Google’s Gemini 4 Carbon takes benchmark lead with access limited to cyber defenders

Google is apparently making up for lost time. Four weeks after its overdue frontier model finally surfaced as Gemini 4 Argon, the company unveiled a successor on October 28 that it calls its strongest model yet: Gemini 4 Carbon. Its first focus area is finding software flaws. The model currently takes first place on Artificial Analysis’s updated Intelligence Index with a score of 59, narrowly ahead of Anthropic and OpenAI. Opus 5.5 has a score of 58.

The gap Carbon follows opened in May. At its I/O conference, Google promised Gemini 3.5 Pro in June. That model slipped repeatedly, and Bloomberg reported its coding performance fell short of internal goals. When Google announced Argon on September 30, a spokesperson told Reuters that the company no longer plans to release 3.5 Pro and that Argon is larger than Google’s earlier Pro models. Cheaper Flash models filled in, from 3.5 Flash at I/O to 3.8 Flash on September 2, and Gemini 3.1 Pro Preview stayed Google’s newest Pro model until Argon arrived on September 30.

Carbon scores 59 at its high reasoning setting on version 5.0 of the independent evaluator’s index. In the same Artificial Analysis ranking, GPT-6 Astra scores 57 and GPT-6.1 Sol 55 in their listed maximum-reasoning configurations. The index combines nine evaluations spanning coding, scientific reasoning, knowledge and other tasks, among them Terminal-Bench 4.0, FrontierCode 2.0, HLE-Diamond and Terminal-Bench-Science 0.1. Argon scores 50 on the same version, nine points below Carbon. Artificial Analysis had scored Argon at 53 on the earlier v4.3.2 index, so scores carry over only within one index version.

Google reports Carbon scores 88.2% on SEC-bench Pro for vulnerability discovery, 54.8% on ExploitGym for exploitation and 71.0% on CWE-bench (a defensive cybersecurity and AI evaluation benchmark from Collinear AI) for patching. Google evaluated these external benchmarks with guardrails disabled, a condition that limits direct extrapolation to the safeguarded product. In its own testing, Google says Carbon more than doubles Argon’s success rate at generating secure code, and its Chrome team found Carbon “more than 10X better” at high-quality patches than another lab’s large frontier model, which Google leaves unnamed. The company also reports fourth place on WebDev Arena at 1,768 Elo, an 89-point improvement.

Google built Carbon for long-horizon engineering work and says its internal teams have seen the model run for days, persisting through dead ends on multi-step tasks. On Gray Swan’s indirect prompt-injection benchmark, which Argon previously led at a 0.7% attack success rate, Google reports 0.0% for Carbon.

The performance lead comes with substantial token consumption, a trait Carbon shares with Argon, which generated 110 million output tokens on the same index, about 1.7 times the median. For Carbon, Artificial Analysis recorded 200 million output tokens across its index evaluation, about three times the 64 million median for comparable models, and calculated a weighted average cost of $7.76 per task using standard pricing. That puts Carbon below Opus 5.5 at maximum reasoning ($10.04) and above GPT-6 Astra ($6.24) and GPT-6.1 Sol ($1.27). Artificial Analysis measured a median 97.5 seconds before Carbon’s first output token on Google’s API, against a 3.6-second median for comparable models. Google plans introductory rates of $2 per million input tokens and $10 per million output tokens, the same as Argon’s, rising to $4 and $20 after the promotion. Cached inputs receive a 95% discount.

The release extends the restricted cyber-defender rollout that accompanied Argon, which Google opened first to its Fairwind Program, launched September 2 for government authorities, critical infrastructure operators and software maintainers. Google plans to give selected defenders access to Carbon this week and expand through Fairwind to more trusted partners. Broader developer, business and consumer access remains a future phase, which Google says will follow feedback and further work on guardrails. Google also says it is taking part in the U.S. government’s voluntary process for pre-release model testing.