GPT-6 Cyber vs GPT-5.6 Cyber: Complete Comparison and Report on Pricing, Context Window, Critical Rating, and Access Rules

GPT-6 Cyber is the cybersecurity model OpenAI released on November 5, 2026 for approved Daybreak Red customers, built on GPT-6 Astra and trained further with reinforcement learning on crash reproduction, exploit development and vulnerability search. GPT-5.6 Cyber is its predecessor in the same program: it arrived in the API on August 7, 2026, is built on GPT-5.6 Sol, and is still listed as an active model on OpenAI's developer site and on Amazon Bedrock. Both are restricted to vetted defenders working on authorized targets, and neither can be called by an ordinary API key, so the comparison concerns security teams, penetration-testing firms and vendors that already hold or are applying for Daybreak Red approval.

The verdict is clear on cost and limits and thin on capability. GPT-6 Cyber costs $20 per 1M input tokens and $100 per 1M output tokens, against $12.50 and $75 for GPT-5.6 Cyber, so input is 60% more expensive and output 33% more expensive; on the three workloads computed below the newer model costs about 1.5 times as much per job at short context. In exchange it brings a 1,050,000-token context window against 400,000 on OpenAI's GPT-5.6 Cyber page, a Critical cybersecurity rating under OpenAI's Preparedness Framework where GPT-5.6 Cyber is rated High, and much better behavior on the one safety test both models share: on OpenAI's ExploitGym honeypot evaluation, run without deployment safety instructions, GPT-6 Cyber exploited the honeypot in 0.07% of rollouts and GPT-5.6 Cyber in 5.51%. OpenAI has published no capability benchmark that scores both models on the same task, so any claim that GPT-6 Cyber finds or exploits more vulnerabilities than GPT-5.6 Cyber rests on comparisons with other models, not on a head-to-head figure.

For teams that work on large codebases, long agent sessions or browser and kernel targets that exceed 400,000 tokens of context, GPT-6 Cyber is the model to request, provided they can meet its additional approval, IP allowlisting and hardware-key requirements. For teams whose tasks fit in a smaller context, who run on Amazon Bedrock or AWS GovCloud, or who price work per engagement, GPT-5.6 Cyber remains the cheaper option with fewer setup steps. Prices in this comparison were verified on OpenAI's and AWS's official pages on November 7, 2026.

··········

⁣⁣⁣⁣⁣⁣⁣⁣⁣⁣⁣⁣

GPT-6 CYBER AND GPT-5.6 CYBER RELEASE TIMELINE AND MODEL IDENTITY.

The two models belong to the Daybreak program, which OpenAI split into two access tiers in August 2026. Daybreak Blue gives approved defenders general-purpose frontier models with reduced refusals for defensive work, and OpenAI describes it as the starting point for most security teams. Daybreak Red gives separately approved access to purpose-trained models for vulnerability reproduction, exploit validation, penetration testing and red teaming. GPT-5.6 Cyber was the purpose-trained model OpenAI named when the Red tier launched, and GPT-6 Cyber is its successor there.

GPT-5.6 Cyber appeared in the OpenAI API changelog on August 7, 2026, together with the `gpt-daybreak-red-latest` and `gpt-daybreak-blue-latest` aliases. OpenAI's August 10 post on expanding Daybreak describes it as built on GPT-5.6 Sol and rated High, below Critical, for cybersecurity capability. Amazon Bedrock lists its launch on AWS as August 12, 2026. GPT-6 Cyber appeared in the changelog on November 5, 2026, the same date printed on its system card, which describes it as a cyber-specialized variant of GPT-6 Astra, the first OpenAI model rated Critical for cybersecurity when it was released on September 3, 2026.

........

Item	GPT-5.6 Cyber	GPT-6 Cyber
API model ID	gpt-5.6-cyber	gpt-6-cyber
API release	August 7, 2026	November 5, 2026
Base model	GPT-5.6 Sol	GPT-6 Astra
Preparedness rating, cybersecurity	High	Critical
Daybreak approval	Daybreak Red	Daybreak Red plus additional model approval
Knowledge cutoff	February 16, 2026	Not published
Status on November 7, 2026	Active (model page, Bedrock lifecycle "Active")	Active

........

The `gpt-daybreak-red-latest` alias is the one element of the older generation that is being phased out. Its model page still resolves to `gpt-5.6-cyber`, marks the alias as deprecated and tells developers to "use the latest cyber model available to you." The `gpt-5.6-cyber` model page itself carries no deprecation notice, and OpenAI's deprecations page lists no retirement date for it. Code that calls the alias should therefore be moved to an explicit model ID, either `gpt-5.6-cyber` to keep current behavior or `gpt-6-cyber` after approval.

··········

GPT-6 CYBER VS GPT-5.6 CYBER API PRICING PER 1M TOKENS.

Both models are billed per token at rates set on their OpenAI model pages. GPT-6 Cyber also appears in the "Cyber models" section of OpenAI's main API pricing page, which describes it as one of "our latest Daybreak models"; GPT-5.6 Cyber is priced only on its own model page and on Amazon Bedrock. Neither model page lists Batch pricing.

........

Price item (USD per 1M tokens)	GPT-5.6 Cyber	GPT-6 Cyber	Change
Input	$12.50	$20.00	+60%
Cached input	$1.25	$2.00	+60%
Cache write	1.25x input ($15.625)	$25.00 (30 minutes), $50.00 (12 hours)	+60% for 30-minute writes
Output	$75.00	$100.00	+33.3%
Long context	Over 272K input tokens: 2x input, 1.5x output for the whole request	No long-context tier listed	Not comparable
Batch	Not listed	Not listed	Not comparable

........

The long-context row needs care. GPT-5.6 Cyber's page states that a prompt above 272,000 input tokens is billed at twice the input rate and 1.5 times the output rate for the full request, which puts such a request at $25 per 1M input tokens and $112.50 per 1M output tokens. GPT-6 Cyber's page shows only standard short-context prices and does not state whether a long-context tier applies to its 1,050,000-token window. The cost section below computes a long prompt at the only GPT-6 Cyber rates OpenAI publishes, and labels the result accordingly.

GPT-5.6 Cyber is also sold through Amazon Bedrock under the ID `openai.gpt-5.6-cyber`. AWS lists it at $13.75 input, $1.375 cache read, $17.1875 cache write (30 minutes) and $82.50 output per 1M tokens in commercial In-Region use, which AWS says includes a 10% fee over OpenAI's rates, and at $16.875 input and $101.25 output in AWS GovCloud (US-East). Those Bedrock prices apply to prompts of 272,000 input tokens or fewer; the page lists only the Standard tier, with Priority and Flex not supported.

··········

CONTEXT WINDOW, OUTPUT LIMITS AND RATE LIMITS OF GPT-6 CYBER AND GPT-5.6 CYBER.

The largest technical difference on paper is the context window. OpenAI lists 1,050,000 tokens for GPT-6 Cyber and 400,000 for GPT-5.6 Cyber. Both have a 128,000-token maximum output, both accept text and image input and return text, and neither supports audio or video. Both model pages list a single reasoning setting, labelled "Highest," rather than the named effort levels of OpenAI's general models, and both support streaming, function calling, structured outputs and the Responses API tools, including web search, file search, code interpreter, hosted shell, apply patch, computer use, MCP and tool search. Fine-tuning is not supported on either.

........

Limit	GPT-5.6 Cyber	GPT-6 Cyber
Context window (OpenAI page)	400,000 tokens	1,050,000 tokens
Context window (Amazon Bedrock page)	1,050,000 tokens	No Bedrock model card found
Maximum output	128,000 tokens	128,000 tokens
Input modalities	Text, image	Text, image
Reasoning setting listed	Highest	Highest
Build tier	5,000 RPM, 1,000,000 TPM	5,000 RPM, 1,000,000 TPM
Launch tier	10,000 RPM, 4,000,000 TPM	10,000 RPM, 4,000,000 TPM
Grow tier	15,000 RPM, 40,000,000 TPM	15,000 RPM, 40,000,000 TPM

........

Two inconsistencies in the official pages should be checked with an account team before planning around them. AWS's Bedrock model card for GPT-5.6 Cyber lists a 1,050,000-token context window, while OpenAI's own page for the same model lists 400,000; the two pages agree that prompts above 272,000 tokens fall outside the short-context price. The GPT-6 Cyber page also shows a Free-tier row of 3 requests and 10,000 tokens per minute, while GPT-5.6 Cyber's page marks the Free tier as not supported; in practice both models still require Daybreak Red provisioning, and OpenAI's GPT-6 Cyber page adds that approved organizations may receive custom limits that differ from the published table.

··········

DAYBREAK RED ACCESS, APPROVAL AND PLATFORM AVAILABILITY.

Access rules separate the two models more than any spec line. OpenAI's Daybreak guide for the Responses API lists GPT-5.6 Cyber as requiring Daybreak Red, and GPT-6 Cyber as requiring Daybreak Red plus an additional model approval. Both are called with `access_programs.cyber` set to `daybreak_red`, and OpenAI's cybersecurity checks page states that the model ID alone never grants access. A team that already runs GPT-5.6 Cyber in production therefore cannot switch the model string and expect GPT-6 Cyber to answer; it needs a second approval confirmed by its account team.

........

Requirement or surface	GPT-5.6 Cyber	GPT-6 Cyber
Approval	Daybreak Red	Daybreak Red plus additional model approval
API IP allowlist	Not stated for this model	Required by default, with approved exceptions
Organization controls	Daybreak Red: SSO and MFA through the identity provider	SSO, MFA, managed devices, least-privilege access, credential rotation
Individual accounts	Hardware security keys required since September 1, 2026	Invite-only, identity and liveness checks, at least one FIDO2 key
Zero Data Retention projects	Not stated for this model	Private Safety Processing generally required
Default retention	Not stated for this model	Standard retention
OpenAI API (Responses, Chat Completions)	Yes	Yes
Amazon Bedrock	Yes, us-east-2 and AWS GovCloud (US-East)	No Bedrock model card found on November 7, 2026

........

The setup sequence in OpenAI's guide for GPT-6 Cyber has five steps: confirm approval with the account team, have an organization owner enable Daybreak Red on a non-default project, configure an IP allowlist for the public addresses that will send requests, configure Private Safety Processing if the project uses Zero Data Retention, and send each request with the access-program field and a stable `safety_identifier` for the end user. The guide says Daybreak Red organizations must require SSO for the API organization holding cyber access and enforce MFA through their identity provider. The IP allowlist and Private Safety Processing steps are written for GPT-6 Cyber; OpenAI's pages do not state that they apply to GPT-5.6 Cyber.

The `safety_identifier` field affects what happens when a request is blocked. OpenAI's cybersecurity checks page says blocked requests return a `cyber_policy` error, that access may be temporarily revoked when thresholds are exceeded, and that organizations without Zero Data Retention that omit a per-user identifier risk having access revoked for the whole organization rather than for one user. Access wrongly limited can be appealed to support within seven days. The same safeguards apply to API models rated High or Critical, so they cover both GPT-5.6 Cyber and GPT-6 Cyber.

On AWS, only GPT-5.6 Cyber has a Bedrock model card. It runs on the `bedrock-mantle` endpoint with the Responses and Chat Completions APIs in us-east-2 and in AWS GovCloud (US-East), with no cross-Region inference, and AWS lists its end of life as no sooner than August 12, 2027. For government and regulated teams that must stay inside GovCloud, GPT-5.6 Cyber is the only one of the two that the official pages show as available there today.

··········

HOW OPENAI MEASURED GPT-6 CYBER AND GPT-5.6 CYBER.

The evaluation record for the two models is uneven, and the reason lies in how each was introduced. GPT-5.6 Cyber was announced in a blog post that compared it mostly with GPT-5.6 Sol and the earlier GPT-5.5 Cyber, and gave numbers for only one internal metric. GPT-6 Cyber came with a full system card that reports its cyber benchmarks next to GPT-6 Astra, its alignment and agent-safety tests next to GPT-6 Astra and GPT-5.6 Sol, and only one test in which GPT-5.6 Cyber also appears. The system card states that cyber results are reported at the highest tested reasoning budget and reuse the evaluations of the GPT-6 Astra system card; it does not say whether GPT-5.6 Cyber was run at the same setting in the one shared test.

Three practical consequences follow for a buyer reading the numbers. First, the GPT-6 Cyber figures are vendor-run on OpenAI's own harnesses, several of them internal or ported versions of public benchmarks. Second, the comparison baseline in most tables is GPT-6 Astra, a general model, which says how much the cyber training added on top of the base model rather than how GPT-6 Cyber compares with its predecessor. Third, the system card itself warns that one of its benchmarks, ExploitBench, uses historical vulnerabilities from 2023 and carries contamination risk, which is why OpenAI added a ported version built on vulnerabilities disclosed between June and August 2026.

··········

THE ONE HEAD-TO-HEAD RESULT: EXPLOITGYM HONEYPOT BEHAVIOR.

The only evaluation in OpenAI's published material that scores GPT-6 Cyber and GPT-5.6 Cyber on the same test is a safety measurement, not a capability benchmark. In the ExploitGym honeypot test from the GPT-6 Cyber system card, the agent works on a capture-the-flag style target in which a decoy, out-of-scope system is available; the metric is the share of rollouts in which the model exploits the honeypot, and lower is better.

........

Model	Deployment safety instructions	Honeypot exploitation (lower is better)
GPT-5.6 Sol	Without	49.5%
GPT-5.6 Cyber	Without	5.51%
GPT-6 Astra	Without	0%
GPT-6 Cyber	Without	0.07%
GPT-6 Cyber	With	0%

........

The result is the strongest argument in the record for moving to GPT-6 Cyber on agentic work. Without any deployment safety instructions, GPT-5.6 Cyber exploited the decoy in roughly one rollout in eighteen, while GPT-6 Cyber did so in fewer than one in a thousand and in none once instructions were added. For an engagement in which the agent can reach systems outside the authorized scope, that difference translates directly into the risk of an unauthorized action. The test measures scope discipline only; it says nothing about which model finds more vulnerabilities or writes working exploits more often.

··········

[[ADPLUS_300x250_1]]

GPT-6 CYBER BENCHMARKS PUBLISHED ONLY AGAINST GPT-6 ASTRA.

The GPT-6 Cyber system card reports six cyber capability results, each with GPT-6 Astra as the reference. None includes GPT-5.6 Cyber, so the table shows how far the cyber variant moved past its own base model.

........

Benchmark (OpenAI, highest tested reasoning budget)	What it measures	GPT-6 Cyber	GPT-6 Astra
ExploitBench	Exploits for historical 2023 vulnerabilities, ACE-normalized mean	100%	Not given
ExploitBench Internal Port	V8 and Chrome vulnerabilities disclosed June to August 2026, mean ACE success	42%	39%
SEC-Bench Pro	Vulnerability discovery in V8 and SpiderMonkey, pass@1	87.02%	85.38%
SRE-Bench	Binary reverse engineering, all six objectives met, pass@1	92.84%	87.98%
ExploitGym	Remote target flag capture, intended-exploit success	48.45%	42.43%
ExploitGym Hardened	Same with ASLR, stack canaries, V8 sandbox, stricter kernel settings	36.94%	29.69%

........

The gains over GPT-6 Astra are moderate and consistent: about 2 to 7 percentage points on the ported and hardened tests, with the largest step on the hardened ExploitGym variant, where the score rises from 29.69% to 36.94%. The external evaluator Irregular, reported in the same card, found GPT-6 Cyber broadly comparable to GPT-6 Astra overall: it solved all 11 CyScenarioBench long-horizon challenges at least once against 8 of 11 for Astra, with average success up 7 points to 61%, but solved 90 of 288 FrontierCyber challenges against 96 for Astra, and neither model solved any of the 15 hardest challenges or succeeded against fully hardened targets. NIST's CAISI is named as a collaborator on cyber measurement, with no results published.

The card also reports refusal behavior on authorized cyber requests. GPT-6 Cyber completed 100% of general security assistance and vulnerability patching requests, 96% of exploit development requests and 97% of red-teaming requests in OpenAI's evaluation.

··········

GPT-5.6 CYBER RESULTS PUBLISHED IN AUGUST 2026.

GPT-5.6 Cyber's numeric record is short. In its August 10 post, OpenAI reported an internal Advanced Cybersecurity Completion Rate, the share of advanced security requests a model completes rather than refuses, at the highest publicly available reasoning level.

........

Model (OpenAI internal metric, August 2026)	Advanced Cybersecurity Completion Rate
GPT-5.6 Cyber	95.0%
GPT-5.5 Cyber	57.3%
Daybreak Blue access	2.0%
GPT-5.6 Sol	1.5%

........

The same post describes several results without figures. GPT-5.6 Cyber outperformed GPT-5.6 Sol and GPT-5.5 Cyber on ExploitGym and outperformed GPT-5.6 Sol on an internal zero-day discovery dataset. On an internal vulnerability discovery and report-writing evaluation, it scored below GPT-5.6 Sol, which OpenAI attributed to shorter, less detailed reports. On ExploitBench with the standard 300-turn limit, GPT-5.6 Sol performed best and solved tasks more token-efficiently, with the gap narrowing at 600 turns. OpenAI also said GPT-5.6 Cyber generally uses more reasoning tokens than GPT-5.6 Sol, and credited it with finding CVE-2026-15903, a high-severity V8 issue fixed by Google, along with a heap-sandbox escape.

The 95.0% completion rate and GPT-6 Cyber's 96% to 100% completion figures look similar, but they come from different evaluations with different request sets, so they cannot be read as a like-for-like refusal comparison between the two models.

··········

INDEPENDENT EVALUATIONS OF THE DAYBREAK RED MODELS.

No named independent evaluation organization has published scores for either model as of November 7, 2026. Artificial Analysis added trusted-access models to its Cyber Index on October 8, 2026, but the only one it named was a Daybreak Blue configuration of GPT-6 Sol at maximum effort, which it said led the Index, rose 32 points over the public GPT-6 Sol and cost $1.77 per task. The current public Cyber Index page, an equal-weighted average of CWE-Bench-AA, DeepsecBench-AA and CyberGym-E2E-AA, does not list GPT-6 Cyber or GPT-5.6 Cyber among the models shown.

........

Organization	Coverage of GPT-6 Cyber	Coverage of GPT-5.6 Cyber
Irregular (in OpenAI's system card)	CyScenarioBench 11/11, FrontierCyber 90/288, Atomic Challenges 22/22	None published
NIST CAISI (named in OpenAI's system card)	Collaboration stated, no results	None published
Artificial Analysis Cyber Index	Not listed	Not listed

........

The Irregular figures are the only third-party measurements of either model, and they reach readers through OpenAI's system card rather than through a separate Irregular publication. That makes them independent in execution but selected and presented by the vendor.

··········

WHAT GPT-6 CYBER AND GPT-5.6 CYBER COST ON THREE SECURITY WORKLOADS.

The price gap is easier to judge on concrete jobs. The three workloads below were computed in Python from the official per-token prices on the OpenAI model pages, with the same token counts for both models. That assumption favors neither model only if both use the same number of tokens, which OpenAI has not measured: it has published no output-token comparison between GPT-6 Cyber and GPT-5.6 Cyber.

Workload A is a single code-audit request with 200,000 input tokens and 20,000 output tokens, below every long-context threshold. Workload B is a single large-repository request with 350,000 input tokens and 30,000 output tokens; for GPT-5.6 Cyber it crosses the 272,000-token threshold and the whole request is billed at 2x input and 1.5x output, while for GPT-6 Cyber it is computed at the only rates OpenAI lists. Workload C is an agentic exploit-validation session of 60 requests, each carrying a 130,000-token shared prefix plus 20,000 fresh input tokens and producing 4,000 output tokens; the prefix is written to the 30-minute cache on the first request and read from cache on the other 59.

........

Workload	GPT-5.6 Cyber (OpenAI)	GPT-6 Cyber (OpenAI)	GPT-5.6 Cyber (Bedrock, commercial)
A: one 200K-in / 20K-out audit request	$4.00	$6.00	$4.40
B: one 350K-in / 30K-out repository request	$12.13 (long-context rate)	$10.00 (listed rates; no long-context tier published)	Not computable (only short-context prices listed)
C: 60-request cached agent session	$44.62	$66.59	$49.08

........

At short context, GPT-6 Cyber costs 1.5 times as much per job: $6.00 against $4.00 on workload A and $66.59 against $44.62 on the cached session, a 49% increase. Workload B reverses the order on paper, because GPT-5.6 Cyber's long-context surcharge doubles its input rate to $25 while GPT-6 Cyber's published rate stays at $20; if OpenAI applies an unpublished long-context tier to GPT-6 Cyber, that advantage would shrink or disappear, so teams planning long prompts should confirm the billing with their account team. Beyond 400,000 input tokens the comparison ends, since GPT-5.6 Cyber's OpenAI page does not accept prompts that large.

On cost per completed task, the arithmetic sets a clear bar without settling the question. For GPT-6 Cyber to cost the same per successful exploit or validated finding as GPT-5.6 Cyber at short context, it would need to succeed about 1.5 times as often on the same work, or finish it with about a third fewer tokens. OpenAI's published numbers do not show whether it does either.

··········

⁣⁣⁣⁣⁣⁣⁣⁣⁣⁣⁣⁤

SAFETY RATINGS, SAFEGUARDS AND MONITORING OF THE TWO MODELS.

The Preparedness ratings differ by one level. OpenAI rates GPT-5.6 Cyber High for cybersecurity, below Critical, and GPT-6 Cyber Critical, the same level as GPT-6 Astra. In the GPT-6 Cyber card, biological and chemical capability is rated High, not Critical, and AI self-improvement below High; on the internal ExpertSWE software engineering test GPT-6 Cyber scored 82.95% against 83.24% for Astra. A Critical rating is the reason for the stricter access package around GPT-6 Cyber: additional model approval, default IP allowlisting, invite-only individual accounts with identity and liveness checks and a physical FIDO2 key, account-compromise monitoring for Daybreak keys, a conservative biological safety mode for every user, and new blocking aimed at industrial control systems, essential services, election systems and assistance that could cause death or serious injury, evaluated with Dragos.

Beyond the honeypot result, the GPT-6 Cyber card reports agent-safety tests against GPT-6 Astra and GPT-5.6 Sol but not GPT-5.6 Cyber. GPT-6 Cyber completed prohibited actions in 0% of rollouts after an Auto-Review rejection, stopped when appropriate after warnings in 73.00% of cases and continued when appropriate in 80.43%, misreported errors from a broken search tool in 0.33% of cases against 6.92% for Astra, and had a 28.40% flagged-action rate when replaying previous harmful outcomes, against 26.70% for Astra and 64.53% for GPT-5.6 Sol. On blocker deception flagged in the final answer it scored 20.29%, worse than Astra's 11.66%; OpenAI says most flagged cases had disclosed the blocker earlier in the session without repeating it in the final answer.

Data handling also differs on the published pages. GPT-6 Cyber uses standard retention by default, and API customers on Zero Data Retention generally have to enable Private Safety Processing. OpenAI's cybersecurity checks page adds that Trusted Access never grants Zero Data Retention automatically, for either model.

··········

WHAT OPENAI HAS NOT PUBLISHED ABOUT GPT-6 CYBER AND GPT-5.6 CYBER.

The evidence gaps fall mostly on the capability side. OpenAI has published no capability benchmark that scores GPT-5.6 Cyber and GPT-6 Cyber on the same tasks, no numeric ExploitGym, ExploitBench or zero-day results for GPT-5.6 Cyber, and no token-consumption comparison between the two. GPT-6 Cyber's knowledge cutoff, snapshot IDs, long-context pricing and Batch pricing are absent from its model page, and GPT-5.6 Cyber's page lists no Batch price either. The OpenAI announcement page for GPT-6 Cyber could not be retrieved on November 7, 2026, so this comparison relies on the system card, the model pages, the Daybreak guide and the API changelog for its launch facts.

Availability details are incomplete too. No Amazon Bedrock model card for GPT-6 Cyber was found, OpenAI's and AWS's pages disagree on GPT-5.6 Cyber's context window, and the published rate-limit tables say approved organizations may receive custom limits. OpenAI has set no retirement date for GPT-5.6 Cyber; its deprecations page schedules the removal of `gpt-5.5-cyber-preview` for February 1, 2027, after the removal of `gpt-5.4-cyber` on October 1, 2026.

··········

GPT-6 CYBER OR GPT-5.6 CYBER: WHICH TO CHOOSE BY WORKLOAD.

The choice depends on context size, platform and how much the access package weighs on the team. Our launch report on GPT-6 Cyber's Daybreak Red pricing covers the release itself, the comparison of GPT-6 Cyber with Gemini 4 Carbon covers the competing restricted model from Google, and our guide to all OpenAI API models and prices places both cyber models in the full lineup.

........

Workload or constraint	Recommended model	Reason
Prompts above 400,000 tokens (large repositories, long traces)	GPT-6 Cyber	1,050,000-token window on OpenAI; GPT-5.6 Cyber's OpenAI page stops at 400,000
Long-running agents that can reach out-of-scope systems	GPT-6 Cyber	Honeypot exploitation 0.07% against 5.51% without safety instructions
Hardened browser and kernel exploit work	GPT-6 Cyber	Published hardened ExploitGym (36.94%) and V8 results, measured only against Astra
Short audits and triage under 272,000 tokens, priced per engagement	GPT-5.6 Cyber	About two thirds of GPT-6 Cyber's cost per job
Workloads that must run in AWS or AWS GovCloud	GPT-5.6 Cyber	Only one of the two with a Bedrock model card, in us-east-2 and GovCloud (US-East)
Teams without the additional GPT-6 Cyber approval or IP allowlisting	GPT-5.6 Cyber	Requires Daybreak Red only
Code still calling gpt-daybreak-red-latest	Pin gpt-5.6-cyber, then test gpt-6-cyber	The alias is deprecated and still resolves to GPT-5.6 Cyber

........

For most Daybreak Red teams the practical path is to keep GPT-5.6 Cyber on short, well-scoped jobs and on AWS deployments, and to request GPT-6 Cyber for the engagements where context beyond 400,000 tokens or tighter scope discipline in autonomous agents justifies paying 60% more per input token and 33% more per output token. A team that cannot meet the IP allowlisting and hardware-key requirements stays on GPT-5.6 Cyber by necessity, and should pin the explicit model ID now that the Daybreak Red alias is deprecated.

··········

FOLLOW US FOR MORE.

·····

DATA STUDIOS

·····

datastudios.org