大模型
siliconangle.com ·
@Maria Deutscher
Google推出两款Gemini 3.8模型,具备先进推理能力
Google发布Gemini 3.8 Flash和Gemini 3.8 Flash Cyber,后者专为网络安全研究人员设计,两者基于相同技术基础。
AI推荐理由 Google发布两款Gemini 3.8模型,包括针对网络安全研究的专用版本,信息明确且时效性强,对AI模型和网络安全领域有实际价值。
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正文
更新于美国东部时间2026年9月2日20:04
人工智能
谷歌推出两款具有尖端推理能力的Gemini 3.8模型
作者:Maria Deutscher
距离上次大型语言模型发布仅三周,谷歌有限责任公司今日推出Gemini 3.8 Flash和Gemini 3.8 Flash Cyber。
这两款LLM基于相同的技术基础。主要区别在于,Gemini 3.8 Flash是通用模型,而Gemini 3.8 Flash Cyber专为网络安全研究人员设计。后者通过一项名为Fairwind计划的新早期访问计划提供,该计划也在今日首次亮相。
谷歌通过让Gemini 3.8 Flash完成16项人工智能基准测试来对其进行检验。据谷歌称,它在其中9项测试中优于Claude Opus 5和GPT 5.6 Sol。
该模型更准确完成的一项评估是Terminal-Bench 1.1,该测试衡量LLM处理多步骤编码任务的能力。其他基准测试涵盖金融数据分析和图表理解等用例。
Gemini 3.8 Flash在竞争对手LLM表现更好的基准测试中也取得了有竞争力的性能。它在DeepSWE-1.1上得分73.7%,该测试评估AI模型自动化长周期编码任务的能力。这使得Gemini 3.8 Flash比GPT-5.6 Sol领先1%,比Opus 5落后零点几个百分点。
“这些性能提升源于一个核心设计选择:3.8 Flash更努力地工作,”谷歌高管Tulsee Doshi和Raluca Ada Popa在博客文章中写道。“在复杂任务上,它表现出更大的勤奋——执行额外的推理步骤,并迭代调用工具。有时,模型可能会使用更多令牌来最大化性能,尤其是在更高努力水平下。”
谷歌今日推出的另一款LLM Gemini 3.8 Flash Cyber也提供了有竞争力的性能。它在CyberGym基准测试中得分86.2%,该测试检验LLM识别C和C++代码中漏洞的能力。Claude Mythos 5得分83.8%,而GPT-5.6 Sol得分83.6%。
Gemini 3.8 Flash Cyber通过名为Fairwind计划的早期访问计划提供。该计划面向政府机构、关键基础设施运营商以及负责“保护广泛软件基础”的科技公司。
谷歌表示,推出时有超过650名参与者。该群体包括Snowflake Inc.、CrowdStrike Holdings Inc.、Datadog Inc.等主要软件公司。
Fairwind计划参与者可以将Gemini 3.8 Flash Cyber与一种名为CodeMender的技术结合使用。它是一个工具集,包含提示、代码文件和其他技术资产。CodeMender由谷歌DeepMind创建,旨在提高LLM发现漏洞、评估漏洞严重性并开发补丁的能力。
谷歌工程师正在内部使用Gemini 3.8 Flash Cyber来加快工作速度。据该公司称,Chrome的开发人员发现,该LLM生成的浏览器漏洞“正确补丁数量是竞争对手的2.6倍”。另一个谷歌团队使用Gemini 3.8 Flash Cyber发现了一个“关键的基础性漏洞”,手动发现该漏洞需要数月时间。
图片:谷歌
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查看原文(中文正文为 AI 翻译)
UPDATED 20:04 EDT / SEPTEMBER 02 2026
AI
Google launches two Gemini 3.8 models with cutting-edge reasoning capabilities
by Maria Deutscher
Just three weeks after its last large language model release, Google LLC today launched Gemini 3.8 Flash and Gemini 3.8 Flash Cyber.
The two LLMs are based on the same technical foundation. The primary difference is that Gemini 3.8 Flash is a general-purpose model while Gemini 3.8 Flash Cyber is designed for cybersecurity researchers. The latter algorithm is available through a new early access initiative, the Fairwind Program, that also made its debut today.
Google put Gemini 3.8 Flash to the test by having it complete 16 artificial intelligence benchmarks. According to Google, it outperformed Claude Opus 5 and GPT 5.6 Sol across nine of the tests.
One of the evaluations that the model completed more accurately is Terminal-Bench 1.1, which measures LLMs’ ability to tackle multistep coding tasks. The other benchmarks spanned use cases such as financial data analysis and chart comprehension.
Gemini 3.8 Flash also achieved competitive performance on the benchmarks that rival LLMs completed better. It scored 73.7% on DeepSWE-1.1, which evaluates AI models’ ability to automate long-horizon coding tasks. That put Gemini 3.8 Flash 1% ahead of GPT-5.6 Sol and a few fractions of a percent behind Opus 5.
“These performance gains stem from a core design choice: 3.8 Flash works harder,” Google executives Tulsee Doshi and Raluca Ada Popa wrote in a blog post. “On complex tasks, it exhibits greater diligence — executing extra reasoning steps, and calling tools iteratively. At times, the model might use more tokens to maximize performance, especially at higher effort levels.”
Gemini 3.8 Flash Cyber, the other LLM that Google introduced today, also offers competitive performance. It scored 86.2% on the CyberGym benchmark, which tests LLMs’ ability to spot vulnerabilities in C and C++ code. Claude Mythos 5 scored 83.8% while GPT-5.6 Sol managed 83.6%.
Gemini 3.8 Flash Cyber is available through an early access program called the Fairwind Program. It’s open to government agencies, critical infrastructure operators and tech firms responsible for “securing widespread software foundations.”
Google says there are more than 650 participants on launch. The group includes Snowflake Inc., CrowdStrike Holdings Inc., Datadog Inc. and other major software companies.
Fairwind Program participants can use Gemini 3.8 Flash Cyber with a technology called CodeMender. It’s a harness, a collection of prompts, code files and other technical assets. CodeMender was created by Google DeepMind to improve LLMs’ ability to find vulnerabilities, evaluate their severity and develop patches.
Google engineers are using Gemini 3.8 Flash Cyber internally to speed up their work. According to the company, the developers of Chrome found that the LLM produces “2.6 times more correct patches” to browser vulnerabilities than rivals. Another Google team used Gemini 3.8 Flash Cyber to find a “critical foundational vulnerability” that would have taken months to uncover manually.
Image: Google
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