Google DeepMind announced Gemini 4 Carbon on Oct. 28, 2026, introducing the company's next frontier model and its strongest to date, with state-of-the-art cybersecurity and long-horizon capabilities. The announcement was published on the Google DeepMind blog by Koray Kavukcuoglu, SVP, Google DeepMind and Chief AI Architect, Google.

Carbon ranks #1 on the recently updated v5.0 of the Artificial Analysis Intelligence Index at 59. The company reports significant gains across coding and agentic tasks, as well as across key capabilities critical for cybersecurity defense, landing a firm lead in SEC-bench Pro (88.2%) for finding vulnerabilities, ExploitGym (54.8%) for exploitation, and CWE-bench (71.0%) for patching. On internal benchmarks, Carbon drives a strong uplift in generating secure code, and in live coding environments with Google DeepMind's own teams it shows reduced misalignment and fabrication rates.

Building on Gemini 4 Argon, which was launched two weeks earlier, Carbon illustrates the pace at which the company is pushing the frontier forward. "Our researchers and models are working hand in hand to advance capabilities faster, while strengthening our safeguards in tandem," the company stated.

Deliberate rollout and pricing

Google DeepMind said it is taking a deliberate approach to rollout and is actively engaged in the U.S. government's voluntary process for pre-release model testing. Starting this week, Carbon will be made available to a subset of cyber defenders, and access will gradually be phased to additional trusted partners through the company's Fairwind Program. The company said it is continuing to gather feedback and iterate on guardrails before making Carbon available to developers, businesses, and consumers via its product surfaces as soon as possible. The company did not announce a date for that wider developer, business, and consumer release, so the progression of access through the Fairwind Program is the near-term development to watch.

Gemini 4 Carbon will launch at the same introductory price as Argon: $2 per million input tokens and $10 per million output tokens, with cached input tokens priced at 95% off the input token price. After the introductory period expires, pricing of $4 per 1 million input tokens and $20 per 1 million output tokens will apply.

Coding and reasoning for long-horizon tasks

Designed to take on much harder, long-horizon engineering problems, Carbon is built for sustained agentic workflows. Internally, Google DeepMind's teams have seen the model run for days, persisting through dead ends to tackle complex, multi-step engineering tasks such as root-causing and patching subtle bugs across large codebases and low-level systems.

Building on user feedback, the company focused on improving model performance across a variety of domains, including coding, agentic, and scientific tasks, as well as full-stack web development and multimodal understanding. With improved quality of output and artifacts in web development, Carbon jumps +89 elo points to land at #4 (1769) on WebDev Arena.

State-of-the-art cybersecurity performance

Google DeepMind said Gemini 4 Carbon delivers a significant leap in cybersecurity capabilities, achieving state-of-the-art performance across the cybersecurity defense lifecycle — vulnerability detection, validation, and remediation.

The company's teams are already seeing strong gains in cyberdefense. On internal benchmarks, Carbon achieves more than 2x uplift in success rate for generating secure code over Argon. The Chrome team has reported that Carbon performed more than 10X better than another lab's large frontier model when generating high-quality patches. Wiz, Google's cloud security platform, also observes Carbon leading on benchmarks for web penetration testing, a core capability for Wiz's Scan for Good initiative.

Carbon excels across key external benchmarks, which the company said were evaluated without guardrails — meaning the published scores reflect the model's unaided capability rather than its behavior with safety tooling applied:

• Finding real vulnerabilities: Core to cybersecurity defense is finding real vulnerabilities. Carbon achieves a state-of-the-art 88.2% on SEC-bench Pro, autonomously uncovering complex flaws buried in real-world software.
• Validating risk through exploitation: To prioritize which vulnerabilities to remediate first — or remediate at all — cyber defenders increasingly rely on models to check which vulnerabilities are exploitable. Carbon sets a new state-of-the-art on the popular exploitation benchmark ExploitGym (54.8%).
• Patching at the root cause: After identifying vulnerabilities, fixing the root cause is a critical step in the cybersecurity defense lifecycle. Carbon reaches 71.0% on Collinear's CWE-bench, turning validated findings directly into working code fixes.

Advancing frontier model safety and security

Gemini 4 Carbon builds on the same multi-layered safety and security stack as Argon — combining model training, real-time misuse defenses, prompt-injection resilience, and chain-of-thought monitoring. Google DeepMind made significant strides in model alignment with Argon and reported its propensities to behave in an aligned way in its Safety and Security report. With Carbon, the company said it went a step further on alignment, training the model to respond to complex or high-pressure tasks in the right way.

• Reducing shortcuts and loophole exploitation: The company further mitigated shortcut attempts in training while ensuring high-quality coding performance. Carbon reduced successful cheating on Terminal-Bench 4.0 to 0.0%, with attempts to cheat dropping to 0.4% — all while improving overall accuracy. In live coding environments with internal teams, high-severity misalignment alerts dropped by almost 80%.
• Greater transparency and honesty: In internal testing, Carbon cuts unsupported claims by approximately 2x over Argon. It puts methodological caveats directly into the deliverable, or withholds blocked actions with a clear list of what remains required, rather than fabricating or hedging around missing evidence.
• Improved collaboration in the face of ambiguity: Rather than guessing or forcing a path forward, Carbon retrieves the relevant sources and surfaces discrepancies to the user before acting — as a result, users should observe a much better collaborative experience.
• Following through without overstepping: Carbon simultaneously reduced overreach by 26% and under-service by 29%, resulting in much more reliable execution of multi-step plans end-to-end while respecting project constraints and staying strictly within scope.
• Resisting prompt injection: While Argon previously led Gray Swan's Indirect Prompt Injection (IPI) Benchmark in prompt injection resistance with a very low 0.7% attack success rate, Carbon achieves 0.0% — resisting every evaluated attack attempt.

Coming soon to developers, businesses, and consumers

Google DeepMind said pushing the frontier forward requires moving fast while remaining deliberate about deployment. With Gemini 4 Carbon, the company's stated goal is to deliver meaningful leaps in software engineering and cybersecurity defense without compromising on safety or reliability. The company added that it is eager to see how the initial cohort of cyber defenders use the model and looks forward to bringing Carbon to developers, businesses, and consumers soon.