Google: Gemini 4 Argon

google/gemini-4-argon

Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across...

Modalities

In / out price

$2 / $10 per 1M

Context

1.05M

Released

Oct 13, 2026

Why use Gemini 4 Argon

Understands images
Understands audio
Reads PDFs and other files
Step-by-step reasoning mode
Tool and function calling (agent-ready)
Structured (JSON) outputs
Very long context: whole books or codebases in one prompt

Pricing

Input	$2 / 1M tokens
Output	$10 / 1M tokens
Cached input (read)	$0.1 / 1M tokens
Cache write	$0.19 / 1M tokens
Image input	$2 / 1M tokens

List prices via OpenRouter, checked daily. Real cost depends on the provider and on reasoning tokens.

How it ranks

Intelligence index52.6

Source: Artificial Analysis (artificialanalysis.ai) via OpenRouter (openrouter.ai/rankings).

Cost calculator

Pick a task, set how often you run it, and compare what it costs on each model.

TaskInput tokens≈ 602 wordsOutput tokens≈ 1,504 wordsRuns per month

Input served from cache: 0%Repeated prompts (same instructions or document) are billed at the cheaper cache-read price where the model supports it.

Model	Per run	Per month	Per 1,000 runs
Google: Gemini 4 Argon	$0.022	$21.60	$21.60

Estimates from list prices via OpenRouter; real bills vary by provider and reasoning tokens.

Will it fit? Context window simulator

Each square is about one page (500 words). Colored squares are your content; grey squares are free space in the model's context window.

Your content

Novel (90,000 words)

Total: about 120,000 tokens (≈ 90,226 words). Token counts are estimates.

Models

Zoom (square size): 6pxZoom out to see a whole million-token window at once.