Last refreshed 2026-10-17. Next refresh: weekly.
Why use Gemini 4 Argon on Google AI Studio?
Google AI Studio offers Gemini 4 Argon with pay-as-you-go pricing at $2.00/1M input tokens. Google AI Studio is a model prototyping environment and API access point for Gemini models, offering an inference playground for developers to test and build AI applications.
Compare Gemini 4 Argon across 4 providers to find the best fit for your use caseSetup recipe
Python + curlpip install google-genaiexport GOOGLE_API_KEY=...import os
from google import genai
client = genai.Client(api_key=os.environ["GOOGLE_API_KEY"])
response = client.models.generate_content(gemini-4-argonRequest example
import os
from google import genai
client = genai.Client(api_key=os.environ["GOOGLE_API_KEY"])
response = client.models.generate_content(
model="gemini-4-argon",
contents="Hello"
)
print(response.text)Gotchas
- Use the model name directly, e.g. "gemini-2.0-flash", "gemini-1.5-pro", or "gemini-2.5-pro-preview-05-06".
- The examples expect GOOGLE_API_KEY; rename it only if your application config maps the new variable.
Compare Gemini 4 Argon Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Google AI Studio | $2.00 | $10.00 |
| GCP Vertex AI | $2.00 | $10.00 |
| OpenRouter | $2.00 | $10.00 |
| Vercel AI Gateway | $2.00 | $10.00 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $2.00 |
| Output tokens | $10.00 |
| Image input | $1.00 |
| Video input | $1.00 |
| Audio input | $1.00 |
Capabilities
About Gemini 4 Argon
Gemini 4 Argon is a Google DeepMind reasoning model, announced on September 30, 2026 for trusted cyber defenders and testers in Google's Fairwind Program and made generally available on October 13, 2026 through the Gemini API, Gemini Enterprise Agent Platform, Google Antigravity and the Gemini app. Google built it for long-horizon software engineering, legal and finance work, cybersecurity defense and science. It takes text, image, video, audio and PDF input and returns text. Input and output share a 1,048,576-token limit; one synchronous request returns up to 65,536 output tokens, and long decodes extend output up to 1,048,576 tokens.