Enterprises can now harness the power of a large language model that's near that of the state-of-the-art Google’s Gemini 3 Pro, but at a fraction of the cost and with increased speed, thanks to the newly released Gemini 3 Flash.The model joins the flagship Gemini 3 Pro, Gemini 3 Deep Think, and Gemini Agent, all of which were announced and released last month.Gemini 3 Flash, now available on Gemini Enterprise, Google Antigravity, Gemini CLI, AI Studio, and on preview in Vertex AI, processes information in near real-time and helps build quick, responsive agentic applications. The company said in a blog post that Gemini 3 Flash “builds on the model series that developers and enterprises already love, optimized for high-frequency workflows that demand speed, without sacrificing qual [...]
Google DeepMind today released three new proprietary AI models it says are among its most token-efficient yet: Gemini 3.6 Flash, Gemini 3.5 Flash-Lite, and Gemini 3.5 Flash Cyber. The models aim to ma [...]
Google DeepMind today released three new proprietary AI models it says are among its most token-efficient yet: Gemini 3.6 Flash, Gemini 3.5 Flash-Lite, and Gemini 3.5 Flash Cyber. The models aim to ma [...]
Google is rolling out Gemini 3.7 Flash, a new version of its workhorse AI model that puts coding, agentic workflows and knowledge work at the center of the upgrade — while temporarily cutting API pr [...]
Google unveiled Gemini 3.5 Flash at its annual I/O developer conference on Tuesday, a new artificial intelligence model that the company says shatters what had become a seemingly iron law of the AI in [...]
To quote an ancient Jedi Master "Begun, the AI price wars have!"OpenAI is sharply reducing the prices of two models in its GPT-5.6 frontier series, cutting GPT-5.6 Luna, the smallest and fas [...]
Across 170 enterprises, AI infrastructure has moved decisively into production — two-thirds now run AI workloads live and three in 10 run them at scale — while the ability to account for what that [...]
Across 101 enterprises, the context feeding AI agents is failing often and repeatedly. Sixty-eight percent have traced a confident but wrong agent answer to missing or inconsistent business context in [...]
For the past year, enterprise decision-makers have faced a rigid architectural trade-off in voice AI: adopt a "Native" speech-to-speech (S2S) model for speed and emotional fidelity, or stick [...]