Gemini 3 Pro
Gemini 3 Pro is Google's flagship multimodal AI featuring 1M context, 'Anti-gravity' agentic reasoning, and record-breaking performance on GPQA and ARC-AGI.
googleGemini 3November 18, 2025Your AI response will appear here
About Gemini 3 Pro
Learn about Gemini 3 Pro's capabilities, features, and how it can help you achieve better results.
Gemini 3 Pro represents Google's most significant leap in artificial intelligence, introducing a 'dynamic thinking' architecture that allows the model to scale its reasoning capabilities based on task complexity. Built on Google’s custom TPU infrastructure, it is designed for high-performance agentic workflows and state-of-the-art multimodal understanding across text, image, audio, and video.
As a sparse Mixture-of-Experts (MoE) model, it shifts the AI landscape toward active agents, featuring a record-breaking 64k output limit and a massive context window capable of processing hour-long videos or entire codebases in a single prompt. Its core differentiator is 'Anti-gravity,' a unified platform that enables the model to execute code and interact with computer environments in real-time.
By closing the loop between reasoning and environmental interaction, Gemini 3 Pro transitions the LLM from a passive advisor to an autonomous operator. It achieves state-of-the-art scores across nearly every major reasoning benchmark, effectively setting the new standard for what constitutes a frontier AI model in the agentic era.
Use Cases for Gemini 3 Pro
Discover the different ways you can use Gemini 3 Pro to achieve great results.
Autonomous Frontend Development
Leveraging the 'Anti-gravity' loop to one-shot complex React/Next.js interfaces by observing and fixing visual bugs in real-time.
Long-Form Video Intelligence
Analyzing hour-long surveillance or meeting footage frame-by-frame to identify specific events or extract detailed meeting minutes.
Agentic Research Orchestration
Managing 'Gemini Deep Research' agents to synthesize thousands of technical papers into a single coherent report.
Complex Logic & Math Competitions
Solving IMO-level mathematical proofs and AIME problems with nearly 100% accuracy using extended thinking time.
Multi-Modal Document Parsing
Processing entire folders of medical records or financial statements to find cross-document patterns and anomalies.
Real-Time Game State Analysis
Acting as a high-level strategist in complex games like Pokémon Crystal or Minecraft by understanding visual game state directly.
Strengths
Limitations
API Quick Start
google/gemini-3-pro-preview
import { GoogleGenAI } from "@google/genai";
const client = new GoogleGenAI({ apiKey: process.env.GOOGLE_API_KEY });
const model = client.getGenerativeModel({ model: "gemini-3-pro-preview" });
async function run() {
const result = await model.generateContent({
contents: [{ role: "user", parts: [{ text: "Analyze this codebase for security flaws." }] }],
generationConfig: { maxOutputTokens: 64000, thinking: true }
});
console.log(result.response.text());
}
run();Install the SDK and start making API calls in minutes.
What People Are Saying About Gemini 3 Pro
See what the community thinks about Gemini 3 Pro
"Gemini 3 Pro is great for code review, but I just use 5.2 exclusively - the benefit of 5.2 Pro on API is tremendous"
"It's very obvious they trained Gemini 3.0 to make it more neutral... it rejects 'balance' on science but maintains a neutral point of view on politics"
"Gemini 3 Pro led by a wide margin with a score of 83.64 on the SuperCLUE-VLM benchmark"
"Gemini 3 Pro completed Pokémon Crystal using 50% fewer tokens than 2.5 Pro. It defeated Red!"
"It literally looking frame by frame at the video unlike any other model... understand it frame by frame"
"Google launched its deepest AI research agent yet... based on Gemini 3 Pro"
Videos About Gemini 3 Pro
Watch tutorials, reviews, and discussions about Gemini 3 Pro
“Gemini 3 Pro gets 37.5% [on HLE]... a huge leap above GPT 5.1 and that's a theme you'll see recurring.”
“Gemini 3 Pro almost doubles the performance of GPT 5.1 on ARC AGI 2 visual reasoning puzzles.”
“Google trained Gemini 3 on their own in-house TPUs, not Nvidia's GPUs. They may be the only company that can afford to serve this.”
“We are seeing a massive jump in the reasoning density of these models compared to the previous generation.”
“The multimodal performance here really sets a new baseline for what we expect from frontier models.”
“It literally looking frame by frame at the video unlike any other model... understand it frame by frame.”
“It can load a full YouTube video and understand it... I use this all the time for chapter markers.”
“The ability to handle long context without losing focus is where Gemini 3 really shines.”
“I've tested its vision on complex technical diagrams and it's significantly more accurate than GPT.”
“Google's integration with AI Studio makes testing these advanced features very straightforward.”
“Pricing is $2 per 1M input / $12 per 1M output tokens... it's token-heavy and expensive.”
“It acts like a senior engineer who says 'got it done' but needs babysitting... verify its own work.”
“The context window is actually insane, you can just dump an entire repo in there.”
“If you're building agents, the function calling reliability on this model is a game changer.”
“You have to be careful with the safety filters, they can be a bit over-tuned on certain topics.”
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Pro Tips
Expert tips to help you get the most out of this model and achieve better results.
Dynamic Thinking
For simpler tasks, use the model in 'Flash' mode to save costs; only invoke the 'Deep Think' or 'Pro' modes for tasks requiring ARC-AGI level reasoning.
Context Management
While the window is 1M tokens, pricing doubles after 200k tokens. Use selective context engineering to keep sessions under this threshold for better ROI.
The 'Senior Engineer' Strategy
When coding, treat the model as a senior developer who needs verification—always ask it to 'double-check logs and verify imports' to mitigate its 88% hallucination quirk in complex environments.
Testimonials
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Frequently Asked Questions
Find answers to common questions about this model