Gemini 4 Argon is an AI model of Google, announced on September 30, 2026. It was built to perform complicated, multi-step professional jobs across software development, research, finance and cybersecurity. Its notable feature is a cap of 1 million tokens of output.
But how does it stack up against Claude 5.5 and ChatGPT 6? For a correct comparison, we will analyze Claude Opus 5.5 and GPT-6 Astra because ChatGPT is OpenAI’s application.
Key Gemini 4 Argon Features
According to Google, the model offers:
- Extended reasoning: solves problems that require multiple steps.
- Advanced software development: supports code debugging, optimization and migration.
- Multimodal analysis: interprets charts, documents and long videos.
- Specialized work: assists with financial research and legal document preparation.
- Defensive cybersecurity: detects, validates and patches vulnerabilities.
- Extended output: up to 1 million tokens, compared with the previous limit of 64,000.
The last value is the output capacity. The announcement doesn’t define the size of the input context window, which dictates how much information the model may receive.
Gemini 4 Argon vs. Claude Opus 5.5 vs. GPT-6 Astra
The table compares API prices per million tokens, in US dollars, and use cases described by the providers.
| Feature | Gemini 4 Argon | Claude Opus 5.5 | GPT-6 Astra |
|---|---|---|---|
| Company | Anthropic | OpenAI | |
| Input, base rate | $2 introductory; then $4 | $4 | $10 |
| Output, base rate | $10 introductory; then $20 | $20 | $50 |
| Main use cases | Software development, specialized work and cybersecurity | Coding agents and extended knowledge work | Reasoning, software development, research and document creation |
| Access | Initially restricted to the Fairwind Program | Commercially available | Available through the API and ChatGPT, subject to plan |
Sources: official notification and paperwork of all the three providers. API fees are not the same as the pricing of application subscriptions.
GPT-6 Astra provides greater rate limits for requests that have over 272,000 input tokens. Cost can also be influenced by faster modes, tools and other choices.
What Do the Performance Tests Show?
Google scores 77.9% on DeepSWE v1.1, 91.7% on LVBench and 51.3% on AutomationBench. Since each test measures different talents, do not compare these percentages directly.
Artificial Analysis rates Argon at the High setting on the Intelligence Index, giving it a score of 53. The group also notes that the model used 110 million output tokens during evaluation, which is above the median for reasoning models on a similar price tier. The cost of a task is not simply the price of a token.
When Can You Use Gemini 4 Argon?
It will be rolled out to paying API customers and subscribers to Google AI Ultra, but no timeline has been given. Fairwind is designed to provide first access to reputable cybersecurity specialists.
To assess the model once access is available:
- Choose tasks that match your actual work.
- Compare quality using the same documents and instructions.
- Measure the entire cost, the response time and the necessary corrections.
- Double check answers before posting content or making changes.
For large projects, a higher output limit might help. You should choose the one that gives you the best results with the least amount of reviewing effort.
