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
Claude Sonnet 4.5 Anthropic	Transluce Independent lab · 2026-08-04	monitor evasion detection on coding agent transcripts Deception and sabotage	“On these transcripts, 1.9% contained a severe case of monitor evasion: the agents merged a PR to main or disabled tests; and 1.8% contained cases where the agent claimed review had passed before it completed or fabricated human approval.” source
Claude Opus 4.5 Anthropic	Transluce Independent lab · 2026-08-04	overselling rubric Deception and sabotage	“We found severe cases of monitor evasion in 1.9% of swe-chat sessions, and severe cases of overselling in 1.8% of sessions.” source
Claude Opus 4.5 Anthropic	Transluce Independent lab · 2026-08-04	monitor evasion detection in coding agent transcripts Deception and sabotage	“On these transcripts, 1.9% contained a severe case of monitor evasion: the agents merged a PR to main or disabled tests; and 1.8% contained cases where the agent claimed review had passed before it completed or fabricated human approval.” source
Claude Mythos 5 Anthropic	UK AI Security Institute Government evaluator · 2026-08-04	cyber range challenge Cyber	“Our investigation found that in 10 of those runs, an AI agent took autonomous, unsanctioned action on the live internet, targeting real people and organisations.” source
Claude Haiku 4.5 Anthropic	Transluce Independent lab · 2026-08-04	overselling success Deception and sabotage	“On these transcripts, 1.9% contained a severe case of monitor evasion: the agents merged a PR to main or disabled tests; and 1.8% contained cases where the agent claimed review had passed before it completed or fabricated human approval.” source
GPT-5.5 OpenAI	SaferAI Independent lab · 2026-08-02	LAB-Bench Chemical, biological, radiological, nuclear	“On biological knowledge, it was about level with Opus 4.7 and slightly below GPT-5.5, roughly two months behind.” source
GPT-5.5 OpenAI	SaferAI Independent lab · 2026-08-02	SWE-bench Pro Autonomy and AI research	“On software engineering, it was the furthest behind, below Opus 4.6 and GPT-5.4, the frontier models from around four months earlier.” source
GPT-5.5 OpenAI	SaferAI Independent lab · 2026-08-02	Agentic Misalignment Deception and sabotage	“Additionally, it attempted persuasion on conspiracy and control-undermining topics more readily than the comparison models, and it could be pushed into harmful actions under pressure.” source
GPT-5.5 OpenAI	SaferAI Independent lab · 2026-08-02	agentic misalignment benchmark Deception and sabotage	“In this evaluation, GLM-5.2 never displays any leaking or murder behavior, similar to GPT-5.5 and Opus 4.7.” source
GPT-5.5 OpenAI	SaferAI Independent lab · 2026-08-02	agentic misalignment evaluation Deception and sabotage	“In this evaluation, Claude Opus 4.7 and GPT-5.5 display a 0% harmful-action rate across every scenario, goal, and threat condition.” source
GPT-5.5 OpenAI	SaferAI Independent lab · 2026-08-02	MASK Deception and sabotage	“Opus 4.7 lies in 17% of the trials and GPT-5.5 in 10%.” source
GPT-5.5 OpenAI	SaferAI Independent lab · 2026-08-02	APE (Attempt to Persuade Eval) Harmful content	“GLM-5.2 attempts to persuade towards conspiracy in 43% of the cases as opposed to 8% for Opus 4.7 and 18% for GPT-5.5.” source
GPT-5.5 OpenAI	SaferAI Independent lab · 2026-08-02	Petri audit Deception and sabotage	“By comparison, GPT-5.5 behaved more conservatively across the audit.” source
GPT-5.5 OpenAI	SaferAI Independent lab · 2026-08-02	Attempt to Persuade Eval (APE) Misuse and jailbreaks	“We run our own GPT-5.5 and Opus 4.7 baselines, using the same harness and the same conﬁguration for the supporting roles (e.g., the simulated persuadee) as we used for GLM-5.2.” source
GPT-5.5 OpenAI	SaferAI Independent lab · 2026-08-02	Agentic misalignment scenarios Deception and sabotage	“We evaluate GLM-5.2, GPT-5.5, and Claude Opus 4.7 on Anthropic's Agentic Misalignment scenarios (Lynch et al. 2025), with Inspect Evals (UK AI Security Institute, n.d.-b).” source
GPT-5.4 mini OpenAI	SaferAI Independent lab · 2026-08-02	cybergym Cyber	“We run CyberGym on GLM-5.2 using Inspect Evals (UK AI Security Institute, n.d.-b), comparing against the GPT-5.5 and Claude Opus 4.6 results published by Lyptus Research (Payne et al., 2026) on the same 122-task Level 1 sample (see Appendix A.2 for details).” source
GPT-5.4 mini OpenAI	SaferAI Independent lab · 2026-08-02	biomysterybench Chemical, biological, radiological, nuclear	“On biological knowledge, it was about level with Opus 4.7 and slightly below GPT-5.5, roughly two months behind.” source
GPT-5.4 mini OpenAI	SaferAI Independent lab · 2026-08-02	swe-bench pro Autonomy and AI research	“On software engineering, it was the furthest behind, below Opus 4.6 and GPT-5.4, the frontier models from around four months earlier.” source
GPT-5.4 mini OpenAI	SaferAI Independent lab · 2026-08-02	agentic misalignment Deception and sabotage	“Additionally, it attempted persuasion on conspiracy and control-undermining topics more readily than the comparison models, and it could be pushed into harmful actions under pressure.” source
GPT-5.4 mini OpenAI	SaferAI Independent lab · 2026-08-02	automated behavioral audit Other	“Beyond capability, it refused none of the oﬀensive-security or biological tasks, and as an open-weight model, any safeguards that might be present can be stripped by a self-hoster.” source
GPT-5.4 mini OpenAI	SaferAI Independent lab · 2026-08-02	reward-hacking analysis Deception and sabotage	“Our reward-hacking analysis ( Appendix A.5.1.2 ) found that when transcripts showing signs of reward hacking are excluded, GLM-5.2's solve rate falls from 43% to 37%, and spot-checks suggest the agent's cheating attempts frequently succeeded.” source
GPT-5.4 mini OpenAI	SaferAI Independent lab · 2026-08-02	agentic misalignment blackmail scenario Deception and sabotage	“When the goal is implicit (latent) in the email contents that the model reads (latent goal), GLM-5.2 chose to blackmail 10% of the time under the threat of replacement.” source
GPT-5.4 mini OpenAI	SaferAI Independent lab · 2026-08-02	LLM judge assessment of SWE-bench Pro transcripts for environment issues Other	“Spot checking indicates a reasonable correspondence between judge score and genuine environment issues.” source
GPT-5.4 mini OpenAI	SaferAI Independent lab · 2026-08-02	MASK Deception and sabotage	“Table A.3 breaks down MASK honesty by prompt category, with 95% Wilson CI scores.” source
GLM-5.2 Z.ai (Zhipu AI)	SaferAI Independent lab · 2026-08-02	Cybench Cyber	“We run Cybench on GLM-5.2, GPT-5.5, and Opus 4.7 using Inspect Evals (UK AI Security Institute, n.d.-b).” source
GLM-5.2 Z.ai (Zhipu AI)	SaferAI Independent lab · 2026-08-02	CyberGym Cyber	“We run CyberGym on GLM-5.2 using Inspect Evals (UK AI Security Institute, n.d.-b), comparing against the GPT-5.5 and Claude Opus 4.6 results published by Lyptus Research (Payne et al., 2026) on the same 122-task Level 1 sample (see Appendix A.2 for details).” source
GLM-5.2 Z.ai (Zhipu AI)	SaferAI Independent lab · 2026-08-02	LAB-Bench Chemical, biological, radiological, nuclear	“GLM-5.2 meets or exceeds the human-expert score on all of the subtasks.” source
GLM-5.2 Z.ai (Zhipu AI)	SaferAI Independent lab · 2026-08-02	BioMysteryBench Chemical, biological, radiological, nuclear	“GLM-5.2 scores comparably to both GPT-5.5 and Opus 4.7 on both the human-solvable and human-diﬃcult datasets.” source
GLM-5.2 Z.ai (Zhipu AI)	SaferAI Independent lab · 2026-08-02	SWE-bench Pro Autonomy and AI research	“GLM-5.2 solves 43% of the tasks we run.” source
GLM-5.2 Z.ai (Zhipu AI)	SaferAI Independent lab · 2026-08-02	Agentic Misalignment Deception and sabotage	“In this evaluation, GLM-5.2 never displays any leaking or murder behavior, similar to GPT-5.5 and Opus 4.7.” source
GLM-5.2 Z.ai (Zhipu AI)	SaferAI Independent lab · 2026-08-02	agentic misalignment evaluation Deception and sabotage	“When the goal is implicit (latent) in the email contents that the model reads (latent goal), GLM-5.2 chose to blackmail 10% of the time under the threat of replacement.” source
GLM-5.2 Z.ai (Zhipu AI)	SaferAI Independent lab · 2026-08-02	MASK Deception and sabotage	“GLM-5.2 is honest on 61% of prompts, lies on 21%, and evades or holds no belief on 18%.” source
GLM-5.2 Z.ai (Zhipu AI)	SaferAI Independent lab · 2026-08-02	APE Misuse and jailbreaks	“GLM-5.2 attempts to persuade towards conspiracy in 43% of the cases as opposed to 8% for Opus 4.7 and 18% for GPT-5.5.” source
GLM-5.2 Z.ai (Zhipu AI)	SaferAI Independent lab · 2026-08-02	Petri Deception and sabotage	“We audit GLM-5.2 and GPT-5.5 using Inspect Petri 3.0, running all 173 of the public seeds ( Appendix A.6.1 ).” source
GLM-5.2 Z.ai (Zhipu AI)	SaferAI Independent lab · 2026-08-02	Petri Misuse and jailbreaks	“Its cooperation with misuse scored 6 or higher on 14 of the 166 scored seeds and 7 or higher on 8 of them.” source
GLM-5.2 Z.ai (Zhipu AI)	SaferAI Independent lab · 2026-08-02	agentic misalignment evaluations Autonomy and AI research	“In our Agentic Misalignment evaluations, GPT-5.5 verbalized its awareness of being evaluated 10% of the time, and GLM-5.2 verbalized it 30% of the time.” source
GLM-5.2 Z.ai (Zhipu AI)	SaferAI Independent lab · 2026-08-02	SWE-bench Pro Cyber	“We run the public tasks from SWE-Bench Pro (Scale AI, n.d.-b) using Inspect Harbor (Meridian Labs, n.d.-b), which provides an interface to run Harbor tasks (Meridian Labs, n.d.-a) inside Inspect AI (UK AI Security Institute, n.d.-a).” source
GLM-5.2 Z.ai (Zhipu AI)	SaferAI Independent lab · 2026-08-02	LLM judge assessment of SWE-bench Pro transcripts for environment issues Other	“32% of transcripts have judge_score 5 or higher.” source
GLM-5.2 Z.ai (Zhipu AI)	SaferAI Independent lab · 2026-08-02	LLM judge assessment of SWE-bench Pro transcripts for reward hacking Other	“When removing transcripts with a judge_score >= 3 (41% of samples excluded), or a judge_score >= 2 (48% of samples excluded), the agent’s score reduces to 37%.” source
GLM-5.2 Z.ai (Zhipu AI)	SaferAI Independent lab · 2026-08-02	Attempt to Persuade Eval (APE) Misuse and jailbreaks	“We run the full 600-prompt set in the main persuade condition.” source

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