for Opus 5.5.
- Patching: 71.0% on Collinear’s CWE-bench, versus 68.0% for Argon and GPT-6 Astra.
Google computed SEC-bench Pro and ExploitGym scores itself, using its Antigravity harness. ExploitGym ran with mitigations off. Internally, Carbon showed more than 2x higher success at generating secure code than Argon. Google team states that the Chrome team found Carbon over 10x better than another lab’s model at high-quality patches. Wiz reports Carbon leading its web penetration testing benchmarks.
What safety changes ship with Carbon?
Carbon keeps Argon’s layered stack: training, real-time misuse defenses, prompt-injection resilience and chain-of-thought monitoring. Google reports several alignment gains:
- Successful cheating on Terminal-Bench 4.0 fell to 0.0%, with cheating attempts at 0.4%.
- High-severity misalignment alerts in live internal coding dropped by almost 80%.
- Unsupported claims fell roughly 2x versus Argon.
- Overreach fell 26% and under-service fell 29%.
- Attack success on Gray Swan’s Indirect Prompt Injection benchmark is 0.0%, down from Argon’s 0.7%.
These are Google’s internal or self-run figures. Independent replication is not yet available.
How can developers access Gemini 4 Carbon?
Not yet, for most. Google is participating in the U.S. government’s voluntary pre-release testing process. This week, a subset of cyber defenders gets access. More trusted partners follow through the Fairwind Program, which prioritizes governments, critical infrastructure operators and core tech platforms. Developers, businesses and consumers get Carbon later, with no date given.
Pricing matches Argon’s introductory rate: $2 per million input tokens and $10 per million output tokens. Cached input is 95% off. After the introductory period, prices rise to $4 and $20.
Gemini 4 Carbon vs competitors
Benchmark rows: Google launch post; rival scores mostly self-reported per methodology.
Key Takeaways
- Gemini 4 Carbon ranks #1 on Artificial Analysis Index v5.0 at 59.
- It leads SEC-bench Pro (88.2%), ExploitGym (54.8%) and CWE-bench (71.0%).
- GraphWalks long context hits 96.2%, its widest margin.
- Claude Opus 5.5 still wins OSWorld-2.1; GPT-6 Astra wins FrontierSWE.
- Access starts with cyber defenders at $2/$10 per million tokens.
Check out the Google’s launch post, the evaluation methodology and the Fairwind Program page. Also, feel free to follow us on Twitter and don’t forget to join our 150k+ML SubReddit and Subscribe to our Newsletter. Wait! are you on telegram? now you can join us on telegram as well.
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Asif Razzaq is the CEO of Marktechpost AI Media Inc.. As a visionary entrepreneur and engineer, Asif is committed to harnessing the potential of Artificial Intelligence for social good. His most recent endeavor is the launch of an Artificial Intelligence Media Platform, Marktechpost, which stands out for its in-depth coverage of machine learning and deep learning news that is both technically sound and easily understandable by a wide audience. The platform boasts of over 2 million monthly views, illustrating its popularity among audiences.
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