After a period of restriction to cybersecurity specialists, Gemini 4 Carbon was launched to general users and businesses this Tuesday, November 10th. This model is presented as the most advanced artificial intelligence developed by Google.
Developers can access the model through the API in Google AI Studio, Android Studio, and Gemini for Business. Costs are set at $2 per million input tokens and $10 per million output tokens (equivalent to approximately R$ 10 and R$ 53). However, this promotional price is only valid until the end of the month, at which point it is expected to double, reaching the cost level of Claude Opus 5.5.
According to The Verge, this pricing structure aims to increase the company's competitiveness against its rivals. Even after the end of the promotional offer, scheduled for the end of November, the cost per token for Carbon will remain below the GPT-6 Astra and Fable 5.2 models.
For the general public, access to Gemini 4 Carbon is available in the Gemini app, Search AI Mode, and Google Antigravity, but only for Google AI Ultra subscribers, whose initial monthly fee is R$ 779.90.
Gemini 4 Carbon positions itself as the most sophisticated AI within Google's offerings, surpassing Gemini 4 Argon, which was released in October. Argon is aimed at tasks requiring greater processing capacity and reasoning, such as scientific investigations, system audits, and identifying code flaws.
Although the model uses more tokens than Argon to perform such activities, it maintains extended verification cycles. This feature allows the AI to analyze multiple possibilities, review partial results, and explore alternatives.
One of the core functionalities introduced with the launch of Gemini 4 Carbon is the /swarm command, initially implemented in Google Antigravity. This command allows a single task to be distributed among multiple AI agents that operate in a coordinated manner.
In this process, Carbon can manage activities that require deeper reasoning, such as planning system architecture, while less complex tasks can be delegated to more agile models. The goal is to enable the execution of multi-phase projects without the user needing to manually orchestrate every step.
In demonstrations conducted by Google DeepMind, the technology was applied to create a library of graphical interfaces in the Rust language during the early morning hours. Another practical example involved agents who developed a three-dimensional game using Three.js, simulating the company's own campus.
In addition to programming tools, the model demonstrated 100% sensitivity in threat detection in Project Fortify, an internal Google system focused on mitigating and identifying vulnerabilities. In additional simulations, it managed to block 99% of intrusion attempts.
The advancement also covers defenses against prompt injection attacks. In internal tests, Gemini 4 Carbon was not susceptible to any type of attack. Furthermore, the company evaluated the model's behavior in scenarios where agents could fabricate results, achieving a 92% success rate in integrity tests.



