Gemini 3.1 Pro Pricing: $1.25/M Input — ARC-AGI-2 77.1%, Native Video, 1M Context (2026)
February 2026 — Google Gemini 3.1 Pro costs $1.25 input / $10 output per 1M tokens. 77.1% ARC-AGI-2, native video understanding, 1M context window. Full pricing breakdown vs GPT-5, Claude Opus 4.6.
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 aggressive $1.25/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
| Metric | Value |
|---|---|
| Input Price | $1.25 / 1M tokens |
| Output Price | $10.00 / 1M tokens |
| Context Window | 1,000,000 tokens |
| Max Output | 16,384 tokens |
| Release Date | February 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
| Model | Input | Output | Context | ARC-AGI-2 / SWE-bench |
|---|---|---|---|---|
| Gemini 3.1 Pro | $1.25 | $10.00 | 1M | 77.1% ARC-AGI-2 |
| GPT-5 | $1.25 | $10.00 | 400K | — |
| Claude Opus 4.6 | $5.00 | $25.00 | 200K | 80.8% SWE-bench |
| Claude Sonnet 4.6 | $3.00 | $15.00 | 200K | 79.6% SWE-bench |
| GPT-5.3 Codex | $2.00 | $10.00 | 200K | — |
| Gemini 2.5 Pro | $1.25 | $10.00 | 1M | — |
| DeepSeek V3.2 | $0.27 | $1.10 | 128K | — |
Key takeaway: Gemini 3.1 Pro matches GPT-5 on input pricing ($1.25/M) while offering 2.5x the context window (1M vs 400K). Against Claude Opus 4.6, it costs 75% less on input and 60% 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)
| Model | Monthly Cost |
|---|---|
| DeepSeek V3.2 | $2.46 |
| Gemini 3.1 Pro | $18.75 |
| GPT-5 | $18.75 |
| Claude Sonnet 4.6 | $31.50 |
| Claude Opus 4.6 | $52.50 |
Startup (1M input + 500K output tokens/day)
| Model | Monthly Cost |
|---|---|
| DeepSeek V3.2 | $24.60 |
| Gemini 3.1 Pro | $187.50 |
| GPT-5 | $187.50 |
| Claude Sonnet 4.6 | $315.00 |
| Claude Opus 4.6 | $525.00 |
Production Scale (10M input + 5M output tokens/day)
| Model | Monthly Cost |
|---|---|
| DeepSeek V3.2 | $246 |
| Gemini 3.1 Pro | $1,875 |
| GPT-5 | $1,875 |
| 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 Case | Best Choice | Why |
|---|---|---|
| Long document analysis (>200K tokens) | Gemini 3.1 Pro | Only flagship with 1M context |
| Video understanding tasks | Gemini 3.1 Pro | Native video support |
| Abstract reasoning & research | Gemini 3.1 Pro | 77.1% ARC-AGI-2 |
| Cost-effective flagship | Gemini 3.1 Pro or GPT-5 | Tied at $1.25/M input |
| Maximum code quality | Claude Opus 4.6 | 80.8% SWE-bench |
| Agentic coding workflows | GPT-5.3 Codex | Purpose-built for agents |
| Budget-constrained projects | DeepSeek V3.2 | $0.27/M input |
Gemini 3.1 Pro vs Gemini 2.5 Pro
| Feature | Gemini 3.1 Pro | Gemini 2.5 Pro |
|---|---|---|
| Input Price | $1.25/M | $1.25/M |
| Output Price | $10.00/M | $10.00/M |
| Context Window | 1M | 1M |
| Max Output | 16,384 | 8,192 |
| Video Understanding | Native | Frame-based |
| ARC-AGI-2 | 77.1% | — |
| Release | Feb 2026 | Mar 2025 |
Same pricing, but Gemini 3.1 Pro is strictly better in capabilities. If you’re already on Gemini 2.5 Pro, upgrading to 3.1 Pro is a free performance boost.
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 the best value flagship model for developers who need long-context processing, multimodal capabilities, or strong abstract reasoning. At the same $1.25/M input price as GPT-5 but with a 1M context window (vs GPT-5’s 400K), it offers more capability per dollar for context-heavy workloads.
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.
Related resources:
- AI Model Pricing Calculator — Compare monthly costs across 40+ models
- AI Token Counter — Count tokens before making API calls
- AI API Pricing Comparison 2026 — Full pricing table for all 7 major providers
- Google Gemini API Pricing Guide 2026 — Gemini 2.5 Pro/Flash pricing and free tier
- GPT-5.3 Codex Pricing Guide — OpenAI’s new agentic coding model
- Claude API Pricing 2026 — Opus 4.6 vs Sonnet 4.6 vs Haiku
- DeepSeek API Pricing 2026 — V3.2 at $0.27/M, the budget king