Today we are rolling out Gemini 4 Argon globally in the Gemini API, to Pro + Ultra in Gemini App, and Ultra subs in Antigravity! Argon is a huge step forward for Gemini, and a labor of love. This model has been battle tested by over 100,000 people at Google over the last month, with so much new innovation, ambition, and hard work baked into this release. The team has been heads down over the last 6 months working to make this possible across the stack (research, infra, safety, eng, etc). We rolled the model out to cyber defenders as part of our fairwind program and early access customers over the last 2 weeks, it has been amazing to see and talk to folks who are now using this model daily. Seeing the models writing capability, raw knowledge and persistence for coding, paired with new features like 1M token output when the model needs to work more has gotten me even more excited about our path ahead. This is just the start of the Gemini 4 era. As you saw with 3.5, 3.6, 3.7, and 3.8 Flash, our iteration speed with Gemini is fast : ) Now with Gemini 4 Argon to work from, I am cannot wait to see the progress continue, and most importantly see what this new model enables for the world. This is such a special moment in the arc of technology, as millions of people everyday tackle problems they could never have thought possible before. Gemini 4 Argon was built to help you tackle the hardest problems. I have personally felt this spark with Argon and hope you do too. Onwards!!

Introducing Gemini 4 Argon, our new frontier model, rolling out to cyber defenders starting today, and more widely as soon as possible. I am really excited by the progress we have made here. Argon is priced at $2 in and $10 out during introductory pricing!

this agentic video understanding with Gemini based experiment got a lot of reactions & questions, will share a repo soon, so you can try it out. I have more examples coming in the next few days. there are so many possibilities with this model !!! 👾📹

Introducing Gemini 3.8 Flash, another jump in Gemini's agentic + coding capabilities, and our 3rd updated Flash model in only 6 weeks... This model has been a ton of fun to work with, excited to see what you all think!

Mosaic is a Day 1 partner with @GoogleDeepMind and the new Gemini Flash 3.7 Agentic Video Understanding model. we had the opportunity to test this new model out in early access with our video agents over the past few weeks and the results are stark. full blog post from @googledevs in the comments! 👇

Today we're launching Gemini 3.7 Flash - our latest workhorse model for coding and agentic workflows, with an introductory price at half the original cost of 3.6 Flash. ⚡️ We have been iterating rapidly with the Flash series, going from 3.5 to 3.7 in just 3 months, making it more helpful across a wide range of tasks: • Software Engineering (DeepSWE v1.1): 37.0% ➔ 65.3% • Web Development (Code Arena Elo): 1506 ➔ 1588 • Enterprise Automation (AutomationBench): 13.4% ➔ 30.4%

Google gets a lot of criticism on here for falling behind on agentic coding, but Gemini 3.5 Flash has long been my daily driver for agentic document extraction, which is one of the highest-value use-cases for LLMs IMO I even had Fable supervise doc extraction benchmarks across a bunch of models and it told me to keep using Gemini instead of itself for this Excited to try out these new models

Just tested Gemini 3.5 Flash-Lite vs. Claude Fable 5 on a tightly structured doc extraction task. Flash-Lite was 71x cheaper and 4.1x faster for identical results. Knowing how and when to use AI models - rather than reaching for the "most powerful" one every time - is an underrated skill