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Google makes Gemini 4 Carbon available to developers and enterprises

Google DeepMind has made Gemini 4 Carbon available to developers, enterprises, scientists and consumers, positioning it as its strongest model for cybersecurity and long-horizon agentic work. It is offered through the API in Google AI Studio and Gemini for business at an introductory price of $2 per million input tokens and $10 per million output tokens.

Source: deepmind.google/blog/gemini-4-carbon-is-now-available

Google DeepMind has made Gemini 4 Carbon available to developers, enterprises, scientists and consumers. The company positions Carbon above Gemini 4 Argon for tasks such as complex multi-step coding, debugging and open-ended scientific research, where it uses more tokens to explore and verify its work. Paid developers and enterprises can reach it through the API in Google AI Studio and Gemini for business, and the introductory price rises to $4 per million input tokens and $20 per million output tokens after November 30, 2026.

Google is also previewing /swarm in Google Antigravity, which turns a single prompt into a coordinated team of agents that can be tracked in real time. Developers can assign Carbon to design, coordination and auditing roles and pair it with lighter models. Google says Carbon ranks first on CursorBench 4.0, Perplexity's WANDR and Zapier's AutomationBench at more than 2X lower cost per task than the next best external model.

On cybersecurity, Google says Carbon blocked 99% of attack trajectories from its adaptive red-teaming agent in simulated testing. It also lowered the per-attempt breach rate to 0.8%, down from 3.1% on Argon. Access to Carbon for cyber runs through the Fairwind Program.

Why it matters if you build agents

Developers building agents can now call Carbon through the API for multi-step coding and long agentic tasks. Teams that plan around the introductory price should budget for the higher rate that starts after November 30, 2026. Because Carbon uses more tokens than Argon by design, measure cost per task on your own workloads before switching.

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