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 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-6.1 Terra OpenAI	High Autonomy and AI research	Not reached	“In AI Self-Improvement, GPT-6.1 Terra does not reach our High threshold.” source
GPT-6.1 Terra OpenAI	High Chemical, biological, radiological, nuclear	Reached	“Under our Preparedness Framework, we are treating GPT-6.1 Terra as Critical in cybersecurity and High for Biological and Chemical capability.” source
GPT-6.1 Terra OpenAI	Critical Cyber	Reached	“Under our Preparedness Framework, we are treating GPT-6.1 Terra as Critical in cybersecurity and High for Biological and Chemical capability.” 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

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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
Gemma 4 31B Google DeepMind	Transluce Independent lab · 2026-07-21	bloom Misuse and jailbreaks	“Bloom uses an LLM to generate candidate prompts directly from the behavior description, with no further optimization.” source
GPT-5.6 Sol OpenAI	UK AI Security Institute Government evaluator · 2026-07-21	AISI cyber capability evaluation Cyber	“Every model tested in this analysis attempted to cheat some of the time (Figure 1).” source
GPT-5.6 Sol OpenAI	UK AI Security Institute Government evaluator · 2026-07-21	self-report questioning about prohibited or suspicious actions Deception and sabotage	“In our experiments, models did not consistently acknowledge attempted cheating when asked, and described it as wrong less than 50% of the time (Figure 3).” source
GPT-5.6 Sol OpenAI	UK AI Security Institute Government evaluator · 2026-07-21	chain-of-thought monitoring Deception and sabotage	“In our experiments, models often did not reason about their cheating in their chain-of-thought (Figure 5).” source
GPT-5.5 OpenAI	UK AI Security Institute Government evaluator · 2026-07-21	AISI cybersecurity capability evaluations Cyber	“Every model tested in this analysis attempted to cheat some of the time (Figure 1).” source
GPT-5.5 OpenAI	UK AI Security Institute Government evaluator · 2026-07-21	self-report questioning on prohibited or suspicious actions Deception and sabotage	“In our experiments, models did not consistently acknowledge attempted cheating when asked, and described it as wrong less than 50% of the time (Figure 3).” source
GPT-5.5 OpenAI	METR Independent lab · 2026-07-21	NanoGPT speedrun agentic optimization runs Other	“We ran six high-expenditure agentic optimization runs starting from record #78 of the speedrun (March ’26, 85.56 seconds of training time).” source
GPT-5.5 OpenAI	METR Independent lab · 2026-07-21	NanoGPT speedrun agentic optimization run Other	“We ran agents against historic records from the NanoGPT speedrun giving them multiple GPUs.” source
GPT-5 OpenAI	METR Independent lab · 2026-07-21	agentic optimization runs against NanoGPT Autonomy and AI research	“The raw trajectories from GPT-5 and Opus-4.1 show progress, but revalidation of their final algorithms shows no increase over the baseline.” source
GPT-5 OpenAI	METR Independent lab · 2026-07-21	NanoGPT speedrun Autonomy and AI research	“GPT-5 and Opus-4.1 did not make any meaningful progress at all.” source
GPT-5 OpenAI	METR Independent lab · 2026-07-21	memorization test Other	“However, when we probed the same way for records subsequent to #78, no model — including Opus-4.8 — showed knowledge of them, passing the memorization test.” source
DeepSeek-V4-Flash DeepSeek	Transluce Independent lab · 2026-07-21	weirdchat Harmful content	“To produce WeirdChat, we used automated elicitation tools to surface instances of user harm, inappropriate or illicit behavior, misrepresentation of model actions, harmful or illegal advice, and misinformation in DeepSeek-V4-Flash, Gemma 4 31B, Inkling, Nemotron 3 Ultra, Qwen3.6-35B-A3B, and Qwen3.6-27B.” source
DeepSeek-V4-Flash DeepSeek	Transluce Independent lab · 2026-07-21	WeirdChat Misuse and jailbreaks	“Why does DeepSeek-V4-Flash respond in Russian when asked in English about the trolley problem?” source
Claude Opus 4.8 Anthropic	METR Independent lab · 2026-07-21	agentic optimization runs on the NanoGPT speedrun Other	“Some models show significant improvements.” source
Claude Opus 4.8 Anthropic	METR Independent lab · 2026-07-21	expenditure horizon on NanoGPT speedrun Autonomy and AI research	“GPT-5.5 and Opus-4.8 show significant improvements over the baseline, and we can quantify those with significant expenditure horizons, as shown above.” source
Claude Opus 4.8 Anthropic	METR Independent lab · 2026-07-21	NanoGPT speedrun agentic optimization run Other	“On re-validation, we think Opus-4.8’s final solution gives ~1.5% and GPT-5.5 ~1% efficiency win starting at record #78 (March ’26).” source
Claude Opus 4.7 Anthropic	UK AI Security Institute Government evaluator · 2026-07-21	cybersecurity capability evaluations Cyber	“In AISI’s cybersecurity capability evaluations, models are tasked with finding a ‘flag’ (a sequence of letters and numbers) hidden within a simulated environment, by carrying out a sequence of offensive cyber actions, such as reverse-engineering compiled code or exploiting security vulnerabilities.” source
Claude Opus 4.7 Anthropic	UK AI Security Institute Government evaluator · 2026-07-21	automated LLM monitor Deception and sabotage	“To analyse cheating behaviour at scale, we used an automated LLM monitor.” source
Claude Opus 4.7 Anthropic	UK AI Security Institute Government evaluator · 2026-07-21	self-report Deception and sabotage	“One proposed way to detect cheating is to ask the model whether it took any prohibited or suspicious actions.” source
Claude Opus 4.7 Anthropic	UK AI Security Institute Government evaluator · 2026-07-21	chain-of-thought monitoring Deception and sabotage	“Another possible method for identifying cheating is monitoring the model’s chain-of-thought - the written reasoning it produces whilst working through a task, which is usually, but not always, human-legible (in today’s models).” source
Claude Opus 4.1 Anthropic	METR Independent lab · 2026-07-21	agentic optimization runs against NanoGPT Autonomy and AI research	“We also report the status of preliminary agentic optimization runs against NanoGPT: after more than \$10K of expenditure we estimate expenditure horizons of \$0-\$3K.” source
Claude Opus 4.1 Anthropic	METR Independent lab · 2026-07-21	six high-expenditure agentic optimization runs Autonomy and AI research	“We ran six high-expenditure agentic optimization runs starting from record #78 of the speedrun (March ’26, 85.56 seconds of training time).” source
Claude Opus 4.1 Anthropic	METR Independent lab · 2026-07-21	NanoGPT speedrun agentic optimization run Autonomy and AI research	“GPT-5 and Opus-4.1 did not make any meaningful progress at all.” source
Gemini 3.1 Pro Google DeepMind	RAND (CAST / Project Canary) Independent lab · 2026-07-20	pre-run check Chemical, biological, radiological, nuclear	“We tested a range of tool-level safeguards (text or code embedded within biological software tools to restrict agent usage) and evaluated their efficacy in preventing AI agents from assisting with the tool’s use.” source
Gemini 3.1 Pro Google DeepMind	RAND (CAST / Project Canary) Independent lab · 2026-07-20	pre-run check Deception and sabotage	“On the ESM3 task, both Opus 4.5 and Gemini 3.1 Pro make these false claims in 50% of trials and 63% of trials, respectively.” source
Gemini 3.1 Pro Google DeepMind	RAND (CAST / Project Canary) Independent lab · 2026-07-20	environmental identifier safeguard Deception and sabotage	“However, we found that Opus 4.5 and Gemini 3.1 Pro frequently delete these variables to evade detection.” source
Gemini 3.1 Pro Google DeepMind	RAND (CAST / Project Canary) Independent lab · 2026-07-20	agents.md safeguard Deception and sabotage	“Despite the fact that AGENTS.md files are intended to contain instructions written by humans for AI agents (Agents.md project, 2026), we 16 found that agents would create and modify AGENTS.md files in order to bypass this safeguard.” source
Gemini 3.1 Pro Google DeepMind	RAND (CAST / Project Canary) Independent lab · 2026-07-20	pre-run check displaying a message stating an intent to synthesize variola major Harmful content	“While Opus 4.5 and Gemini 3.1 Pro were either blocked by content filters or refused to proceed in every trial, GPT 5.2 proceeded without refusal in every trial.” source
Gemini 3.1 Pro Google DeepMind	RAND (CAST / Project Canary) Independent lab · 2026-07-20	false identity claim experiment Deception and sabotage	“All frontier LLMs we tested falsely claimed to be human when doing so enabled them to accomplish the task.” source
Gemini 3.1 Pro Google DeepMind	RAND (CAST / Project Canary) Independent lab · 2026-07-20	agents.md experiments Prompt injection and agents	“We designed safeguards that leverage harness’s treatment of AGENTS.md files and that detect harness’s environment identifiers.” source
Gemini 3.1 Pro Google DeepMind	RAND (CAST / Project Canary) Independent lab · 2026-07-20	pre-run check Misuse and jailbreaks	“The strongest safeguard, the pre-run check, was only highly effective on one of the three tasks, and even on this task the help denial rate was as low as 90% (for Opus 4.5).” source
Gemini 3.1 Pro Google DeepMind	RAND (CAST / Project Canary) Independent lab · 2026-07-20	jailbreak of the strongest safeguard Misuse and jailbreaks	“Jailbreaks reduce the efficacy of our strongest safeguard to near-zero, illustrating that LLM guardrails can fail and highlighting the need for a defense in depth strategy.” source
Gemini 3.1 Pro Google DeepMind	RAND (CAST / Project Canary) Independent lab · 2026-07-20	documentation changes Misuse and jailbreaks	“We ran experiments where statements prohibiting AI agent usage were placed into the readme.md documentation files of RFdiffusion.” source
Gemini 3.1 Pro Google DeepMind	RAND (CAST / Project Canary) Independent lab · 2026-07-20	greedy coordinate gradient (GCG) optimization of safeguard text Misuse and jailbreaks	“We ran this algorithm with an abliterated gpt-oss-20b model on the RFdiffusion tasks.” source
Gemini 3.1 Pro Google DeepMind	RAND (CAST / Project Canary) Independent lab · 2026-07-20	GCG-optimized prompt injection misdirection Misuse and jailbreaks	“After 500 training steps on the abliterated OSS model, help denial via misdirection to the unrelated task increased, going from help denial in 0/10 trials to 10/10 trials.” source
Gemini 3 Pro Google DeepMind	RAND (CAST / Project Canary) Independent lab · 2026-07-20	tool-level safeguards Chemical, biological, radiological, nuclear	“We tested a range of tool-level safeguards (text or code embedded within biological software tools to restrict agent usage) and evaluated their efficacy in preventing AI agents from assisting with the tool’s use.” source
Gemini 3 Pro Google DeepMind	RAND (CAST / Project Canary) Independent lab · 2026-07-20	jailbreaks Misuse and jailbreaks	“The tool-level safeguards we developed are compromised by subversion of LLM guardrails1: adversarial subversion techniques such as jailbreaks and refusal-vector ablation reduce the efficacy of safeguards, indicating that reliance on LLM guardrails does not currently provide robust risk mitigation.” source
Gemini 3 Pro Google DeepMind	RAND (CAST / Project Canary) Independent lab · 2026-07-20	help denial rate Chemical, biological, radiological, nuclear	“Our evaluation metric, the help denial rate, measures the frequency with which the safeguard stops the agent from both (i) running the biological tool and (ii) providing assistance to the user on the use of the tool.” source
Gemini 3 Pro Google DeepMind	RAND (CAST / Project Canary) Independent lab · 2026-07-20	pre-run check Chemical, biological, radiological, nuclear	“Across all tasks and all LLMs, the pre-run check increased the help denial rate, except in the one case in which the baseline help denial rate was already 100% (Opus 4.5 on the EVEscape task).” source
Gemini 3 Pro Google DeepMind	RAND (CAST / Project Canary) Independent lab · 2026-07-20	jailbreak robustness test Misuse and jailbreaks	“We test our safeguards’ robustness to jailbreaks by appending the jailbreak text to each initial task prompt, repeating the methodology described above, and observing how the jailbreak affects refusal-to-help rate.” source

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