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Gemini 3.1 ProGoogle AIAPI PricingARC-AGI-2Multimodal AI

Gemini 3.1 Pro Pricing: $2.00/$12 per M — 1M Context, Video

Google Gemini 3.1 Pro costs $2.00 input / $12.00 output per 1M tokens. 77.1% ARC-AGI-2 score, native video understanding, 1M context window, free tier available. Pricing vs GPT-5, Claude Opus 4.6.

DevTk.AI 2026-02-26 Updated 2026-03-04 7 min read

Google’s Gemini 3.1 Pro launched in February 2026 as the most capable Gemini model to date. With a 77.1% score on ARC-AGI-2, native video understanding, and Google’s competitive $2.00/M input pricing, it immediately becomes one of the most competitive flagship models on the market.

This guide covers everything developers need to know: pricing, capabilities, how it compares to GPT-5 and Claude, and when to choose it over alternatives.

Gemini 3.1 Pro Pricing

MetricValue
Input Price$2.00 / 1M tokens
Output Price$12.00 / 1M tokens
Context Window1,000,000 tokens
Max Output16,384 tokens
Release DateFebruary 2026

Note: Gemini 2.5 Pro has separate long-context pricing ($2.50 input, $15.00 output for >200K contexts). Check whether Gemini 3.1 Pro inherits this tiered pricing or uses flat rates across all context lengths.

How Gemini 3.1 Pro Compares

ModelInputOutputContextARC-AGI-2 / SWE-bench
Gemini 3.1 Pro$2.00$12.001M77.1% ARC-AGI-2
GPT-5$1.25$10.00400K
Claude Opus 4.6$5.00$25.001M beta80.8% SWE-bench
Claude Sonnet 4.6$3.00$15.001M beta79.6% SWE-bench
GPT-5.3 Codex$2.00$10.00200K
Gemini 2.5 Pro$1.25$10.001M
DeepSeek V3.2$0.27$1.10128K

Key takeaway: Gemini 3.1 Pro is priced at $2.00/M input — slightly above GPT-5’s $1.25/M but with 2.5x the context window (1M vs 400K). Against Claude Opus 4.6, it costs 60% less on input and 52% less on output. The 1M context window remains a unique advantage no other flagship model matches.

Monthly Cost Estimates

Solo Developer (100K input + 50K output tokens/day)

ModelMonthly Cost
DeepSeek V3.2$2.46
Gemini 3.1 Pro$24.00
GPT-5$18.75
Claude Sonnet 4.6$31.50
Claude Opus 4.6$52.50

Startup (1M input + 500K output tokens/day)

ModelMonthly Cost
DeepSeek V3.2$24.60
GPT-5$187.50
Gemini 3.1 Pro$240.00
Claude Sonnet 4.6$315.00
Claude Opus 4.6$525.00

Production Scale (10M input + 5M output tokens/day)

ModelMonthly Cost
DeepSeek V3.2$246
GPT-5$1,875
Gemini 3.1 Pro$2,400
Claude Sonnet 4.6$3,150
Claude Opus 4.6$5,250

Want exact numbers for your usage? Try our AI Model Pricing Calculator.

What’s New in Gemini 3.1 Pro

77.1% ARC-AGI-2

ARC-AGI-2 measures abstract reasoning and novel problem-solving — the kind of tasks where AI models historically struggle. Gemini 3.1 Pro’s 77.1% score represents a significant jump in reasoning capabilities, making it suitable for complex analytical and research tasks.

Native Video Understanding

Unlike previous Gemini models that processed video frame-by-frame, Gemini 3.1 Pro has native video understanding — it processes video as a continuous stream, understanding temporal relationships, scene changes, and audio-visual alignment. This opens up use cases like:

  • Video content moderation and summarization
  • Surveillance and monitoring analysis
  • Educational video processing
  • Sports and event analysis

1M Token Context Window

The 1M token context window carries over from Gemini 2.5 Pro. This remains the largest production context window among major API providers. For perspective:

  • 1M tokens ≈ 750,000 words ≈ 10+ full-length books
  • Process entire codebases, legal document sets, or research paper collections in a single prompt
  • No chunking or retrieval-augmented generation needed for most document sets

16K Max Output

Max output increased to 16,384 tokens (up from 8,192 in Gemini 2.5 Pro). This is still lower than Claude Opus 4.6’s 128K output, but sufficient for most generation tasks.

Getting Started with Gemini 3.1 Pro

Python

import google.generativeai as genai

genai.configure(api_key="your-api-key")

model = genai.GenerativeModel("gemini-3.1-pro")

response = model.generate_content(
    "Analyze this codebase and suggest architectural improvements.",
    generation_config={
        "temperature": 0.7,
        "max_output_tokens": 8192,
    }
)

print(response.text)

JavaScript / TypeScript

import { GoogleGenerativeAI } from '@google/generative-ai';

const genAI = new GoogleGenerativeAI('your-api-key');
const model = genAI.getGenerativeModel({ model: 'gemini-3.1-pro' });

const result = await model.generateContent(
  'Analyze this codebase and suggest architectural improvements.'
);

console.log(result.response.text());

OpenAI-Compatible Endpoint

Google also offers an OpenAI-compatible endpoint, making migration easier:

from openai import OpenAI

client = OpenAI(
    api_key="your-google-api-key",
    base_url="https://generativelanguage.googleapis.com/v1beta/openai/"
)

response = client.chat.completions.create(
    model="gemini-3.1-pro",
    messages=[
        {"role": "user", "content": "Explain quantum entanglement simply"}
    ]
)

When to Choose Gemini 3.1 Pro

Use CaseBest ChoiceWhy
Long document analysis (>200K tokens)Gemini 3.1 ProOnly flagship with 1M context
Video understanding tasksGemini 3.1 ProNative video support
Abstract reasoning & researchGemini 3.1 Pro77.1% ARC-AGI-2
Cost-effective flagshipGPT-5 or Gemini 3.1 ProGPT-5 $1.25/M, Gemini 3.1 Pro $2.00/M input
Maximum code qualityClaude Opus 4.680.8% SWE-bench
Agentic coding workflowsGPT-5.3 CodexPurpose-built for agents
Budget-constrained projectsDeepSeek V3.2$0.27/M input

Gemini 3.1 Pro vs Gemini 2.5 Pro

FeatureGemini 3.1 ProGemini 2.5 Pro
Input Price$2.00/M$1.25/M
Output Price$12.00/M$10.00/M
Context Window1M1M
Max Output16,3848,192
Video UnderstandingNativeFrame-based
ARC-AGI-277.1%
ReleaseFeb 2026Mar 2025

Gemini 3.1 Pro costs slightly more than 2.5 Pro ($2.00/$12.00 vs $1.25/$10.00), but the capability upgrade — native video understanding, 77.1% ARC-AGI-2, and doubled max output — justifies the premium for most use cases.

Free Tier

Google continues to offer a free tier for Gemini models through AI Studio. Check the Google AI Studio for current free tier limits on Gemini 3.1 Pro.

Bottom Line

Gemini 3.1 Pro is a strong flagship model for developers who need long-context processing, multimodal capabilities, or strong abstract reasoning. At $2.00/M input with a 1M context window (vs GPT-5’s $1.25/M with 400K), it offers significantly more context capacity, making it the better choice for context-heavy workloads despite the slightly higher per-token cost.

If your use case involves long documents, video processing, or you simply want the most context for your money, Gemini 3.1 Pro should be your top choice.

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