Gemini 4 Argon launched at $2 and $10 and goes to $4 and $20 on 1 December. Price your product on the second number.
Every tier on the pricing page doubles on the same date. What changes, what the number includes, and what to do if you are building on the launch rate.
- Model
- gemini-4-argon, generally available 13 October 2026
- Standard to 30 November
- $2 input, $10 output, $0.10 caching
- Standard from 1 December
- $4 input, $20 output, $0.20 caching
- Batch and Flex
- $1 and $5 to 30 November, $2 and $10 from 1 December
- Priority
- $3.60 and $18 to 30 November, $7.20 and $36 from 1 December
- Not available on
- The free tier and the Google AI Pro plan
- Caching
- Implicit only. Explicit caching is not supported
The schedule
Google made Gemini 4 Argon (gemini-4-argon) generally available on 13 October, and its pricing page describes it as a flagship reasoning model built for complex software engineering, deep mathematical and scientific problem solving, autonomous multi step agents and long decode generation up to 1M tokens.
The paid tier price is written as two lines. Input is "$2.00 through November 30, 2026" and "$4.00 starting December 1, 2026". Output, which the page says includes thinking tokens, is $10.00 and then $20.00. Context caching is $0.10 and then $0.20.
Every tier moves together
The increase is not limited to the standard tier. Batch and Flex are $1 input and $5 output through 30 November and $2 and $10 after. Priority is $3.60 and $18, then $7.20 and $36. In each case the later figure is twice the earlier one.
Argon is not available on the free tier or on the Google AI Pro plan, so there is no free route to test it. Caching is implicit only, meaning the model decides what to reuse and the page says explicit caching is not supported, so you cannot structure requests to guarantee a hit the way you can with explicit cache markers elsewhere.
Planning with a price that moves
Take a request with 10,000 input tokens and 2,000 output tokens, with the output including thinking. At the launch rate it costs $0.02 plus $0.02, so $0.04. From 1 December it costs $0.04 plus $0.04, so $0.08. At a million such requests a month, that is $40,000 becoming $80,000.
For comparison, Claude Sonnet 5.5 and GPT-6.1 Sol are both listed at $2 input and $10 output on their own pricing pages as of 15 October, and we found no scheduled change on the pages we read. That makes the December comparison $4 and $20 against $2 and $10 at list rates. Token counts differ between models, so a fair test uses your own prompts and each vendor counter for tokens rather than the rate cards.
What we could not confirm
The Google pricing page does not say whether the December increase could be changed or extended, so assume it happens. We also have not assessed the capability claims, which are the description Google gives. Whether Argon is worth twice the price of its two $2 and $10 neighbours is a question for your evals, not for a rate card.
What to do
- 1Build every cost model and every price you quote customers on $4 and $20, not on the launch rate.
- 2If you want to use the launch rate, treat it as a time limited evaluation window ending 30 November.
- 3Run your evals against Argon, Sonnet 5.5 and GPT-6.1 Sol and compare cost per successful task, not cost per token.
- 4Remember output pricing includes thinking tokens, and that explicit caching is not available.
- 5Put 1 December in the calendar for a pricing review.
Common questions
What does Gemini 4 Argon cost?
$2 input and $10 output per million tokens on the paid standard tier through 30 November 2026, and $4 and $20 starting 1 December 2026, per the Google pricing page.
Does the price rise apply to batch and caching too?
Yes. Batch and Flex go from $1 and $5 to $2 and $10, caching from $0.10 to $0.20, and Priority from $3.60 and $18 to $7.20 and $36.
Is there a free tier for Gemini 4 Argon?
No. The pricing page says it is not available on the free tier or on the Google AI Pro plan.
Does the output price include thinking?
Yes. The pricing page labels the output price as including thinking tokens.
Sources
Read against the primary documentation rather than secondary coverage. Where a figure comes from a provider's own docs, it is quoted as published on 2026-10-15.
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