Ryan Trostle

Atlanta via the Lowcountry 🌙 🌴 / Googler / Views are my own

[Erling Haaland @Erling]

One thing to do today… search my name on Google 😉

[Google Gemma @googlegemma]

Introducing the Fast Gemma Challenge with Hugging Face

Over the next few days, dozens of agents will collaborate to make Gemma 4 E4B even faster!

[Logan Kilpatrick @OfficialLoganK]

Today we are rolling out some big updates to Managed Agents in the Gemini API:

- support for background tasks
- remote MCP & function calling
- network credential refresh

and you can now get started with Managed agents in the API via the free tier!

https://t.co/lc7giVtekq

[Google @Google]

Today we're releasing two generative media models for developers and enterprises with strong cost-performance.

🍌 Nano Banana 2 Lite: our fastest, most cost-efficient image model in the Nano Banana family.

🌐 Gemini Omni Flash: our natively multimodal high quality, cost efficient model for video generation and conversational editing.

Both models are available today in @GoogleAIStudio, the Gemini API, and the Gemini Enterprise Agent Platform.

[Logan Kilpatrick @OfficialLoganK]

Introducing Nano Banana 2 Lite 🍌 and Gemini Omni Flash 🔮, our new generative media models in the Gemini API and AI Studio!

Nano Banana 2 Lite is extremely fast (<4s image) & cheap ($0.034 / 1K image).

Omni Flash is SOTA at video editing at $0.10 / sec, same as Veo 3.1 Fast!

[Olivier Lacombe @o_lacombe]

200 million times! 🚀🚀

That’s how many times developers, researchers, and startups have downloaded the Gemma 4 family in just 2.5 months. When we built Gemma, our goal was to bring Google’s Gemini research to the open-science community in an accessible and highly capable package. Seeing this milestone today is both humbling and exhilarating.

From lightweight agents to satellites orbiting Earth, the community is pushing the boundaries of what's possible with our open models.

At Google DeepMind, our commitment to open science and developer choice remains unwavering. Gemma 4 is just one step in this journey, and we are excited to keep iterating alongside you.

To celebrate, here is a look at the real-world, global impact Gemma is having, and how it’s empowering the next generation of builders 👇

Thank you to everyone who has downloaded, fine-tuned, and built with Gemma. We can't wait to show you what's next.

[Google AI Studio @GoogleAIStudio]

https://t.co/oFKtt2LToj

[Google @Google]

We recently released Gemma 4, our most capable open models to date. Since then, they’ve been downloaded more than 150 million times. Here’s how three builders are using @GoogleGemma to create apps, platforms, and more.

First up: Builder @measure_plan, who used Gemma 4 to perform visual question answering (VQA) through a specific persona.

🔹By prompting Gemma 4 this way, the model effectively maintained a "medieval bard" character while accurately identifying objects in the room, like “glass of amber liquid” or “shelves with bound tomes.”

[Ryan Trostle @ryantrostle]

So cool to see @GoogleDeepMind's Gemma 3 running on a satellite in space. 🛰️🧠 Onboard data triage is finally happening. Pretty major milestone for edge AI! @googlegemma @NASA

https://t.co/xGT2Rx1qvt

[Arena.ai @arena]

Exciting news: Gemini Omni Flash is now #1 in the Video Arena (both Text-to-Video and Image-to-Video)!

For Text-to-Video this is a massive +158 pt improvement over Veo 3.1 (1080p) and a large +61 pt lead over the next best model, Seedance 2.0.

Congrats @GoogleDeepMind for this huge milestone!

[Google @Google]

Because it generates everything at once, DiffusionGemma unlocks new patterns of model behavior.

⚡ Fast: Generates up to 1,000+ tokens a second for up to 4x faster text generation.

💻 Lightweight: Runs smoothly right on 18GB consumer graphics cards.

🧠 Smart editing: Since it processes larger amounts of information at once, it can easily fill in blanks, format code, and fix its own errors in real time.

[Google DeepMind @GoogleDeepMind]

DiffusionGemma is our new experimental open model with up to 4x faster output on dedicated GPUs.

Instead of predicting word-by-word, it generates entire blocks of text simultaneously. This lets the model self-correct and format complex markdown in real time.

[Google Gemma @googlegemma]

Meet DiffusionGemma!

An experimental open model that explores a fast approach to text generation, released under an Apache 2.0 license.

Moving beyond sequential, token-by-token processes to generate entire blocks of text simultaneously. Here’s what’s new with DiffusionGemma: 👇

[Sundar Pichai @sundarpichai]

DiffusionGemma is an open, experimental model that brings our text diffusion research to Gemma 4. It’s a racehorse 🏇achieving up to 4x faster inference by generating entire blocks of text simultaneously vs predicting token-by-token (word-by-word) output!

[Ryan Trostle @ryantrostle]

See what 3 builders are making with Gemma 4 @google @googlegemma https://t.co/EwRk1yhyM8

[Logan Kilpatrick @OfficialLoganK]

Introducing Gemini 3.5 Flash Live Translate, our real time speech to speech translation model which supports more than 70 languages (both in and out), and is so natural.

It is available in the Gemini API, AI Studio, & Google Translate right now + coming soon to Google Meet!!

[Demis Hassabis @demishassabis]

Celebrating the milestone of a massive 150+ million downloads of Gemma 4 with the release of the new Gemma 4 12B model! It's incredibly powerful for such a small model and it’s tiny enough to run locally on a laptop with just 16GB VRAM. Apache 2.0 license - happy building!

[Sundar Pichai @sundarpichai]

Our new Gemma 4 12B model hits a sweet spot between size + performance: it can run locally on a laptop, while enabling powerful multi-step reasoning and agentic workflows. Can’t wait to see what the community does with this one!

[Google @Google]

Today we’re introducing Gemma 4 12B — our latest open model that brings advanced agentic reasoning, vision and audio directly to your laptop.

It delivers performance nearing our larger Gemma models with a much smaller total memory footprint, while being small enough to run locally with just 16GB of VRAM. It’s open and accessible for everyone to use under a permissive Apache 2.0 license.

This is all made possible by our new, unified architecture that removes separate multimodal encoders. Here’s how we did it 🧵

[Parisa Tabriz @laparisa]

In a totally delightful surprise, I just learned I was featured in a question on @Jeopardy today! 😲😆☺️

Achievement unlocked. ✅