AI Safety

What AI providers state their models reached in safety testing, in their own words, and what outside testers found.

Also: compare models side by side · statements that a capability level was crossed · providers · practices providers document · safety news.

What providers state

Each row is one statement in a provider's own safety document about a capability level of one of its models: the level as the provider names it, whether the provider says the model reached it, and the sentence that says so.

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Model	Level, as the provider names it	The provider states	The provider's sentence
Muse Spark 1.1 Meta	Moderate or lower Misuse and jailbreaks	Not reached	“Therefore, we conclude that we have addressed these risks from unmitigated Muse Spark 1.1, which bring the residual risk to the “moderate or lower” risk threshold under our Advanced AI Scaling Framework.” source
Muse Spark Meta	Moderate or lower Autonomy and AI research	Not reached	“We assess loss of control risk as “moderate or lower”.” source
Muse Spark Meta	High Chemical, biological, radiological, nuclear	Not determined	“Those evaluations identified elevated risks prior to mitigations, with Chemical and Biological capabilities assessed as likely reaching the “high risk” category under the Advanced AI Scaling Framework before safeguards were applied.” source
Muse Spark Meta	Moderate or lower Chemical, biological, radiological, nuclear	Not reached	“However, after applying mitigations, the residual risk of the model is that of “moderate or lower risk.”” source
Muse Spark Meta	Below the level required to meaningfully enable the cyber threat scenarios defin Cyber	Not reached	“Muse Spark’s offensive cyber capabilities remain below the level required to meaningfully enable the cyber threat scenarios defined in the Advanced AI Scaling Framework.” source
Muse Spark Meta	Moderate or lower Cyber	Not reached	“We assess cybersecurity risk as “moderate or lower” with respect to the threat scenarios outlined in Meta’s Advanced AI Scaling Framework.” source
Gemini 4 Argon Google DeepMind	TCL (Tracked Capability Level) Autonomy and AI research	Not determined	“In light of this, we assess that we cannot rule out the TCL.” source
Gemini 4 Argon Google DeepMind	TCL (Tracked Capability Level) Chemical, biological, radiological, nuclear	Not reached	“We can rule out the TCL for the chemical, radiological, and nuclear domains with reasonable confidence.” source
Gemini 4 Argon Google DeepMind	CCL (Critical Capability Level) Deception and sabotage	Not reached	“we assess its overall capabilities to be below the CCL threshold.” source
Gemini 4 Argon Google DeepMind	CCL (Critical Capability Level) Misuse and jailbreaks	Not reached	“Gemini 4 Argon demonstrates some ability to influence user beliefs and behaviors during one-on-one direct conversations in human behavioral studies, and may provide utility in the planning stage of a malicious influence operation but we assess its overall capabilities to be below the CCL threshold.” source
Gemini 4 Argon Google DeepMind	CCL (Critical Capability Level) Other	Not reached	“Gemini 4 Argon's performance remains below our CCL threshold.” source
Gemini 3.7 Flash Google DeepMind	CCL (Critical Capability Level) Autonomy and AI research	Not reached	“The model does not reach the CCL alert threshold.” source
Gemini 3.7 Flash Google DeepMind	CCL (Critical Capability Level) Chemical, biological, radiological, nuclear	Not reached	“We can rule out the CCL for the CBRN domain with reasonable conﬁdence based on the results from our testing.” source
Gemini 3.7 Flash Google DeepMind	TCL (Tracked Capability Level) Chemical, biological, radiological, nuclear	Not reached	“We can rule out the TCL for the CBRN domain with reasonable conﬁdence based on the results from our testing.” source
Gemini 3.7 Flash Google DeepMind	CCL (Critical Capability Level) Cyber	Not reached	“Gemini 3.7 Flash reaches the alert threshold for this CCL, but not the CCL.” source
Gemini 3.7 Flash Google DeepMind	TCL (Tracked Capability Level) Deception and sabotage	Not reached	“The model does not reach the TCL.” source
Gemini 3.5 Transcribe Live Google DeepMind	CCL (Critical Capability Level) Other	Not determined	“Our assessments have shown that none of Gemini 3.5 Translate, Gemini 3.5 Transcribe, or Gemini 3.5 Transcribe Live have meaningful new T/CCL-relevant capabilities or material increases in performance with respect to Frontier Safety compared to Gemini 3.1 Pro and Gemini 3.7 Flash, therefore we are conﬁdent that none of them are likely to reach any CCLs.” source
Gemini 3.5 Transcribe Google DeepMind	CCL (Critical Capability Level) Other	Not determined	“Our assessments have shown that none of Gemini 3.5 Translate, Gemini 3.5 Transcribe, or Gemini 3.5 Transcribe Live have meaningful new T/CCL-relevant capabilities or material increases in performance with respect to Frontier Safety compared to Gemini 3.1 Pro and Gemini 3.7 Flash, therefore we are conﬁdent that none of them are likely to reach any CCLs.” source
Gemini 3.5 Flash-Lite Google DeepMind	CCL (Critical Capability Level) Other	Not determined	“Our assessments have shown that, while Gemini 3.5 Flash-Lite excels at agents and coding, it does not have meaningful new capabilities or material increases in performance with respect to the domains outlined in our Frontier Safety Framework compared to Gemini 3.1 Pro; therefore, based on Gemini 3.1 Pro results, we are confident that Gemini 3.5 Flash-Lite is also unlikely to reach any CCLs.” source
Gemini 3.5 Audio Google DeepMind	Tracked or critical capability level (t/ccls) Other	Not reached	“they did not reach any Tracked or Critical Capability Levels (T/CCLs) outlined in our Frontier Safety Framework .” source
Gemini 3.1 Pro Google DeepMind	Uplift level 1 Chemical, biological, radiological, nuclear	Not reached	“We found that the model remains below alert thresholds for the CBRN, harmful manipulation, machine learning R&D, and misalignment CCLs.” source
Gemini 3.1 Pro Google DeepMind	Uplift level 1 Cyber	Not reached	“As previous models passed the alert threshold for cyber, we performed more additional testing in this domain on Gemini 3.1 Pro with and without Deep Think mode, and found that the model remains below the cyber CCL.” source
Gemini 3.1 Flash-Lite Google DeepMind	CCL (Critical Capability Level) Other	Not determined	“Our assessments have shown that Gemini 3.1 Flash-Lite is less capable than Gemini 3.1 Pro, therefore based on Gemini 3.1 Pro, we are confident that Gemini 3.1 Flash-Lite is also unlikely to reach any CCLs.” source
Gemini 3.1 Flash Audio Google DeepMind	CCL (Critical Capability Level) Other	Not determined	“Our assessments have shown that Gemini 3.1 Flash Audio is less capable than Gemini 3.1 Pro.” source
Gemini 2.5 Pro Google DeepMind	Machine Learning R&D Uplift Level 1 Autonomy and AI research	Not determined	“given Gemini 2.5 Pro Preview's poor median performance on RE-Bench relative to experts, the model likely lacks the necessary capabilities to automate or signiﬁcantly uplift any signiﬁcant fraction of the research process.” source
Gemini 2.5 Pro Google DeepMind	Instrumental Reasoning Level 1 Deception and sabotage	Not reached	“Instru- mental Reasoning Level 1 ✘ CCL not reached” source
Gemini 2.5 Pro Google DeepMind	Instrumental Reasoning Level 2 Deception and sabotage	Not reached	“Instru- mental Reasoning Level 2 ✘ CCL not reached” source
Gemini 2.5 Deep Think Google DeepMind	Uplift level 1 Chemical, biological, radiological, nuclear	Not determined	“Our assessment is that the model has enough technical knowledge in certain CBRN scenarios and stages to be considered at early warning.” source
Gemini 2.5 Deep Think Google DeepMind	Cyber Uplift Level 1 Cyber	Not determined	“CCL reached? No, but the early warning alert threshold was originally reached by Gemini 2.5 Pro and continues to be met by Gemini 2.5 Deep Think.” source
Gemini 2.5 Deep Think Google DeepMind	Uplift level 1 Cyber	Not determined	“For Cyber Uplift Level 1 , the early warning alert threshold was originally reached by Gemini 2.5 Pro and continues to be met by Gemini 2.5 Deep Think.” source
GPT-5.5 Instant OpenAI	Below high capability Autonomy and AI research	Not reached	“GPT-5.5 Instant is considered below High Capability.” source
GPT-5.5 Instant OpenAI	High Autonomy and AI research	Not reached	“For AI Self-Improvement, evaluations of final checkpoints indicate that, like its predecessor models, GPT-5.5 Instant does not have a plausible chance of reaching a High threshold.” source
GPT-5.5 Instant OpenAI	High Chemical, biological, radiological, nuclear	Reached	“GPT-5.5 Instant is our first Instant model to be treated as High Capability in the Biological and Chemical domain, as well as in the Cybersecurity domain.” source
GPT-5.5 Instant OpenAI	High Cyber	Reached	“this is the first Instant model that we are treating as High capability in our Cybersecurity and Biological & Chemical Preparedness categories, and implementing appropriate safeguards.” source
GPT-5 OpenAI	High Chemical, biological, radiological, nuclear	Reached	“Similarly to ChatGPT agent, we have decided to treat gpt-5-thinking as High capability in the Biological and Chemical domain under our Preparedness Framework, activating the associated safeguards.” source
GPT-5 OpenAI	High cyber risk Cyber	Not reached	“The gpt-5 model series does not meet the threshold for high cyber risk.” source
Claude Sonnet 4.5 Anthropic	AI R&D-4 Autonomy and AI research	Not reached	“All models tested remain below our pre-committed rule-out threshold of 0.6.” source
Claude Sonnet 4.5 Anthropic	ASL-3 Autonomy and AI research	Not determined	“Exhibited improved autonomy capabilities in software engineering and AI research tasks, though still below the ASL-4 rule-out threshold.” source
Claude Sonnet 4.5 Anthropic	ASL-3 Chemical, biological, radiological, nuclear	Not determined	“Remained well below ASL-4 thresholds across all domains of concern;” source
Claude Sonnet 4.5 Anthropic	ASL-4 rule-out Chemical, biological, radiological, nuclear	Not determined	“However, given that this type of logic can have a general frog-boiling effect—where gradual changes mask the crossing of important thresholds—we do not use this evaluation as indicative of a strong ASL-4 rule-out.” source

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What outside testers report

Each row is one result from a government evaluator, independent lab, academic or security firm that tested a model, quoted from where it is reported.

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Model	Tester	Test	What was found
GPT-6 Astra OpenAI	Epoch AI Independent lab · 2026-10-08	Epoch Automation Reports Other	“Of the six models we evaluated, Fable 5.1 and GPT-6 Astra achieve the highest aggregate scores and lead on most individual task categories as well.” source
GPT-6 Astra OpenAI	Epoch AI Independent lab · 2026-10-08	Epoch-style Data Insight writing task Other	“We asked the model to write an Epoch-style Data Insight, a short article on an AI trend.” source
GPT-6 Astra OpenAI	Epoch AI Independent lab · 2026-10-08	research project proposal task based on Epoch’s “9 big questions benchmarks can help answer” Other	“We task models with proposing a research project based on Epoch’s “9 big questions benchmarks can help answer”.” source
GPT-6 Astra OpenAI	Epoch AI Independent lab · 2026-10-08	pilot experiment on hidden-rule puzzle with limited inputs Other	“In the pilot experiment, it tested whether models could figure out the hidden rule behind a simple puzzle by trying a limited number of inputs and seeing their outputs.” source
GPT-6 Astra OpenAI	Epoch AI Independent lab · 2026-10-08	Epoch-style Data Insight writing task Other	“However, GPT-6 Astra chose a topic that is too niche for such an audience:” source
GPT-6 Astra OpenAI	Epoch AI Independent lab · 2026-10-08	Research project proposal based on Epoch's "9 big questions benchmarks can help answer" Other	“However, it’s unclear how this experiment would be executed in practice.” source
GPT-6 Astra OpenAI	Epoch AI Independent lab · 2026-10-08	Pilot experiment on hidden-rule puzzle with limited inputs Other	“The models Astra tested in its experiment could output up to 4096 tokens while choosing the input, which cut off 61 of 280 responses before they could name an input at all.” source
Claude Mythos 5 Anthropic	OWASP GenAI Security Project Standards body · 2026-10-08	Claude Mythos 5 publishes a malicious PyPI package Cyber	“A Claude evaluation agent published a malicious Python package to the real PyPI registry.” source
Claude Fable 5.1 Anthropic	Epoch AI Independent lab · 2026-10-08	Epoch Automation Reports Other	“Although Fable 5.1 and GPT-6 Astra broadly lead, they still fall short of automating our work.” source
Leanstral 1.5 Mistral AI	Academic Academic · 2026-10-07	BehaviorTrace Other	“Across three seeds on Qwen2.5-1.5B, much of the apparent attribution signal comes from confounds.” source
Leanstral 1.5 Mistral AI	Academic Academic · 2026-10-07	gradient-size-only control ranking of training steps Other	“A control that ranks training steps by gradient size alone, with no behavior target, reaches 4.2 to 4.5 times chance and matches or beats the best targeted estimator on two of three seeds.” source
Leanstral 1.5 Mistral AI	Academic Academic · 2026-10-07	fluency-based prediction of behavior label at saturated checkpoints Other	“At saturated checkpoints, model fluency predicts the behavior label at least as well as every gradient method we compared it with.” source
GPT-6 Astra OpenAI	Epoch AI Independent lab · 2026-10-07	InnovationEval Other	“But their successors, Claude Fable 5.1 and GPT-6 Astra, were aware of the task.” source
GPT-6 Astra OpenAI	Epoch AI Independent lab · 2026-10-07	SDPO reimplementation task Other	“Both models failed to fully solve the task, although the cause differed between GPT-6 Astra and Claude Fable 5.1.” source
GPT-6 Astra OpenAI	Epoch AI Independent lab · 2026-10-07	EBR-bench (original version) Other	“GPT-6 Astra scored 100% on the original version of the benchmark.” source
GPT-6 Astra OpenAI	Epoch AI Independent lab · 2026-10-07	EBR-bench under the card ban Other	“Under the card ban, Astra no longer appears capable of fully saturating the benchmark, though its highest score of 20/21 objectives comes very close.” source
GPT-6 Astra OpenAI	Epoch AI Independent lab · 2026-10-07	multi-agent experiments Other	“Astra in particular explores many types of decks even as a single agent, showing that a multi-agent scaffold is not necessary to overcome repetitive play.” source
GPT-5.6 Sol OpenAI	Epoch AI Independent lab · 2026-10-07	InnovationEval Other	“If scope is assessed generously, Sol’s method achieved 35% of SDPO’s gains.” source
GPT-5.6 Sol OpenAI	Epoch AI Independent lab · 2026-10-07	memorization test (prompted to recall or guess details about the paper without using search) Other	“But their successors, Claude Fable 5.1 and GPT-6 Astra, were aware of the task.” source
GPT-5.6 Sol OpenAI	Epoch AI Independent lab · 2026-10-07	submission write-up review for misleading claims Deception and sabotage	“Meanwhile, Sol’s submission did not mention multiple-run selection at all, even though it had noted the issue in its workspace before submission.” source
GPT-5.6 Sol OpenAI	Epoch AI Independent lab · 2026-10-07	SDPO reimplementation task (short-answer questions and coding) Other	“GPT-5.6 Sol used its full 3,000 GPU-hour budget (about $14,000) but only $2,100 in tokens, or 24% of its 10B-token budget.” source
Claude Opus 5 Anthropic	Epoch AI Independent lab · 2026-10-07	multi-agent experiments Other	“Overall, we found a multi-agent setup did improve deck exploration for most of the four models we tested, though the effect was only statistically significant for Claude Opus 5.” source
Claude Haiku 5.5 Anthropic	Dyno Therapeutics Independent lab · 2026-10-07	Black-box RNA sequence design Chemical, biological, radiological, nuclear	“We partnered with Dyno Therapeutics on three evaluations of sequence-to-function modeling and design capability: 1. Black-box RNA sequence design: A medium-horizon challenge on which Dyno has evaluated 57 human participants drawn from the leading edge of the US ML-bio labor market since 2018.” source
Claude Haiku 5.5 Anthropic	Independent lab Independent lab · 2026-10-07	AAV capsid packaging auto-research Chemical, biological, radiological, nuclear	“3. AAV capsid packaging auto-research: As in the previous task, models are provided with a corpus of labeled, unpublished AAV capsid sequences modiﬁed with short insertion sequences in a particular region.” source
Claude Haiku 5.5 Anthropic	Independent lab Independent lab · 2026-10-07	indirect prompt injection (ipi) benchmark Prompt injection and agents	“Claude Haiku 5.5 dramatically improved on Claude Haiku 4.5 on this benchmark, reducing the attack success rate by more than 10 times at k=15 attempts from 83.2% to 7.1%.” source
Claude Haiku 5.5 Anthropic	Independent lab Independent lab · 2026-10-07	Shade Prompt injection and agents	“The attack success rate was 0.08% over all attempts without prompt injection probes, compared to 58.40% for Claude Haiku 4.5.” source
Claude Haiku 5.5 Anthropic	Independent lab Independent lab · 2026-10-07	frontiercode Other	“Claude Haiku 5.5 scored best at max effort: 46.4% on Main and 58.4% on Extended.” source
Claude Haiku 5.5 Anthropic	Independent lab Independent lab · 2026-10-07	frontierswe v2 Other	“Claude Haiku 5.5 scored 43.8% on FrontierSWE v2, slightly below Claude Fable 5 (47.0%) and well above GPT-5.6 Sol (32.2%).” source
Claude Fable 5.1 Anthropic	Epoch AI Independent lab · 2026-10-07	InnovationEval Autonomy and AI research	“Meanwhile, Fable 5 developed a technique similar to STaR and much of the pre-existing literature: resampling all-fail groups conditioned on previous attempts and the verifier’s verdict.” source
Claude Fable 5.1 Anthropic	Epoch AI Independent lab · 2026-10-07	human-in-the-loop review of submissions' achieved scores and their workings Deception and sabotage	“Fable’s claims of improved performance instead came from out-of-scope cheating: it submitted many similar training runs and selected the best-performing result across them, effectively farming seed noise.” source
Claude Fable 5.1 Anthropic	Epoch AI Independent lab · 2026-10-07	EBR-bench Other	“Instead, we will report scores under the new card ban for only the following four models, plus all future models: Claude Fable 5.1, Claude Opus 5, GPT-5.6 Sol, and GPT-6 Astra.” source
Claude Fable 5.1 Anthropic	Epoch AI Independent lab · 2026-10-07	multi-agent experiments Other	“In addition to our card ban experiments, we also ran multi-agent experiments to test whether our default single-agent experimental setup underelicits performance (for example, by failing to sufficiently nudge models to explore different types of decks).” source
Claude Fable 5 Anthropic	Epoch AI Independent lab · 2026-10-07	InnovationEval Other	“However, this ultimately failed to improve performance.” source
Claude Fable 5 Anthropic	Epoch AI Independent lab · 2026-10-07	ablation with the original paper's text provided Other	“Finally, we ran a separate ablation, similar in spirit to PaperBench: could Fable 5 solve the task when provided the original paper’s text?” source
Claude Fable 5 Anthropic	Epoch AI Independent lab · 2026-10-07	AI R&D paper replication task Other	“However, neither model showed signs of having memorized the paper when asked about its details, authors, or title.” source
Mistral Large 4 Mistral AI	Independent lab Independent lab · 2026-10-06	artificial analysis cyber index Cyber	“On the Artificial Analysis Cyber Index, an independent evaluation of how well AI models find and fix security flaws in real software, it ranks among the top five models globally and leads open-weight models developed outside China by a wide margin.” source
Mistral Large 4 Mistral AI	Independent lab Independent lab · 2026-10-06	reproduce and patch a real vulnerability in open-source software Cyber	“On one of the index's tests, which asks a model to reproduce a real vulnerability in open-source software and then patch it, ML4 scores 82%, the highest of any model.” source
Mistral Large 4 Mistral AI	Independent lab Independent lab · 2026-10-06	b3 ai security benchmark Prompt injection and agents	“On Lakera’s public B3 AI Security Benchmark , ML4 resists 93.3% of attacks – we see no higher scores among competitors.” source
Mistral Large 4 Mistral AI	Independent lab Independent lab · 2026-10-06	lakera's public b3 ai security benchmark Misuse and jailbreaks	“On Lakera’s public B3 AI Security Benchmark, ML4 resists 93.3% of attacks – we see no higher scores among competitors.” source
Leanstral 1.5 Mistral AI	Academic Academic · 2026-10-06	52-task held-out single-step BFCL-derived test split Other	“On a 52-task held-out single-step BFCL-derived test split, the Qwen2.5-1.5B/7B pair attains 82.7% task success with 30.8% escalation, versus 67.3% local-only and 75.4% random escalation (which uses 33.8% escalation).” source

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