Gemini 4 Argon API

Gemini 4 Argon is a text model from Google's Gemini 4 series. It has one shared 1,048,576-token window for input, thinking and output. Thinking depth has three levels (low, medium - the default, high). It supports tool calls and JSON schema output. In Jantaris you call it with the same OpenAI SDK as every other model, without a separate Google account.

A single answer is capped at 32,768 tokens without streaming and 65,536 with streaming, and thinking counts toward that cap. For long answers set stream: true.

Best for

• Analysis of very long documents and file sets
• Summaries and data extraction to JSON
• Tool-using agents at a low token price
• Head-to-head tests with GPT-6 Astra and Claude Opus 5.5 on your own tasks

How to call it

from openai import OpenAI

client = OpenAI(base_url="https://jantaris.com/v1", api_key="sk-jt-...")
resp = client.chat.completions.create(
    model="gemini-4-argon",
    stream=True,
    messages=[{"role": "user", "content": "Summarize this report in 5 bullet points."}],
)
for chunk in resp:
    print(chunk.choices[0].delta.content or "", end="")

FAQ

What is the Gemini 4 Argon API price?

$1.08 / $5.40 per 1M tokens. The vendor announces separate introductory and standard rates, so the price may change - Jantaris always shows the current one.

How long can an answer be?

Up to 32,768 tokens without streaming and 65,536 with streaming, thinking included.

Does Argon generate images or audio?

No, it answers with text only.

How to call Gemini 4 Argon via API

from openai import OpenAI

client = OpenAI(base_url="https://jantaris.com/v1", api_key="sk-jt-...")
resp = client.chat.completions.create(
    model="gemini-4-argon",
    messages=[{"role": "user", "content": "Write a haiku about Baltic amber."}],
)
print(resp.choices[0].message.content)

curl https://jantaris.com/v1/chat/completions \
  -H "Authorization: Bearer $JANTARIS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "gemini-4-argon", "messages": [{"role": "user", "content": "Write a haiku about Baltic amber."}]}'

import OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://jantaris.com/v1", apiKey: process.env.JANTARIS_API_KEY });
const resp = await client.chat.completions.create({
  model: "gemini-4-argon",
  messages: [{ role: "user", content: "Write a haiku about Baltic amber." }],
});
console.log(resp.choices[0].message.content);