GPT-6 Cyber vs Claude Mythos vs Gemini 4 Carbon: Closed Models

Update (9 Nov 2026): Claude Fable 5.2 and Mythos 5.2 are out - prices, access and benchmarks are in my Claude Fable 5.2 guide.

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Autumn 2026 marks the first time that the three largest AI labs each offer a model dedicated specifically to cybersecurity, and none of them are available to regular commercial customers. Anthropic has Claude Mythos, Google launched Gemini 4 Carbon on October 28, and OpenAI announced GPT-6 Cyber on November 5. It is tempting to put them all in one comparison table and pick a clear winner. I built the table, but I will not name a winner, and here is why.

Three models, three gated tiers

Why 54.8 does not beat 48.5

On paper, Carbon leads on both benchmarks where both providers published figures. However, Google explicitly notes that its scores were measured “in a version without cyber safeguards.” OpenAI reports its GPT-6 Cyber score in the exact configuration delivered to vetted customers, highlighting in the same system card that standard GPT-6 Astra with safeguards scores 0%, compared to 42.4% without them. The difference between running a model with safety guardrails on versus off can account for the entire score.

On top of that, neither lab standardizes its parameters: reasoning budget, number of attempts, time allowances, and task versioning remain undisclosed or inconsistent. OpenAI specifies its results “at the highest tested reasoning budget.” Google does not clarify its parameters. Until an independent team runs both models across identical task sets under identical conditions, that six-point delta tells you very little.

Where GPT-6 Cyber offers stronger empirical proof

Rather than relying solely on synthetic benchmarks, look at real-world empirical track records. Here, OpenAI has provided the most concrete evidence so far:

• Linux: 948 unique kernel exploits and 304 critical vulnerability reports with patches, complete with full cost breakdowns (covered in my article on the Linux kernel audit).
• Firefox: 81 newly discovered high-severity vulnerabilities, verified in part by Mozilla advisory MFSA 2026-118 (covered in my article on Firefox).
• External auditors: Independent assessments by NIST CAISSI and Irregular, with Irregular’s verification metrics documented in the system card.

Google relies largely on internal validation for Carbon: the Chrome team noted that the model produces high-quality fixes over 10 times more effectively than an “advanced model from another lab,” while Wiz reported strong performance in web penetration testing. Those are promising signals, but they lack external figures that independent researchers can verify. Anthropic shared reports in the spring of thousands of vulnerabilities found by Glasswing partners, but those figures reflect earlier revisions rather than current model weights.

Where Gemini 4 Carbon might be more versatile

Carbon is not strictly a security model. Google is positioning it as its most capable general-purpose flagship, securing first place on the Artificial Analysis index (59 points), with plans to roll it out to developers, enterprises, and consumers. GPT-6 Cyber sits at the opposite end of the spectrum: a specialized offensive and defensive tool that actually scores slightly lower in general coding than base Astra (82.95% vs 83.24% on ExpertSWE). If Carbon arrives in the general API, it will be far more accessible. Its introductory price of $2/$10 is also one-tenth the cost of GPT-6 Cyber. I covered Carbon in detail in my piece on Gemini 4 Carbon, and Google’s access framework in my overview of Argon and Fairwind.

Where Claude Mythos stands

Anthropic pioneered the closed cybersecurity model model, launching Project Glasswing back in April before expanding partner access in June. For standard workloads, Anthropic offers Claude Opus 5.5 and Fable 5.1, but it has not rolled out a program analogous to Daybreak Blue, where vetted defenders can access standard frontier models with relaxed refusal guardrails. Anthropic has also not released an updated public system card for Mythos with numbers that can be benchmarked directly against GPT-6 Cyber.

What you should choose

The pragmatic answer for most security teams: none of them right now, because none are available off the shelf. Today, your practical options look like this:

• Large organizations running internal red teams: Apply for Daybreak Red and Fairwind concurrently. Access decisions are discretionary, so do not bet your toolchain on a single vendor.
• Solo penetration testers and independent researchers: Your only viable path is Daybreak Blue for GPT-6 Sol and Luna. I detailed the verification workflow in my guide on requesting Daybreak access.
• Defensive teams handling secure code review without a red team: Frontier general models like Opus 5.5, GPT-6 Astra, and Gemini 4 Argon provide ample capability for vulnerability triage and patching. Rapid deployment cycles matter far more than an unreleased exploit model.

You can find my complete coverage and technical breakdown of OpenAI’s cybersecurity model in the GPT-6 Cyber hub.

Sources

• OpenAI, Introducing GPT-6 Cyber and System Card, November 5, 2026
• Google DeepMind, Introducing Gemini 4 Carbon, October 28, 2026

// read moreAI Cybersecurity in 2026: From Mythos to GPT-6 CyberState of AIGPT-6 Cyber Benchmarks: What the System Card Really MeasuresBenchmarksGemini 4 Carbon benchmarks: what Google’s scores showAI Tools

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