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Gemini 3.6 Flash、3.5 Flash-Lite 以及 3.5 Flash Cyber
Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

原始链接: https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-6-flash-3-5-flash-lite-3-5-flash-cyber/

为了支持对高效、高性能 AI 智能体日益增长的需求，Google 推出了 Gemini Flash 系列的多项更新： * **Gemini 3.6 Flash**：作为全新的“主力”模型，它提升了编码和多模态能力。该模型大幅提高了效率，整体输出 Token 使用量减少了 17%（在特定基准测试中最高可达 65%），同时将成本降低至每百万输入 Token 1.50 美元，每百万输出 Token 7.50 美元。 * **Gemini 3.5 Flash-Lite**：针对极致速度和性价比进行了优化，该模型每秒可输出 350 个 Token，非常适合高速智能体工作流。 * **Gemini 3.5 Flash Cyber**：一款专注于安全的专用模型，集成了“CodeMender”智能体，旨在提供先进的网络安全编排。 展望未来，Google 目前正在测试功能更强大的 Gemini 3.5 Pro，并已正式启动下一代 Gemini 4 的预训练工作。这些发布凸显了 Google 的核心目标：为构建可扩展 AI 智能体的开发者降低延迟、提高可靠性并降低成本门槛。

谷歌近期发布的 Gemini 3.6 Flash、3.5 Flash-Lite 和 3.5 Flash Cyber 在 Hacker News 上引发了质疑。虽然部分用户认可谷歌加快发布节奏并专注于核心模型性能的做法，但另一些人仍对其发展方向持批评态度。 讨论的主要观点包括： * **基准测试的担忧：** 评论者批评谷歌仅将这些模型与其前代产品进行对比，而非与当前的前沿模型或国际竞争对手进行比较。 * **清晰度问题：** 用户指出所提供的性能统计数据存在不一致，导致人们对具体的效率提升感到困惑。 * **竞争生存能力：** 许多参与者对这些新模型表示失望，认为它们在成本和智能表现上均落后于 GLM-5.2 等其他产品。 * **战略前景：** 尽管存在质疑，仍有人希望谷歌加速开发能够最终恢复其竞争优势，特别是在多模态能力方面。 总体而言，社区情绪较为冷淡，许多人质疑在竞争日益激烈且高性能 AI 层出不穷的市场环境下，这些更新的价值主张何在。
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原文

Developers and customers building production AI agents need higher token efficiency, lower latency, and more reliable performance. Our Flash series of models is built to meet the sweet spot of efficiency and quality to enable scaling agentic workflows. Building on Gemini 3.5 Flash, we’re introducing new Gemini models:

  • 3.6 Flash: Our workhorse model that delivers better coding, knowledge work, and multimodal performance. According to the Artificial Analysis Index, it reduces output token usage by 17% compared to 3.5 Flash, and in some benchmarks like DeepSWE by Datacurve, we observe up to 65%, all at a lower cost per output token.
  • 3.5 Flash-Lite: Our fastest, most cost-effective 3.5-class model, delivering 350 output tokens per second according to the Artificial Analysis Index, also significantly outperforming prior Flash-Lite generations in agentic workflows.
  • 3.5 Flash Cyber in CodeMender: Successful cybersecurity applications require careful orchestration of a model alongside an agent infrastructure. We’re introducing a combination of a new, highly efficient, specialized cyber-focused model paired with our CodeMender code security agent that delivers competitive performance at the frontier.

Beyond today’s releases, Gemini 3.5 Pro is currently testing with partners and we plan to make it broadly available as soon as it’s ready. In parallel, our team is already focusing on building the next generation of models. We have started our most ambitious pre-training run yet, for Gemini 4, and are excited by the progress.

Gemini 3.6 Flash builds directly on developer and customer feedback from 3.5 Flash. 3.6 Flash not only delivers a step up in coding and knowledge work, but it does this while meaningfully improving token efficiency. For example, on the Artificial Analysis Index, we see 3.6 Flash consuming 17% fewer output tokens than 3.5 Flash. It also takes fewer reasoning steps and tool calls to accomplish multi-step workflows.

This enhanced efficiency is also combined with a lower price than 3.5 Flash. At $1.50/1M input tokens and $7.50/1M output tokens, 3.6 Flash reduces the overall cost per agentic task, making agents more cost-effective to build and run.

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