On February 19, 2026, Google released Gemini 3.1 Pro, the latest upgrade to its flagship reasoning model. Building on the Gemini 3 series, 3.1 Pro scored 77.1% on ARC-AGI-2, more than doubling the reasoning performance of 3.0 Pro. It's rolling out across the Gemini API, Vertex AI, the Gemini app, NotebookLM, and developer tools like Gemini CLI and Android Studio.

In this post, we break down what's new, walk through the benchmark results, cover API pricing and access details, and explain how Lushbinary can help your team integrate Gemini 3.1 Pro into production workflows.

1What Is Gemini 3.1 Pro?

Gemini 3.1 Pro is Google DeepMind's latest flagship model in the Gemini 3 series. It's positioned as the core intelligence upgrade that powers everything from the consumer Gemini app to enterprise Vertex AI deployments. Last week Google released Gemini 3 Deep Think for science and research; 3.1 Pro is the upgraded baseline that makes those breakthroughs accessible for everyday developer applications.

The model is designed for tasks where a simple answer isn't enough. It takes advanced reasoning and makes it practical for complex problem-solving, whether you're synthesizing data, generating code-based animations, or building agentic workflows.

2What's New in 3.1 Pro

The headline improvement is reasoning. On ARC-AGI-2, a benchmark that evaluates a model's ability to solve entirely new logic patterns it has never seen before, 3.1 Pro achieved 77.1%, more than double the 31.1% score of 3.0 Pro. This isn't incremental; it's a generational leap in the model's ability to reason through novel problems.

Beyond raw reasoning, key improvements include:

• Code-based SVG animation: 3.1 Pro can generate website-ready, animated SVGs directly from text prompts. Because these are built in pure code rather than pixels, they stay crisp at any scale with tiny file sizes compared to video.
• Complex system synthesis: the model can bridge complex APIs and user-friendly design. Google demonstrated it building a live aerospace dashboard that configured a public telemetry stream to visualize the ISS orbit.
• Interactive 3D experiences: 3.1 Pro can code complex 3D simulations with hand-tracking and generative audio that responds to user interaction.
• Creative coding: the model can translate literary themes into functional code, reasoning through tone and atmosphere to design interfaces that capture the essence of source material.
• Agentic workflow improvements: Google is specifically advancing 3.1 Pro for ambitious agentic workflows, with further improvements expected before general availability.

3Benchmark Results: The Numbers

Here's how Gemini 3.1 Pro performs across key benchmarks, compiled from Google's release and independent evaluations:

The SWE-Bench Verified score of 80.6% puts 3.1 Pro in direct competition with Claude Opus 4.6 (80.9%) for real-world coding tasks. The GPQA Diamond score of 94.3% shows strong graduate-level scientific reasoning, and the BrowseComp jump from 59.2% to 85.9% is a massive improvement in the model's ability to find and synthesize information from the web.

43.1 Pro vs 3.0 Pro: What Changed

Here's a direct comparison showing the improvements from 3.0 Pro to 3.1 Pro:

The standout is ARC-AGI-2 with a 2.5x improvement. BrowseComp also saw a massive jump, indicating significantly better web-based information retrieval and synthesis. SWE-Bench improved more modestly but now sits neck-and-neck with the best coding models available.

5API Access, Pricing & Context Window

Gemini 3.1 Pro maintains the same pricing as 3.0 Pro, which makes the performance gains essentially free for existing users:

At $2 per million input tokens, Gemini 3.1 Pro is significantly cheaper than comparable frontier models. For context, Claude Opus 4.6 runs at roughly 6x the cost per input token. The 1M token context window remains one of the largest available, making it ideal for processing large codebases, long documents, or multi-turn agentic conversations.

import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({ apiKey: "YOUR_API_KEY" });

const response = await ai.models.generateContent({
  model: "gemini-3.1-pro",
  contents: "Explain how transformer attention works",
});

console.log(response.text);

6Where You Can Use It Today

3.1 Pro is rolling out across Google's entire product surface in preview:

For enterprise customers, Gemini Enterprise provides managed access with compliance controls, data residency options, and dedicated support. The model is currently in preview, with general availability expected soon.

7Practical Capabilities for Developers

Beyond benchmarks, here's what 3.1 Pro can actually do that matters for day-to-day development:

import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({ apiKey: "YOUR_API_KEY" });

const response = await ai.models.generateContent({
  model: "gemini-3.1-pro",
  contents: "Find the current ISS position and create a tracking dashboard",
  config: {
    tools: [{ googleSearch: {} }],
    systemInstruction:
      "You are a helpful assistant that can search the web " +
      "and generate code. Use tools when needed.",
  },
});

8What's Coming Next

Google has signaled several areas of active development:

• General availability: 3.1 Pro is currently in preview. Google plans to make further advancements in agentic workflows before GA, so expect additional improvements.
• Deeper Antigravity integration: Google's agentic development platform is being built around Gemini 3.1 Pro's reasoning capabilities.
• Continued benchmark progress: the pace of improvement from 3.0 to 3.1 suggests Google is iterating rapidly. The jump from 31.1% to 77.1% on ARC-AGI-2 happened in just a few months.
• Multimodal expansion: Gemini's native multimodal architecture (text, image, audio, video) continues to improve, with video understanding already at state-of-the-art levels.

9How Lushbinary Can Help You Integrate Gemini 3.1 Pro

At Lushbinary, we specialize in integrating AI models into production systems. Gemini 3.1 Pro's combination of strong reasoning, massive context window, and competitive pricing makes it a compelling choice for businesses looking to add AI capabilities to their products and workflows.

Here's what we bring to the table:

Whether you're a startup exploring AI-powered features, an enterprise migrating from another model provider, or a team building agentic workflows from scratch, we can take you from prototype to production on Gemini 3.1 Pro.

Related reading: MCP Developer Guide 2026 · How OpenClaw Works Behind the Scenes