Google Unveils Gemini 3.5: A Leap in AI Capabilities for Agents and Coding Google DeepMind has launched Gemini 3.5, a new family of AI models designed to enhance complex workflows and coding tasks. The release includes 3.5 Flash, a model optimized for speed and performance, and 3.5 Pro, which is already being tested internally and will be rolled out next month. The announcement highlights advancements in agentic intelligence, multimodal understanding, and real-world applications across industries. Gemini 3.5 Flash is now available globally through the Gemini app, Google Search’s AI Mode, and developer platforms like Google Antigravity and the Gemini API. It is positioned as a powerful tool for developers and enterprises, offering capabilities that rival large flagship models in performance while maintaining exceptional speed. The model excels in coding, long-horizon tasks, and multimodal reasoning, achieving notable benchmarks such as 76.2% on Terminal-Bench 2.1, 1656 Elo on GDPval-AA, and 83.6% on MCP Atlas. Its output token speed is four times faster than other frontier models, balancing quality and latency. The release emphasizes the model’s ability to handle complex, real-world problems. For instance, 3.5 Flash can automate tasks like renaming and categorizing unstructured assets, synthesizing academic papers into playable games, and transforming legacy codebases into modern frameworks like Next.js. It also supports collaborative subagents through the Antigravity platform, enabling scalable solutions for tasks such as financial document preparation, data analysis, and application development. Industry partners are already leveraging Gemini 3.5 Flash for transformative applications.#google #google_deepmind #shopify #gemini_35 #google_antigravity
Google's New Gemma 4 Models Bring Complex Reasoning Skills to Low-Power Devices Google LLC has launched its latest open-weight artificial intelligence models, Gemma 4, marking a significant advancement in the field of lightweight, high-performance AI. These models, built on the architectural foundation of Gemini 3, are designed to handle complex reasoning tasks and support autonomous AI agents running on low-power devices such as workstations and smartphones. The release positions Google as a key player in the growing market for edge computing and local AI applications. The Gemma 4 family includes four variants: Effective 2B, Effective 4B, a 26B Mixture of Experts (MoE) model, and a 31B Dense model. The smaller "Effective" models are tailored for edge use cases, such as Android smartphones and Raspberry Pi computers, while the 26B MoE model introduces an innovative approach by activating only 3.8 billion parameters during inference tasks. This optimization allows the model to maintain high performance without compromising the depth of knowledge typical of larger models. The 31B Dense variant currently ranks third in open models on the industry-standard Arena AI Text leaderboard, demonstrating its competitive edge. Google DeepMind researchers Clement Farabet and Olivier Lacombe highlighted the models' ability to deliver "more intelligence per parameter," enabling them to outperform their size class. This efficiency is critical for applications requiring real-time processing and minimal computational resources. The models are also engineered to support AI agents, with native capabilities for function calling and structured JavaScript Object Notation (JSON) outputs.#google_llc #google_deepmind #clement_farabet #olivier_lacombe #hugging_face
