Google Introduces Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

Google Introduces Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber Google has announced new Gemini models tailored for scaling AI agents with enhanced token efficiency, latency, and reliability: Gemini 3.6 Flash, Gemini 3.5 Flash-Lite, and the specialized security model Gemini 3.5 Flash Cyber. Gemini 3.6 Flash cuts output token usage by 17% compared to 3.5 Flash and is priced at $1.50 per 1M input tokens and $7.50 per 1M output tokens. Gemini 3.5 Flash-Lite delivers 350 output tokens per second at $0.30 per 1M input tokens and $2.50 per 1M output tokens. Gemini 3.5 Flash Cyber is paired with the CodeMender code security agent and will be restricted to governments and trusted partners in a limited pilot. Gemini 3.5 Pro is currently in partner testing, and Google has begun pre-training for Gemini 4. Gemini 3.6 Flash Efficiency and Benchmarks Gemini 3.6 Flash is engineered for coding, knowledge work, and multimodal tasks while reducing token usage and reasoning steps. Benchmarks reflect gains over 3.5 Flash, including DeepSWE (49% vs. 37%), MLE Bench (63.9% vs. 49.7%), OSWorld-Verified (83.0% vs. 78.4%), and GDPval-AA v2 (1421 vs. 1349). It also integrates client-side computer use and includes safety safeguards against CBRN and cyber offense misuses. Gemini 3.5 Flash-Lite Throughput and Scaling Designed for high-throughput, low-latency workloads such as agentic search and document processing, 3.5 Flash-Lite operates at 350 output tokens per second. It allows developers to configure thinking levels for varied task complexities and includes computer use as a built-in tool. The model scores higher than 3.1 Flash-Lite across metrics like Terminal-Bench 2.1 (54% vs. 31%) and surpasses 3 Flash on benchmarks including SWE-Bench Pro (54.2% vs. 49.6%). Cybersecurity Specialization and Rollout Gemini 3.5 Flash Cyber is fine-tuned to detect, validate, and patch software vulnerabilities within CodeMender, which orchestrates multiple agents to generate consolidated reports. Due to dual-use security concerns, access is restricted to governments and trusted partners through a limited pilot. Meanwhile, Gemini 3.6 Flash and 3.5 Flash-Lite are available immediately across Google AI Studio, Android Studio, the Gemini Enterprise Agent Platform, and consumer apps, with Flash-Lite rolling out in Google Search.

Google 推出 Gemini 3.6 Flash、3.5 Flash-Lite 与 3.5 Flash Cyber 模型 Google 发布了针对 AI Agent 规模化工作流打造的全新 Gemini 模型系列，包括性能与效率提升的 3.6 Flash、高吞吐低延迟的 3.5 Flash-Lite，以及专用于代码安全漏洞修复的 3.5 Flash Cyber。 Gemini 3.6 Flash 输出 token 消耗比 3.5 Flash 减少 17%，输入和输出价格分别为每百万 token 1.50 美元与 7.50 美元。 Gemini 3.5 Flash-Lite 达到每秒 350 输出 token，定价为每百万输入 token 0.3 美元、输出 token 2.5 美元。 3.5 Flash Cyber 结合 CodeMender 用于代码漏洞检测与修复，将通过受限试点项目提供给政府和受信合作伙伴。 Gemini 3.5 Pro 正在与合作伙伴进行测试，同时团队已启动 Gemini 4 的预训练。 Gemini 3.6 Flash 提升效率与多模态表现 3.6 Flash 在编程、知识工作和多模态能力上较 3.5 Flash 均有增强。测试显示其在 Artificial Analysis Index 上减少了 17% 的输出 token 消耗，在 DeepSWE 测试中降幅最高达 65%，并且推理步骤与工具调用更少。该模型定价为每百万输入 token 1.50 美元、输出 token 7.50 美元，支持计算机使用内置客户端工具，并在 DeepSWE（49% 对比 37%）和 MLE Bench 等基准上取得提升。安全方面增强了应对 CBRN 与网络进攻滥用的前沿防护。 Gemini 3.5 Flash-Lite 主打高吞吐与 Agent 扩展 3.5 Flash-Lite 输出速度达每秒 350 token，每百万输入 token 为 0.3 美元、输出 token 为 2.5 美元，适用于 Agent 搜索与文档处理等高并发场景。开发者可根据负载调节其思考级别，在 Terminal-Bench 2.1 与 GDM-MRCR v2 等基准上显著超越 3.1 Flash-Lite，甚至在 SWE-Bench Pro 等测试中超过 3 Flash。该模型同样内置了计算机使用工具支持。 3.5 Flash Cyber 安全应用与后续模型规划 3.5 Flash Cyber 基于 3.5 Flash 微调，专用于寻找并修复代码安全漏洞。其与 CodeMender 代码安全 Agent 配合运作，在 CyberGym 基准测试中展现出前沿竞争力。鉴于技术双重用途，该模型将仅通过受限试点计划提供给政府及受信合作伙伴。此外，Gemini 3.5 Pro 目前正处于合作伙伴测试阶段，团队亦已启动 Gemini 4 的预训练工作。

Jul 21, 2026 | Our newest Gemini models deliver the efficiency, latency, and reliability to build AI agents at scale. 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. 3.6 Flash: More efficient and better quality than 3.5 Flash 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. 3.6 Flash shows better token efficiency and reduced verbosity than 3.5 Flash in an OSWorld verified task (API) Even while being more efficient, 3.6 Flash sees performance gains compared to 3.5 Flash across use cases: 3.6 Flash delivers higher precision with fewer unwanted code edits and reduced execution loops, as seen in DeepSWE (49% vs. 37%), and shows significant improvement in ML Research, as seen in MLE Bench (63.9% vs. 49.7%). It has improved computer use capabilities as seen in OSWorld-Verified (83.0% vs. 78.4%). Computer use is now a built-in client side tool via the Gemini API and Gemini Enterprise. It outperforms 3.5 Flash in knowledge work, as shown by benchmarks like GDPval-AA v2 (1421 vs. 1349). Customers like Hebbia and Harvey have found it particularly capable at multimodal tasks like document parsing, chart and data analysis, and report drafting. Customers report 3.6 Flash is a step forward in both cost and quality, balancing token efficiency, accuracy, and speed across complex workflows and knowledge-based tasks: Built with safety 3.6 Flash is shipping with enhanced Frontier Safety safeguards in the domains of Chemical, Biological, Radiological, and Nuclear (CBRN) and cyber offense misuses. These safeguards make the model substantially more resistant to jailbreaks. At the same time, the model has been trained to minimize refusals for beneficial uses. For more information, see the 3.6 Flash model card. 3.5 Flash-Lite: Built to scale agentic workflows Beyond Flash, we’re also releasing Gemini 3.5 Flash-Lite, designed for both low-latency tasks and tasks where high throughput is critical for developers workflows, like agentic search and document processing. 3.5 Flash-Lite is the fastest model in the 3.5 series. As measured by Artificial Analysis , it runs at 350 output tokens/s. Priced at $0.3/1M input tokens and $2.5/1M output tokens and with significantly better quality than 3.1 Flash-Lite, 3.5 Flash-Lite offers a strong price-to-performance ratio for developers and customers running high throughput production traffic. 3.5 Flash-Lite executes high volume tasks at a lower latency than 3.5 Flash. 3.5 Flash-Lite enables efficient scaling for agentic systems. Across thinking levels, the model significantly outperforms 3.1 Flash-Lite. Depending on the workload, developers can configure the model to prioritize low-latency, low-cost execution for high-volume tasks with the minimal and low thinking levels, or engage higher thinking levels to process multi-step subagent workloads. The model now also has computer use as a built-in tool to reliably support these agentic tasks across surfaces. It’s a significant step up in coding and agentic tasks as seen in Terminal-Bench 2.1 (54% vs 31%), long context as seen in GDM-MRCR v2 (72.2% vs. 60.1%), and real-world task execution as seen in GDPval-AA v2 (1140 vs. 642). In fact, on many agentic and coding evals, 3.5 Flash-Lite even outperforms 3 Flash, including on SWE-Bench Pro (54.2% vs. 49.6%) and OSWorld-Verified (74.0% vs. 65.1%), making it a faster & more capable option for workloads on both 2.5 and 3 Flash. Early customers of 3.5 Flash-Lite are highlighting its unique combination of speed, intelligence, and cost efficiency for scaling agentic workflows and data processing tasks: For more information about the model, see the 3.5 Flash-Lite model card. 3.5 Flash Cyber in CodeMender: finding and fixing vulnerabilities efficiently AI models have become capable of finding security vulnerabilities faster than current systems can fix them. Tackling this growing threat requires an approach to securing software that is highly capable and efficient. Flash’s performance and efficiency makes it an ideal foundation to detect, validate, and patch code security issues at scale. Gemini 3.5 Flash Cyber is built on top of 3.5 Flash, and fine-tuned for finding and fixing cybersecurity vulnerabilities at a lower price per token than larger models. Within CodeMender, which uses multiple 3.5 Flash Cyber agents working together to produce a single combined report, 3.5 Flash Cyber reaches competitive performance at the frontier on the popular benchmark CyberGym. Given the dual-use nature of this technology, we have taken an intentional approach to deploying 3.5 Flash Cyber. The model will be exclusively available to governments and trusted partners via CodeMender soon as part of a limited-access pilot program. This will give frontline defenders a head start in finding and fixing critical vulnerabilities before they can be exploited, while mitigating against broader misuse. 3.6 Flash and 3.5 Flash-Lite: Get started today 3.6 Flash and 3.5 Flash-Lite are available starting today: For developers in the Gemini API via Google AI Studio and Android Studio . 3.6 Flash is also available in Google Antigravity . Get started with the Developer Guide . For enterprises in Gemini Enterprise Agent Platform . 3.6 Flash is also available in the Gemini Enterprise app . For everyone via the Gemini app . 3.5 Flash-Lite is also rolling out in Google Search. As you start building with 3.6 Flash and 3.5 Flash-Lite, we welcome your feedback to improve future Gemini models and look forward to releasing 3.5 Pro soon. Get the latest news from Google in your inbox Sign up for our newsletters with product updates, event information, special offers, and more. Your information will be used in accordance with Google's privacy policy. You may opt out at any time.