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
Gemini 3.1 Flash-Lite Google DeepMind	Redwood Research Independent lab · 2026-07-27	SWE-bench Verified Other	“SWE-bench Verified, Gemini 3.1 Flash Lite: M = 36, so 5.17 bits/step × 35.1 steps ≈ 182 bits/task” source
Claude Sonnet 4.6 Anthropic	Redwood Research Independent lab · 2026-07-27	untrusted advice protocol Other	“For example, in SWE-bench, U can provide just 16 characters of advice per message to recover about 67% of the performance gap between T and U.” source
Claude Sonnet 4.6 Anthropic	Redwood Research Independent lab · 2026-07-27	information-bottlenecked untrusted advice protocol usefulness evaluation Other	“We evaluate the usefulness of our protocol for various information budgets, demonstrating promising results in BashArena and SWE-bench Verified.” source
Claude Sonnet 4.6 Anthropic	Redwood Research Independent lab · 2026-07-27	best-of-n protocol Other	“In “Appendix: best-of-n protocol”, we try sampling 16 actions from T on each step and letting U choose the one it thinks is best, but this doesn’t improve performance.” source
Claude Sonnet 4.6 Anthropic	Redwood Research Independent lab · 2026-07-27	best-of-n experiment in BashArena Other	“Results: In a simple best-of-n experiment in BashArena, using Claude Sonnet 4.6 as U, Gemini 3.1 Flash Lite as T, and n=16, U did not improve on the baseline of using T alone.” source
Claude Sonnet 4.6 Anthropic	Redwood Research Independent lab · 2026-07-27	experiments where we limited how often u can give advice Other	“Neither approach to limiting advice frequency improves the Pareto frontier of usefulness vs. characters seen by T, suggesting that limiting information per message may be more important than limiting message frequency.” source
Claude Sonnet 4.6 Anthropic	Redwood Research Independent lab · 2026-07-27	preliminary experiments using an autoresearch-like approach to get claude opus or fable to create a custom untrusted advice protocol Other	“We tried some preliminary experiments using an autoresearch-like approach to get Claude Opus or Fable to create a custom untrusted advice protocol, given a per-trajectory bit budget.” source
Claude Sonnet 4.6 Anthropic	Redwood Research Independent lab · 2026-07-27	early experiments which weakly suggest that malicious advice does not have substantially greater surprisal than benign advice in basharena Other	“While we avoided spending much effort on evaluating safety in this project, we ran early experiments which weakly suggest that malicious advice does not have substantially greater surprisal than benign advice in BashArena, given similar character counts.” source
Claude Opus 5 Anthropic	UK AI Security Institute Government evaluator · 2026-07-24	cyber range testing Cyber	“We report ﬁve capability evaluations—ExploitBench, OSS-Fuzz, Firefox 147, and two newly added benchmarks, CyScenarioBench and ExploitGym—alongside external cyber range testing from the UK AI Security Institute.” source
Claude Opus 5 Anthropic	Dyno Therapeutics Independent lab · 2026-07-24	Black-box RNA sequence design Chemical, biological, radiological, nuclear	“We partnered with Dyno Therapeutics on two sequence-to-function evaluations: a black-box RNA sequence modeling and design challenge benchmarked against 57 human participants drawn from the leading edge of the US ML-bio labor market, and an AAV capsid packaging prediction task measuring whether model domain knowledge and machine learning capabilities can outperform pretrained protein language models.” source
Claude Opus 5 Anthropic	Government evaluator Government evaluator · 2026-07-24	cyber ranges Cyber	“Opus 5 was assessed on three multi-step, agentic “cyber ranges”: end-to-end network-attack simulations run at a budget of 100M tokens per attempt.” source
Claude Opus 5 Anthropic	Trajectory Labs Independent lab · 2026-07-24	external red-teaming of safeguards Misuse and jailbreaks	“Trajectory Labs, PBC spent roughly 100 hours red-teaming our safeguards.” source
Claude Opus 5 Anthropic	Independent lab Independent lab · 2026-07-24	automated attacker Misuse and jailbreaks	“Grayswan also ran an automated attacker using 150 attempts per task on our example tasks and found that the automated attacker was unable to accomplish any of the tasks.” source
Claude Opus 5 Anthropic	Independent lab Independent lab · 2026-07-24	Indirect Prompt Injection (IPI) benchmark Prompt injection and agents	“On the IPI benchmark, Opus 5 improved over Opus 4.8, reducing the probability of an attacker succeeding within 15 attempts from 5.5% to 2.0%, and from 0.5% to 0.2% on 1 attempt.” source
Claude Opus 5 Anthropic	Independent lab Independent lab · 2026-07-24	Shade Prompt injection and agents	“Claude Opus 5 With thinking 0.56% 13/40 0.18% 4/40 Without thinking 0.41% 8/40 0.18% 4/40” source
Claude Opus 5 Anthropic	Government evaluator Government evaluator · 2026-07-24	unprompted evaluations of safety research compromise Deception and sabotage	“Opus 5 does not compromise safety research in our unprompted evaluations, does not fully refuse to assist with safety research, and has a similar number of partial refusals to assist with safety research compared to the other models.” source
Claude Opus 5 Anthropic	Government evaluator Government evaluator · 2026-07-24	unprompted evaluation Deception and sabotage	“Opus 5 mentions the possibility of being tested in our unprompted evaluation 9.8% of the time and mentions it 2.8% of the time in the continuation evaluation.” source
Claude Opus 5 Anthropic	Government evaluator Government evaluator · 2026-07-24	safety research compromise evaluations Deception and sabotage	“All models tested, including Opus 5, can reliably distinguish our safety research compromise evaluations from deployment data when prompted, although this is likely driven in part by differences in the task distribution, where evaluation tasks are necessarily higher-stakes settings with more safety implications than the deployment data we source from.” source
Claude Opus 5 Anthropic	Government evaluator Government evaluator · 2026-07-24	continuation evaluation Deception and sabotage	“Opus 5 actively continues compromising safety research 0.1% of the time (2 out of 1482 samples), compared with 13.6% for Mythos 5, 1.7% of the time for Mythos Preview and 0.8% of the time for both Opus 4.7 and Opus 4.8.” source
Claude Opus 5 Anthropic	Independent lab Independent lab · 2026-07-24	GDPval-AA v2 Other	“Claude Opus 5 takes the top two spots on the leaderboard: ELO 1861 at max effort and 1827 at xhigh .” source
Claude Opus 5 Anthropic	Independent lab Independent lab · 2026-07-24	AA-Briefcase Other	“Claude Opus 5 takes the top three spots on the leaderboard: ELO 1720 at max effort, 1693 at xhigh , and 1606 at high .” source
Claude Opus 5 Anthropic	Independent lab Independent lab · 2026-07-24	ARC-AGI-1 Other	“The ARC Prize Foundation reports that Claude Opus 5 achieved a veriﬁed score of 97.50% on ARC-AGI-1 and 90.42% on ARC-AGI-2 at max effort on their semi-private datasets.” source
Kimi K3 Moonshot AI	US CAISI (NIST) Government evaluator · 2026-07-23	exploitbench Cyber	“Kimi K3 achieves a score of 32%, whereas GLM-5.2 achieves a score of 24% (Figure 1).” source
Kimi K3 Moonshot AI	US CAISI (NIST) Government evaluator · 2026-07-23	the last ones (tlo) Cyber	“Specifically, Kimi K3 reached step 17 of this 32-step attack path on average, while the most cyber-capable U.S. models reached 28.5 steps on average.” source
Kimi K3 Moonshot AI	US CAISI (NIST) Government evaluator · 2026-07-23	ExploitBench arbitrary code execution (ACE) milestone Cyber	“Kimi K3 achieved ACE on 0/41 samples, whereas the most cyber-capable models achieved ACE on 20/41 samples on average (Figure 3).” source
GPT-5.6 Sol OpenAI	SecureBio Independent lab · 2026-07-23	able Chemical, biological, radiological, nuclear	“on able, a protein-design workflow spanning structure retrieval, sequence generation, and design validation, gpt-5.6 sol delivered best-in-class performance on every task it was willing to attempt, though it refused the highest-level planning steps.” source
GPT-5.6 Sol OpenAI	SecureBio Independent lab · 2026-07-23	dna synthesis screening evasion task Chemical, biological, radiological, nuclear	“the railfree variant set a new high score, reliably identifying a known (though practically inconvenient) method that evades a commercial screening algorithm on the large majority of attempts.” source
GPT-5.6 Sol OpenAI	SecureBio Independent lab · 2026-07-23	manual assessment of dual-use biological queries Chemical, biological, radiological, nuclear	“without api-level safeguards, gpt-5.6 sol occasionally included potentially hazardous information in its responses, such as analysis of the pandemic potential of different viral mutations.” source
GPT-5.6 Sol OpenAI	SecureBio Independent lab · 2026-07-23	manual assessment Chemical, biological, radiological, nuclear	“gpt-5.6 sol also demonstrated impressive agentic capabilities and provided meaningful expert uplift on dual-use tasks, although human input remained necessary due to the model’s limitations in judgement and perspective.” source
GPT-5.5 OpenAI	SecureBio Independent lab · 2026-07-23	world-class bio (wcb) Chemical, biological, radiological, nuclear	“gpt-5.6 sol scored 68%, about nine percentage points above openai’s previous flagship model, gpt-5.5.” source
GPT-5.5 OpenAI	SecureBio Independent lab · 2026-07-23	reprobait Chemical, biological, radiological, nuclear	“on average, gpt-5.6 sol recovered 82% of the original tools’ published performance.” source
GPT-5.5 OpenAI	SecureBio Independent lab · 2026-07-23	biotier Chemical, biological, radiological, nuclear	“gpt 5.6 sol refused 66% of high-risk prompts, whilst correctly responding to 99% of safe prompts.” source
GPT-5.5 OpenAI	SecureBio Independent lab · 2026-07-23	manual assessment Chemical, biological, radiological, nuclear	“our team’s scientific experts performed manual assessments of a railfree variant of gpt-5.6 sol to understand how it responds to dual-use biological queries.” source
Claude Sonnet 4.6 Anthropic	UK AI Security Institute Government evaluator · 2026-07-23	asynchronous reasoning monitor red teaming exercise Deception and sabotage	“With Google DeepMind, we tested an asynchronous reasoning monitor (reviewing agents’ reasoning after they act) designed to detect agents deceptively pursuing misaligned goals.” source
Claude Sonnet 4.6 Anthropic	UK AI Security Institute Government evaluator · 2026-07-23	synchronous internal agentic coding monitor red teaming exercise Deception and sabotage	“With Anthropic, we tested successive versions of a synchronous internal agentic coding monitor (reviewing each action before it executes).” source
Claude Sonnet 4.6 Anthropic	UK AI Security Institute Government evaluator · 2026-07-23	evolutionary search algorithm red teaming experiment in a single-step coding setting Deception and sabotage	“For example, one of our early experiments used our algorithm to red team a monitor in a challenging single-step coding setting, where an agent produces code that covertly exposes their private API key.” source
GPT-5.6 Sol OpenAI	Epoch AI Independent lab · 2026-07-22	Cyber Ranges Cyber	“The UK AI Security Institute has directly evaluated models on their ability to take over realistic simulations of a corporate network, and found that both Mythos 5 and GPT-5.6 Sol are able to consistently fully compromise the network, in attacks that they estimate would take human cybersecurity experts several working days.” source
GPT-5.6 Sol OpenAI	Epoch AI Independent lab · 2026-07-22	FrontierCyber Cyber	“When Irregular evaluated GPT-5.6 Sol’s cyber capabilities on their challenging FrontierCyber benchmark they found that: While attempting to solve challenges in the FrontierCyber benchmark, GPT-5.6 Sol discovered multiple new zero-day vulnerabilities in real-world targets, including widely used software and mobile devices.” source
GPT-5.6 Sol OpenAI	Epoch AI Independent lab · 2026-07-22	Cyber ECI Cyber	“We found that Mythos and 5.6 Sol represented very large leaps in cyber capabilities compared to the prior trend: Currently, access to this level of capabilities is gated by OpenAI and Anthropic’s cyber access programs (and the restrictions placed on their generally available models), as open-weight models do not yet have the relevant level of cyber capabilities.” source
Claude Mythos 5 Anthropic	Epoch AI Independent lab · 2026-07-22	UK AISI's Cyber Ranges Cyber	“The UK AI Security Institute has directly evaluated models on their ability to take over realistic simulations of a corporate network, and found that both Mythos 5 and GPT-5.6 Sol are able to consistently fully compromise the network, in attacks that they estimate would take human cybersecurity experts several working days.” source

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