Google Launches Gemini 3.5 Flash

Google DeepMind has unveiled Gemini 3.5 Flash, a new AI model designed for executing complex, agentic workflows with exceptional speed. This release marks a significant step in building more capable AI agents, prioritizing both intelligence and rapid task completion.

Gemini 3.5 Flash is positioned to deliver frontier-level performance for agents and coding tasks, handling intricate, long-horizon assignments that offer tangible real-world utility. The model is now accessible globally to consumers via the Gemini app and AI Mode in Google Search. Developers can access it through Google's Antigravity platform and the Gemini API in AI Studio and Android Studio, while enterprises can leverage it via Gemini Enterprise platforms.

Frontier Intelligence, Exceptional Speed

The new model boasts intelligence comparable to leading large language models but operates at the accelerated speeds characteristic of the Flash series. Google claims it is their most potent agentic and coding model to date, outperforming Gemini 3.1 Pro on key AI model benchmarks like Terminal-Bench 2.1 and GDPval-AA. Furthermore, it demonstrates strong multimodal understanding, achieving 84.2% on CharXiv Reasoning. Crucially, Gemini 3.5 Flash is reported to be four times faster than other frontier models in terms of output tokens per second, effectively eliminating the trade-off between quality and latency.

Agentic Tasks at Scale

This blend of speed and performance makes Gemini 3.5 Flash ideal for demanding agentic workflows. Tasks that previously took days or weeks can now be completed in a fraction of the time, often at reduced costs compared to other advanced models. It rapidly plans, builds, and iterates on solutions for real-world problems, from application development to financial document preparation.

When integrated with the updated Antigravity harness, Gemini 3.5 Flash can deploy collaborative subagents to tackle problems at scale. Under supervision, it reliably executes multi-step workflows and coding tasks while maintaining high performance. Examples include automatically renaming and categorizing unstructured assets, synthesizing research papers into playable games, and transforming legacy codebases.

Richer Graphics and Real-World Impact

Building on Gemini 3's multimodal capabilities, 3.5 Flash generates more interactive web UIs and graphics. This includes creating interactive animations, converting text descriptions into functional hardware designs, and rapidly developing branding concepts and UX approaches.

The model's agentic capabilities are already demonstrating significant value for enterprises. Partners like Shopify are using it for long-horizon data analysis to improve merchant growth forecasts. Macquarie Bank is piloting its use for accelerated customer onboarding by processing complex documents. Salesforce is integrating Gemini 3.5 Flash into its Agentforce to automate enterprise tasks with multi-agent coordination, while Ramp is enhancing OCR for invoices, and Xero is automating tax form preparation for small businesses. Databricks is employing agentic workflows for real-time data monitoring and issue diagnosis.

Personal AI Agents and Safety

Gemini 3.5 Flash now serves as the default model for the Gemini app and AI Mode in Search globally. New features, such as the personal AI agent Gemini Spark, leverage its capabilities to assist users with daily digital tasks. Google is also enhancing generative UI experiences in Search with its coding prowess.

Developed under Google's Frontier Safety Framework, Gemini 3.5 incorporates strengthened cyber and CBRN safeguards. Advanced safety training and mitigation techniques, including interpretability tools, aim to reduce harmful content generation and prevent unwarranted refusals of safe queries.