AI models · Updated 2026-10-31

Gemini 4 Argon: where it fits

What Argon changes from Gemini 3, who benefits from its long context, and what a typical API month costs.

What changed

Gemini 4 Argon is Google’s current flagship reasoning model, following Gemini 3. Google positions it for complex coding, long-running agents, math, science, and multi-step research. Its context combines input, thinking, and output in one 1,048,576-token limit; it can generate up to that limit with long decode. The Gemini 3 context model instead has separate input and output limits.

Google’s API page lists Argon as stable and the model guide documents built-in function calling, search grounding, code execution, computer use, and file search. These features help only when the task needs them, and their use can add charges.

Who should switch

Try Argon when a task needs a long source bundle or multi-step analysis and shorter-context models lose important details. Google’s release page describes coding, finance, legal, and research workflows. Google AI Pro is $19.99/month in the US and includes Argon in the Gemini app; the API is a separate bill.

Who should stay put

Keep a faster or cheaper model for short, repetitive requests. The API introductory rate ends November 30, 2026: input/output pricing moves from $2/$10 to $4/$20 per million tokens on December 1. Recalculate any monthly budget before leaving an API route in place.

Cost for a typical API month

At 2 million input tokens and 500,000 output tokens, Argon is about $9 at its introductory rates through November 30 and $18 from December 1. This excludes search grounding, other tools, and any workload-specific differences. Google AI Pro and API pricing are separate products.

Place in a suite

Argon can be a coding and long-context research option. Keep a balanced model for normal tasks and compare Argon against it on your actual documents, total completion time, and full cost before moving a route.