🚀 We just launched Gemini 3 Pro — the strongest multimodal understanding model ever built. I lead product for Gemini’s multimodal vision capabilities, and I want to share more about the massive wins we are seeing across document, screen, spatial, and video understanding. 🧵

Gemini 3.5 Flash outperforms 3.1 Pro on many vision use cases (like the below Roboflow eval) while being ~6x faster on average 🤯 Gemini multimodal understanding for the win.

gemini 3.5 flash is the engine that powers agents across all google products. would love to hear what y'all think

Had fun speaking at Cloud Next 2026 as a panelist for "How DeepMind Makes Modeling Decisions" ✨ DM me if you want to keep chatting about the future of frontier models and multimodal agents 🤖

Gemini's agentic vision really shines in our latest SOTA robotics model for things like reading instruments, estimating proportions, and counting 🤖

filesystem code sandbox combo eats another modality. remember when o3 destroyed at geoguessr? gemini agentic vision will find location on any street photo you take faster than Liam Neeson can get back his daughter

An awesome deep dive on how to leverage Gemini 3 Agentic Vision today

Back at Harvard Business School last week speaking on frontier AI agents 🤖 As a ’23 alum, it was energizing to be back - this time teaching from the other side of the classroom My AI agent workshop was completely packed, with 100 students - signal on how much Harvard is leaning into AI The students’ agency, raw IQ, and curiosity left me wildly optimistic about the next wave of AI builders 🚀 Grateful to Profs. Jeffrey Bussgang & Allison Mnookin and the Launching Tech Ventures team for the invite 🙏🏼

what are y'all building with Gemini Agentic Vision??

🚀 Excited to officially launch 👁Agentic Vision via Gemini 3 Flash. Gemini can run code execution on image uploads to zoom, analyze, and annotate: 🔍 Zoom: 5-10% quality win across vision benchmarks 🧮 Analyze: do image math with code (e.g. calculate the tip for a receipt) ✏️ Annotate: Draw arrows or bounding boxes to answer questions Try via the Gemini API (AI Studio / Vertex) or via the Gemini App (rolling out to Thinking mode today). Learn more→ goo.gle/4bsKdFv Demo: goo.gle/3Z05KxK cc: @IoanaBica95 @anastasija56572 @jalayrac @bcaine @eisenjulian @weichengkuo @phillip_lippe @xf1280 @tulseedoshi @BiboXu @OfficialLoganK

Gemini 3 Flash is insane at OCR. It parses this extremely hard to read handwritten letter by Richard Feynman perfectly. It can do ~300 of these for $1. What's crazy is Feynman addresses General Donald J. Kutyna as "Katyna" which Gemini gets. There is no "Meeting Katyna", the first part of the letter, in all of Google search!

⚡️ Gemini 3 Flash just got a major new capability: code execution for images. Gemini can decide when to write code to zoom, count, and annotate—unlocking the next phase of Agentic Vision. 🤖 Wildly fun to PM this 0→1. Stay tuned to hear more 👀

One of my fav parts of being a Gemini model PM - you get to work with billion-user Google products like AI Mode. The future of multimodal search is bright⚡️

🚀🚀🚀 Gemini 3 Flash is live⚡️⚡️⚡️ 🧠 Gemini 3 Pro-level intelligence, but 📉 4x Cheaper and 🏎️ 3x Faster. We pushed the Pareto frontier, unlocking a new generation of multimodal agents. 🤯 We’re already seeing @figma accelerate rapid prototyping, @Harveyaisol master complex legal reasoning, and @Bridgewater unlock investment insights from massive unstructured datasets. 🤖Try now at gemini.google.com or start building at aistudio.google.com. Read more at lnkd.in/gsPv542a 👏🏼Huge shoutout to the team! @jalayrac @RSoricut @bcaine @xf1280 @IoanaBica95 @MarioLucic_ @BiboXu @tulseedoshi @OfficialLoganK @joshwoodward @demishassabis

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gemini 3 is our bet that the future of AGI is multimodal I unpack the thinking behind the evals @demishassabis just shared here → goo.gle/3Mt3UlT

Gemini 3 Pro continues to be SOTA on most multi-modal benchmarks and use cases!

One aspect of our Gemini 3 Pro model to look at is how it performs in multimodal capabilities. We've worked on making it perform really well across a variety of multimodal use cases, like understanding of documents, videos, spatial characteristics, biomedical data, and computer sceens, and being able to reason about visual information. To test it out, I gave the original image from the blog post below, and asked it: Please make a version of this figure with the Gemini Pro column annotated with the relative improvement versus the best result from the other three columns in red (This in itself is a pretty difficult visual reasoning task! It did pretty well at doing this accurately on some spot checking, and those relative accuracy improvements are quite large across some of the benchmarks!) Read more below or in the blog post at: blog.google/technology/devel…