Today at Google I/O, we introduced Gemini 3.5 Flash! It has become an integral part of our daily research cycle and works with all the tools we have at Google.
We used a team of agents in Antigravity 2.0 to recreate the original AlphaZero research paper and build a playable version. They coded the reinforcement learning pipeline in JAX/Flax, trained a ResNet model from scratch via self-play on multi-TPU pods, and shipped a full-stack web app so you can play against it, from just 2 prompts. .
Here’s what else makes 3.5 Flash special 🧵
Excited to launch Gemma 4: the best open models in the world for their respective sizes. Available in 4 sizes that can be fine-tuned for your specific task: 31B dense for great raw performance, 26B MoE for low latency, and effective 2B & 4B for edge device use - happy building!
Launched Gemini 3.1 Flash Live. It’s capable of handling the nuances of live speech, like tone and interruptions, that are critical for real-world interactions. You can experience it on Gemini Live and Search Live!
I’ve been developing the SVG generation capabilities for Gemini 3.1, and the complexity of the SVGs is stunning. 🚀
This allows UX designers to transcend pixel constraints and directly output structural, production-ready code!
Can’t be more proud!
Answering a top request from our users, we’re introducing Personal Intelligence in the @GeminiApp. You can now securely connect to Google apps for an even more helpful experience.
Personal Intelligence combines two core strengths: reasoning across complex sources and retrieving specific details, e.g from an email or photo, to provide uniquely tailored answers.
It’s built with privacy at the center. You choose exactly which apps to connect, these connected app settings are off by default.
Introducing Gemini 3 Flash, our frontier intelligence model, available at scale for everyone. It excels at coding, tool calling, and is stronger than 2.5 Pro across most metrics!! ⚡️
Available in the API at $0.50 in / 1M tokens and $3.00 out / 1M tokens across.
Gemini 3 Flash is live. ⚡️
We’ve packed Gemini 3’s Pro-grade reasoning into a leaner model with Flash-level latency, efficiency, and cost.
It's my favorite model to use – the latency feels like a real conversation, with the deep intelligence intact.
Available in the API, Gemini App, and Search. Give it a spin.
https://t.co/FeGrVUhLvN
🚨Breaking: New Gemini-2.5-Pro (06-05) takes the #1 spot across all Arenas again!
🥇 #1 in Text, Vision, WebDev
🥇 #1 in Hard, Coding, Math, Creative, Multi-turn, Instruction Following, and Long Queries categories
Huge congrats @GoogleDeepMind!
Our best model*, Gemini 2.5 Pro, is now available for everyone in the Gemini app model drop down menu at https://t.co/xR9jN4XMCO. Give it a try with your most difficult questions!
*For now! 😃
BREAKING: Gemini 2.5 Pro is now #1 on the Arena leaderboard - the largest score jump ever (+40 pts vs Grok-3/GPT-4.5)! 🏆
Tested under codename "nebula"🌌, Gemini 2.5 Pro ranked #1🥇 across ALL categories and UNIQUELY #1 in Math, Creative Writing, Instruction Following, Longer Query, and Multi-Turn!
Massive congrats to @GoogleDeepMind for this incredible Arena milestone! 🙌
More highlights in thread👇
Starting today, Gemini Advanced users get priority access to our latest 2.0 Experimental Advanced model, Gemini-Exp-1206. This model is designed to help you with more complex tasks such as:
🧑💻 Advanced coding challenges
🧮 Solving math problems
🧠 Reasoning & instruction following
Subscribe at https://t.co/QMUII87ebx to preview Gemini-Exp-1206. (You can try Gemini Advanced for one month, at no charge!)
Massive News from Chatbot Arena🔥
@GoogleDeepMind's latest Gemini (Exp 1114), tested with 6K+ community votes over the past week, now ranks joint #1 overall with an impressive 40+ score leap — matching 4o-latest in and surpassing o1-preview! It also claims #1 on Vision leaderboard.
Gemini-Exp-1114 excels across technical and creative domains:
- Overall #3 -> #1
- Math: #3 -> #1
- Hard Prompts: #4 -> #1
- Creative Writing #2 -> #1
- Vision: #2 -> #1
- Coding: #5 -> #3
- Overall (StyleCtrl): #4 -> #4
Huge congrats to @GoogleDeepMind on this remarkable milestone!
Come try the new Gemini and share your feedback!
We're excited to unveil Gemma 2. 🛠️
Available in both 9B and 27B parameters, it delivers the best performance for its size - unlocking more possibilities for developers to build and deploy with AI. → https://t.co/RmRLEdFPMV
Gemma 2 is out!
As with our first model, we're super focused on creating models at useful, practical sizes, so that they can be easily deployable... all the while being amazing in quality.
We upgraded our 9B so that it's truly awesome and best in class across many benchmarks. And we're introducing a brand new 27B, also best at size, and actually stronger than some larger models.
Both did real nice on LMSYS.
The 27B Gemma 2 model is designed to run inference efficiently at full precision on a single Google Cloud TPU host, NVIDIA A100 80GB Tensor Core GPU, or NVIDIA H100 Tensor Core GPU.
And of course, this is our open weights model line... enjoy!
https://t.co/TmgaJH52Zi - try it in AI Studio
https://t.co/ypeIKONwSC
More in the tech report =>
https://t.co/2wnb6dIRWH
Gemini 1.5 Pro when zero-shot prompted to perform an LLM-as-a-judge task ranks 1st when compared to other Generative RMs and 2nd best overall vs other dedicated RMs: https://t.co/SpYoU9f49Q (make sure to click on the Generative checkbox).
Gemini 1.5 Pro - A highly capable multimodal model with a 10M token context length
Today we are releasing the first demonstrations of the capabilities of the Gemini 1.5 series, with the Gemini 1.5 Pro model. One of the key differentiators of this model is its incredibly long context capabilities, supporting millions of tokens of multimodal input. The multimodal capabilities of the model means you can interact in sophisticated ways with entire books, very long document collections, codebases of hundreds of thousands of lines across hundreds of files, full movies, entire podcast series, and more.
Gemini 1.5 was built by an amazing team of people from @GoogleDeepMind, @GoogleResearch, and elsewhere at @Google. @OriolVinyals (my co-technical lead for the project) and I are incredibly proud of the whole team, and we’re so excited to be sharing this work and what long context and in-context learning can mean for you today!
There’s lots of material about this, some of which are linked to below.
Main blog post:
https://t.co/QAsDKXBdao
Technical report:
“Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context”
https://t.co/CTzTHNDCdo
Videos of interactions with the model that highlight its long context abilities:
Understanding the three.js codebase: https://t.co/yq7d6OSD6c
Analyzing a 45 minute Buster Keaton movie: https://t.co/adyMgDYHoK
Apollo 11 transcript interaction: https://t.co/Pqvq3Eac1R
Starting today, we’re offering a limited preview of 1.5 Pro to developers and enterprise customers via AI Studio and Vertex AI. Read more about this on these blogs:
Google for Developers blog:
https://t.co/x73Vun0kVS
Google Cloud blog:
https://t.co/OlaTW6PYGn
We’ll also introduce 1.5 Pro with a standard 128,000 token context window when the model is ready for a wider release. Coming soon, we plan to introduce pricing tiers that start at the standard 128,000 context window and scale up to 1 million tokens, as we improve the model.
Early testers can try the 1 million token context window at no cost during the testing period. We’re excited to see what developer’s creativity unlocks with a very long context window.
Let me walk you through the capabilities of the model and what I’m excited about!