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Gemini 4 Argon pricing

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... Live index: 4 priced offers. Best input $2.00 per million tokens from Github Copilot. Best output $10.00 per million tokens from Github Copilot.

1.0M context·4 providers·verified Oct 13, 2026
Best input$2.00per 1M tokens · Github Copilot
Best output$10.00per 1M tokens · Github Copilot

Pricing across providers

All figures are list prices per million tokens unless a column says otherwise. 4 offers are listed for Gemini 4 Argon. Best input in this view: Github Copilot.

GC
Github Copilot
Input / 1M
$2.00
Output / 1M
$10.00
Cached in: $0.100
GV
Google Vertex
Input / 1M
$2.00
Output / 1M
$10.00
Cached in: $0.100
O
Openrouter
Input / 1M
$2.00
Output / 1M
$10.00
G
Googlenative
Input / 1M
$2.00
Output / 1M
$10.00
Cached in: $0.100

Input vs output · per provider

Cost calculator

The calculator uses the same dollars per million tokens as the table. Adjust sliders to see how Gemini 4 Argon cost scales with traffic.

Provider

In: $2.00/M·Out: $10.00/M·Cache: $0.100/M

0.200000¢ / req

0.500000¢ / req

Daily
$70
Monthly
$2.1K
Annual
$25.6K

Model specifications

Context length, caps, and capability flags for Gemini 4 Argon. Values follow the main provider (Google) record in our index.

Context window
1,048,576 tokens
Max output
65,536 tokens
Vision (images)
Yes
Tool / function calling
Yes
Streaming
No
Released
Oct 2026
Primary provider
Google
Model family
N/A

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Frequently asked questions

Quick frequently asked items for Gemini 4 Argon pricing and limits. The short model note from our index: 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...

Gemini 4 Argon costs $2.00 per million input tokens and $10.00 per million output tokens via the native API. Prompt caching reduces input costs to $0.10/M tokens.

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