Gemini 4 Argon API: key, first call and which tool to use

The Gemini 4 Argon API is the Gemini API with the model id `gemini-4-argon` on a billed project. Google made it generally available on 2026-10-13, and its docs show the call shape: the `google-genai` Python SDK, the Interactions API, and a key in `GEMINI_API_KEY`.

Old code breaks in small ways on Argon. Some sampling settings are ignored, a few now return HTTP 400, and the thinking setting has a new name. This post walks through the key, a first call, the parameters to remove, and how to choose between Google's search grounding, your own functions and an MCP server. By the end you have a working call and a plan for the tools your agent needs.

Last checked 2026-10-15, against Google's developer docs and looot's live catalog.

How do you get a Gemini 4 Argon API key?

Create an API key in Google AI Studio and link a billing account to its project. Argon is not on the free tier, so a key on a project without billing cannot call it. Linking billing puts the project in Tier 1 on Google's rate limits page (read 2026-10-15).

The rate limits page does not print Argon's requests per minute. It sends you to AI Studio, where each project sees its own limits. What a call costs is in Gemini 4 Argon pricing.

Your first Gemini 4 Argon API call

Install the SDK, put the key in the environment, and send one short prompt. This is Google's quickstart (read 2026-10-15) with the model id changed from `gemini-3.8-flash` to `gemini-4-argon`.

pip install -U google-genai
export GEMINI_API_KEY=...   # a key on a project with billing linked

from google import genai

client = genai.Client()
interaction = client.interactions.create(
    model="gemini-4-argon",
    input="Explain how AI works in a few words",
)
print(interaction.output_text)

The same call over REST goes to `https://generativelanguage.googleapis.com/v1beta/interactions` with the key in an `x-goog-api-key` header and a JSON body holding `model` and `input`. We have not run this exact call against Argon, so send one cheap prompt first and read the error if there is one.

The model takes text, images, video, audio and PDF as input and returns text. Its context window is 1,048,576 tokens shared by input and output, with 65,536 output tokens per request by default, per the Gemini 4 Argon model page (read 2026-10-15).

Which parameters does the Gemini 4 Argon API reject?

Argon drops the old thinking budget and most sampling settings. Google Cloud's Gemini 4 Argon developer guide (read 2026-10-15) lists the rules below. It is written for Google Cloud's Agent Platform, so confirm each one on your own key.

The guide also asks for `google-genai` 2.30.1 or newer. If a call that worked on an older Gemini model now fails with 400, remove the settings in this table first.

Grounding, functions or MCP: which tool should Argon use?

Use Google's search grounding for answers backed by Google Search, your own functions for your own systems, and an MCP server for data neither one returns, such as company records or ranked Google positions. All three are listed as supported on the model page, and many agents combine them.

Grounding is one line in the tools list, the same shape as Google's grounding docs (read 2026-10-15):

interaction = client.interactions.create(
    model="gemini-4-argon",
    input="What did Google announce for Gemini 4 Argon this week?",
    tools=[{"type": "google_search"}],
)

Each search the model runs is billed, so read the `google_search_call` steps in the response to see how many it made. When grounding gets expensive at your volume, Grounding with Google Search pricing works through the numbers.

Add a looot data step to the Gemini 4 Argon API

looot is one MCP server that reaches many data providers, so Argon can look up a company, read Google results with positions or find a work email without a key for each vendor. The `mcp_server` tool goes in the same `tools` list as grounding. The full code is in Gemini 4 Argon MCP.

Two jobs an Argon agent often needs are company enrichment, which takes a domain and returns the company's name, size and links, and Google results with positions for SEO work. The model reads each job's price before it runs it, and a miss at one provider moves to the next.

What it cannot do

• looot does not resell Gemini 4 Argon. Argon is not in looot's catalog today; your key and your Google bill stay yours.
• It does not replace search grounding. Grounding answers from Google Search inside one call; looot adds data jobs grounding does not return.
• We have not run the calls in this post against Argon. They follow Google's quickstart and guide with the model id changed.
• It does not run on a timer. A recurring report needs scheduled runs, not available yet.
• The Gemini 4 Argon vs GPT-6.1 Sol vs Claude Opus 5.5 comparison covers the other two models; this post covers only Google's API.