Gemini 4 Argon zum Startpreis von 2 und 10 Dollar verfügbar

Posted on Oct 13 • Originally published at techaiwire.com

Google made Gemini 4 Argon generally available on October 13, 2026, two weeks after limiting it to cybersecurity partners. Developers can now call it through the paid Gemini API at $2 per million input tokens and $10 per million output tokens. That launch price runs until November 30, and the standard price from December 1 is double.

The Gemini API release notes list gemini-4-argon as generally available from October 13. VentureBeat lists the places it now runs:

Google's developer pages say the model is not on the API's free tier. When Tech AI Wire covered the September 30 launch, only cyber defenders in Google's Fairwind Program could use it. VentureBeat reports that hundreds more security partners now join that program.

The pricing page lists every tier, in dollars per million tokens:

Output prices include thinking tokens, the model's internal reasoning. Cached input is text the model has already processed, billed at a discount. Batch and Flex trade speed for a lower price. Priority costs more for faster, more reliable responses.

For comparison, the same page lists Gemini 3.8 Flash at $0.75 input and $3.75 output.

Google's model guide gives Argon a context window of 1,048,576 tokens. That window is shared by the input, the model's thinking and its output. By default a reply can run to 65,536 tokens. Longer background requests can produce up to about 1 million tokens, minus the input.

The model accepts text, images, video, audio and PDFs, and replies in text only. It supports function calling, code execution, search grounding, structured outputs and computer use in preview. It does not generate images or audio.

Three settings control how hard it thinks: low, medium and high, with medium as the default. Caching is automatic for prompts of at least 4,096 tokens, and the usual temperature and top-p sampling settings are ignored.

VentureBeat reports these scores against rival models:

VentureBeat also cites Google's safety figures: unauthorized shortcuts in 2% of coding evaluation attempts, and a 0.7% success rate for indirect prompt injection attacks over 15 adaptive attempts.

Sam Witteveen, chief executive of Red Dragon AI, gave a mixed verdict to VentureBeat. "This is a really, really, really good model. But is it the best model out there? I actually don't think it is," he said.

This article was first published on Tech AI Wire.

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