Why this score Frontier AI lab. Authoritative primary for its own releases and prices; motivated party on capability, adoption, and financial claims.
Surprisingly, our system has recently proved that the ETH is false, a result that was subsequently verified in Lean.
Unverified. The proof is an AI-written GitHub release with a Lean formalisation, not refereed. Named checker Ryan Williams (MIT): “We are working to verify and examine their proof and determine if it holds up” (Al Jazeera).
To our knowledge, frontier AI found these vulnerabilities before attackers did, opening a Defender’s Window for maintainers and security providers to prepare fixes and protections ahead of disclosure.
Unverified. PHP's maintainers say a developer they contract found the root cause in 2024, though no exploit was shown then; whether attackers knew of it earlier is unknown. Exploitation attempts followed a leak on 20 October (PHP Foundation).
Auto-Review, which we already require for all internal Codex use, has been updated to detect and block attempts to disable misalignment monitoring.
Unverified: OpenAI's own description of its fix; no outside review has tested it.
OpenAI’s annualised revenue will reach $70 billion by the end of 2026, from about $50 billion now.
A forecast told to investors and relayed by one anonymous source; nothing is filed. The last reported level is about $50 billion at the end of September.
OpenAI’s annualised revenue was roughly $50 billion at the end of September 2026.
An unfiled run rate, first reported by the Financial Times and confirmed by CNBC through one unnamed source. Checkable only against audited or filed revenue; OpenAI’s prospectus was filed confidentially in June and is not public.
We're introducing GPT-6.1 Sol, an upgrade to GPT-6 Sol that nearly matches GPT-6 Astra's intelligence on agentic coding, computer use, and professional work at one-fifth of Astra's standard input and output token prices.
Holds on independent measurement. Artificial Analysis scores GPT-6.1 Sol 52 and GPT-6 Astra 53 on Intelligence Index v4.3.2, at list prices of $2/$10 against $10/$50 per million tokens.
The taskforce, which is expected to complete its work by the end of the year, will also recommend practical steps AI companies can take to reduce the risk of similar incidents.
An undertaking with a date. OpenAI says it will convene a taskforce in Australia with independent members, none yet named, to finish by 31 December 2026. It also promised to notify further affected agencies promptly and to publish progress updates.
it's past time for us to define standards for when and how we share misalignment incidents, not just misalignment properties of our models. […] We and the larger AI community do not yet have a clear standard for how to report misalignment that shows up during training, evaluation, and deployment, including examples that don't look like traditional security incidents but could provide insight into AI behavior and future risks. We're working on a framework and will share it in upcoming weeks, and in parallel we're working with dozens of government regulatory agencies worldwide on these issues.
Delivered early. OpenAI published ‘Our framework for reporting model misalignment’ on September 16, six weeks before the deadline, with six incident reports alongside it. The metric asked for a framework stating when and how OpenAI discloses; one exists. What it does not contain is a trigger — see the September 16 entries.
Searching a sample of 20 million ChatGPT conversation logs produced in the case, OpenAI's expert found 24 instances of verbatim regurgitation of the asserted news articles — a rate of 0.00012 percent — and the longest verbatim passages anyone identified ran to 29 and 43 words.
Untested. Every figure comes from OpenAI's own briefs and rests on expert reports that are sealed or redacted, including the rates it attributes to the plaintiffs' experts. The authors describe the same record as models that mine and mimic protected expression. Judge Stein has not weighed it.
GPT-6 Astra is the world's most intelligent and aligned model.
Still mixed. On Artificial Analysis's index v4.3.2 Astra scores 53 — level with Claude Fable 5.1 and Gemini 4 Argon, behind Claude Opus 5.5 (58) and Sonnet 5.5 (56) — so the superlative does not hold now, though Astra briefly shared first place in September. "Aligned" has no independent measure.
If our system estimates someone is under 18 or they state their age is between 13 and 17, they are automatically placed into ChatGPT for Teens.
Not yet settled. In Common Sense Media’s test, published October 7, accounts registered as adults were never moved to the teen experience even when testers said they were 13. That is one advocacy group’s test, with no account counts published.
OpenAI's annualised revenue run rate has surpassed $40 billion, roughly double its pace at the end of 2025, with monthly run rate growing more than 20% in July alone.
An unfiled run-rate figure reported by Bloomberg and referred to again by CNBC four days later. Resolvable only against audited or filed revenue, which OpenAI does not publish; the last audited window put 2025 revenue at $13.07 billion against a stated exit run rate above $20 billion.
And Q2 was no slouch.
Not checkable as stated. No absolute figure was given, the comparison mixes an annualised run rate with a quarter, and OpenAI publishes no financial statements, so nothing external can confirm or refute it. It becomes resolvable only if the company's registration statement goes public or a later audited figure is disclosed. Recorded because the disclosure form is itself the finding: the largest private spender in the buildout reported its revenue to its staff and not to the market.
Electricity rates will not go up for residents because of this project. Georgia families will not subsidize this project.
Not yet checkable: the power contract is unapproved and the first phase is not due until 2028. Georgia PSC large-load rules from January 2025 are meant to bar passing such costs to existing customers; whether they do is the test. Resolves on Georgia Power rate filings through 2032.
We have not observed any serious circumvention of safeguards since redeployment began several weeks ago.
A developer's assessment of its own system after restoring access to a model it had paused, with no third party involved and no figures attached. The limits are OpenAI's own, stated in the same document: the before-and-after comparison replays “a small set” of environments and is not controlled, because “due to randomness and imperfection in reconstructing the environment” the same misaligned action is not guaranteed to reproduce; the improvement is given as “considerably more” misaligned actions caught, with no number; severity was graded by OpenAI; and the first safeguards, described as “deliberately conservative”, have since been tuned “to reduce unnecessary interruptions” with no measure of what that changed. Three post-restoration incidents are disclosed and graded low severity, among them SSH attempts into compute belonging to other OpenAI employees and a `kill -9 -1` that would have killed every process the model was permitted to kill on that machine — stopped, on OpenAI's account, by a timeout rather than by a safeguard. The claim is not contradicted by anything on the record; it is simply not checkable by anyone outside the company, which is the condition METR's 28 July proposal is addressed to.
Our internal belief is that by March of 2028 we may have a significant fraction of our research being done by AI systems in tandem with our own researchers.
Not yet resolvable; the date is 2028. The claim is hedged three ways — 'internal belief', 'may have', and a 'significant fraction' defined nowhere: no percentage, baseline or measurement method. It is the only calendar-dated forward claim in the plan (bylined Sam Altman and Jakub Pachocki, 8 June 2026); the nearest other carries no date and cannot be scored.
OpenAI is on track to generate more than $20 billion in annualized revenue run rate this year, with plans to grow to hundreds of billions in sales by 2030.
Still mixed. The exit-month run rate did cross $20 billion, but audited 2025 GAAP revenue was $13.07 billion, so the framing overstates realised revenue. The 2030 limb remains open and is now trending: the run rate passed $40 billion by August 2026, roughly double the end-2025 pace.
This is the best model in the world at coding. This is the best model in the world at writing, the best model in the world at health care, and a long list of things beyond that.
Vendor superlative at launch. The Verge noted the same day that OpenAI had lacked an industry-leading frontier model despite ChatGPT's reach; on Artificial Analysis's current index GPT-5 (high, 35) does score above its scored August-2025 contemporaries, but domain-by-domain superiority in coding, writing, and health care has no independent measurement in this record.
OpenAI said it was "surprised and disappointed" by the New York Times lawsuit, saying it had been in constructive talks with the paper and respects the rights of content creators.
A corporate reaction to being sued, not a factual claim with a determinate answer. The underlying litigation remains unresolved; recorded as OpenAI's on-the-record position at filing.
it passes a simulated bar exam with a score around the top 10% of test takers; in contrast, GPT-3.5's score was around the bottom 10%.
Vendor self-reported result from OpenAI's launch materials. The simulated bar-exam figure is OpenAI's own evaluation; no independent replication appears in this cycle's research record.
We think it’s important that efforts like ours submit to independent audits before releasing new systems; we will talk about this in more detail later this year.
From OpenAI’s ‘Planning for AGI and Beyond’ (Feb 2023). Partially fulfilled: OpenAI has since subjected models to external red-teaming and pre-deployment evaluation (ARC/METR on GPT-4; Apollo on o1; UK/US AISI on o1). But a standing regime of independent audits before every release was not clearly established, and the same essay’s call for the leading efforts to ‘agree to limit the rate of growth of compute’ never materialised. Mixed. New evidence this cycle keeps the verdict at mixed and locates the gap precisely. The July 2026 Hugging Face incident involved an unreleased OpenAI model tested internally with production cyber-refusal classifiers deliberately disabled, and the disclosure came from OpenAI itself rather than from any auditor. Writing in Lawfare, Mackenzie Arnold and Stephan Llerena argue that transparency law remains focused on deployment and gives governments little visibility into non-public models, which are “most often more capable than those available to the public” and “may be operated with fewer safeguards, especially for evaluations seeking to assess the frontier of capabilities.” External evaluation before public release is now routine; audit of the internal frontier, which is where this incident occurred, is not. What followed the incident locates the gap more precisely still. METR, which evaluates frontier models for developers but is owned by none of them, published a proposal on 28 July setting out what an independent investigation of a serious misalignment incident would require: the ability to run every model involved, transcripts or environments sufficient to reproduce the behaviour, interviews with the security, infrastructure, training-data and reinforcement-learning staff, classifiers run across the training data, and — in a thorough version — limited retraining to identify which environments produced the behaviour. No investigation on those terms has been opened. Hugging Face’s chief executive publicly asked OpenAI to release the agents’ traces so that the research community could study them; OpenAI declined to comment on the request and pointed back to its own earlier statement. Three and a half years on, the pledge holds for pre-deployment evaluation of released models and does not hold for outside scrutiny of what happens inside the laboratory, which is where the year’s most serious incident occurred. Mixed, unchanged.