Google: Gemini 3 Pro
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Gemini 3 Pro is Google's most intelligent model, delivering state-of-the-art performance in reasoning, multimodal understanding, and agentic coding. It handles text, images, video, audio, and code with a 1M token context window and advanced tool-calling capabilities.
Context Window 1M
tokens
Max Output 200K
tokens
Input Cost $2
per million tokens
Output Cost $12
per million tokens
Input text, image, video, audio, pdf
modalities
Tool Use Yes
Knowledge Cutoff Jan 2025
Release Date Nov 18, 2025
Code Example
Add AI to your app with the Puter.js AI API — no API keys or setup required.
// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms").then(response => {
document.body.innerHTML = response.message.content;
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.chat("Explain quantum computing in simple terms").then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
More AI Models From Google
Gemma 4 26B A4B
Gemma 4 26B A4B is a Mixture-of-Experts (MoE) open model from Google DeepMind, built from the same research as Gemini 3. It has 26B total parameters but activates only 3.8B per forward pass, delivering near-31B-dense quality at a fraction of the compute cost. The model supports a 256K token context window, multimodal image and text input, built-in step-by-step reasoning (thinking mode), and native function calling for agentic workflows. It currently ranks #6 among open models on the Arena AI text leaderboard with an estimated LMArena score of 1441 — competitive with models many times its active size. It excels at reasoning, coding, long-context tasks, and structured tool use. It's a strong pick for developers who need high throughput and low latency without sacrificing capability.
ChatGemma 4 31B
Gemma 4 31B is a dense multimodal model from Google DeepMind, built on the same research foundation as Gemini 3. It is the most capable model in the Gemma 4 family, accepting text, image, and video input with a 256K-token context window. It delivers strong benchmark results: 89.2% on AIME 2026, 85.2% on MMLU Pro, 80.0% on LiveCodeBench v6, and 84.3% on GPQA Diamond. On the Arena AI text leaderboard, it ranks as the #3 open model globally, outperforming many models with far higher parameter counts. Gemma 4 31B features native function calling trained into the model, configurable chain-of-thought reasoning, and structured JSON output — making it especially well-suited for agentic workflows, coding tasks, and multi-turn tool use. It supports over 140 languages and serves as a strong foundation for fine-tuning.
VideoVeo 3.1 Lite
Veo 3.1 Lite is Google DeepMind's most cost-effective video generation model, built for high-volume applications where per-clip cost is a primary concern. It generates video at the same speed as Veo 3.1 Fast but at less than half the price — starting at $0.05 per second for 720p. The model supports text-to-video and image-to-video with 720p and 1080p output in landscape (16:9) or portrait (9:16), at configurable durations of 4, 6, or 8 seconds. It does not support 4K output, scene extension, or native audio generation — clips are silent by default. Veo 3.1 Lite is ideal for developers building batch video pipelines, social media automation, or interactive tools where cost per generation matters most and audio can be added in post-production.
Frequently Asked Questions
You can access Gemini 3 Pro by Google through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Gemini 3 Pro to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.
| Price per 1M tokens | |
|---|---|
| Input | $2 |
| Output | $12 |
Gemini 3 Pro was created by Google and released on Nov 18, 2025.
Gemini 3 Pro supports a context window of 1M tokens. For reference, that is roughly equivalent to 2,097 pages of text.
Gemini 3 Pro can generate up to 200K tokens in a single response.
Gemini 3 Pro has a knowledge cutoff date of Jan 2025. This means the model was trained on data available up to that date.
Gemini 3 Pro accepts the following input types: text, image, video, audio, pdf. It produces: text.
Yes, Gemini 3 Pro supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
Yes — the Gemini 3 Pro API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
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