Gemini 4 Argon
Gemini 4 Argon is Google's most capable model, built for the hardest problems: long-horizon coding, agentic workflows, scientific, legal and financial analysis, and defensive security work. It reads text, images, audio, video and PDFs across a 1M-token context, thinks at low, medium or high effort, and calls tools reliably over many steps.
The real Google model
Same weights, same API, same answers. We change only how you pay for it: one key for every maker, one bill, no separate account to open. Every figure on this page comes from Google’s own page — check it.
Maker's own pagePrice
per 1M tokens
Input
Output
$2.00
$10.00
Context
1,048,576
up to 65,536 out
65,536 by default here
Modalities
Released
Oct 13, 2026
What it would cost you
1000 tokens is roughly 750 English words.
How it is served
Requests are retried automatically if a provider is unavailable.
Similar models
Models built for the same kind of work, at a similar price.
We do not mark up the price of tokens. It is the same price the maker charges.
Use it from your code
from openai import OpenAI
# Works with the official openai package (pip install openai)
client = OpenAI(
base_url="https://api.flintbeam.com/v1",
api_key="sk-live-your-api-key"
)
response = client.chat.completions.create(
model="google/gemini-4-argon",
messages=[
{"role": "system", "content": "You are an experienced software engineer."},
{"role": "user", "content": "Describe the architecture of a distributed cache."}
],
temperature=0.7,
max_tokens=1500
)
print(response.choices[0].message.content)