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
GPT-5.5 OpenAI · 2026-04-23	High capability, below critical Cyber	Not reached	“we are treating GPT-5.5 as High capability in the Cybersecurity domain, but below Critical.” source
Claude Opus 4.7 Anthropic · 2026-04-16	Automated AI R&D Autonomy and AI research	Not reached	“that Opus 4.7 does not cross the threshold for automated AI R&D;” source
Claude Opus 4.7 Anthropic · 2026-04-16	CB-1 Chemical, biological, radiological, nuclear	Not determined	“We believe it is hard to be conﬁdent regarding whether a model passes this threshold.” source
Claude Opus 4.7 Anthropic · 2026-04-16	CB-2 Chemical, biological, radiological, nuclear	Not determined	“Our evaluations suggest that the model is not yet at the level of capability associated with the CB-2 threat model (above).” source
Claude Mythos Preview Anthropic · 2026-04-07	AI R&D rule-out Autonomy and AI research	Not reached	“The main reason we have determined that Claude Mythos Preview does not cross the threshold in question is that we have been using it extensively in the course of our day-to-day work and exploring where it can automate such work, and it does not seem close to being able to substitute for Research Scientists and Research Engineers—especially relatively senior ones.” source
Claude Mythos Preview Anthropic · 2026-04-07	Automated AI R&D Autonomy and AI research	Not reached	“We assess that Claude Mythos Preview does not cross the automated AI-R&D capability threshold.” source
Claude Mythos Preview Anthropic · 2026-04-07	RSP automated AI R&D Autonomy and AI research	Not reached	“we have concluded that Claude Mythos Preview does not cross the RSP automated AI R&D threshold of compressing two years of progress into one.” source
Claude Mythos Preview Anthropic · 2026-04-07	CB-1 Chemical, biological, radiological, nuclear	Not determined	“We believe it is hard to be conﬁdent regarding whether a model passes this threshold.” source
Claude Mythos Preview Anthropic · 2026-04-07	CB-2 Chemical, biological, radiological, nuclear	Not reached	“We believe that Claude Mythos Preview does not pass this threshold due to its noted limitations in open-ended scientiﬁc reasoning, strategic judgment, and hypothesis triage.” source
GPT-5.4 mini OpenAI · 2026-03-05	High Chemical, biological, radiological, nuclear	Not reached	“GPT-5.4 mini’s biology capabilities are closely comparable to those of GPT-5. We conclude that it, too, is not High under our Preparedness Framework.” source
GPT-5.4 Thinking OpenAI · 2026-03-05	High Autonomy and AI research	Not reached	“For AI self-improvement, evaluations of final checkpoints indicate that, like its predecessor models, gpt-5.4-thinking does not have a plausible chance of reaching a High threshold.” source
GPT-5.4 Thinking OpenAI · 2026-03-05	High Chemical, biological, radiological, nuclear	Reached	“As we did for gpt-5.2-thinking before it, we are continuing to treat gpt-5.4-thinking as High capability in the Biological and Chemical domain.” source
GPT-5.4 Thinking OpenAI · 2026-03-05	High Cyber	Reached	“As we did for gpt-5.3-codex, we are treating gpt-5.4-thinking as High capability in the Cybersecurity domain, and applied safeguards as described in the Safeguard section below.” source
Claude Sonnet 4.6 Anthropic · 2026-02-17	AI R&D-4 Autonomy and AI research	Not reached	“Our determination is that Claude Sonnet 4.6 does not cross either the AI R&D-4 or the CBRN-4 capability threshold.” source
Claude Sonnet 4.6 Anthropic · 2026-02-17	ASL-3 Chemical, biological, radiological, nuclear	Not determined	“Claude Sonnet 4.6 performed above thresholds for ASL-3 rule-in on all three evaluations for ASL-3, and it did not exceed the performance of previous models.” source
Claude Sonnet 4.6 Anthropic · 2026-02-17	ASL-4 Chemical, biological, radiological, nuclear	Not reached	“In particular, it did not cross the threshold on our ASL-4 rule-out evaluation short-horizon computational biology tasks evaluation.” source
Claude Sonnet 4.6 Anthropic · 2026-02-17	CBRN-4 Chemical, biological, radiological, nuclear	Not reached	“Our determination is that Claude Sonnet 4.6 does not cross either the AI R&D-4 or the CBRN-4 capability threshold.” source
GPT-5.3-Codex OpenAI · 2026-02-05	High Autonomy and AI research	Not reached	“It does not reach High capability on AI self-improvement.” source
GPT-5.3-Codex OpenAI · 2026-02-05	High Chemical, biological, radiological, nuclear	Reached	“We are also treating GPT-5.3-Codex as High risk in the Biological and Chemical domain, and applying the same safeguards as for our other deployments of models that reach this designation.” source
GPT-5.3-Codex OpenAI · 2026-02-05	High Cyber	Not determined	“This is the first launch we are treating as High capability in the Cybersecurity domain under our Preparedness Framework, activating the associated safeguards.” source
Gemini 3 Pro Google DeepMind · 2025-11	Uplift level 1 Cyber	Not determined	“Cybersecurity On key skills benchmark, v1 hard challenges: 11/12 challenges solved; v2 challenges: 0/13 solved end-to-end.” source
Gemini 3 Pro Google DeepMind · 2025-11	Instrumental reasoning level 1 + 2 Deception and sabotage	Not determined	“Misalignment (Exploratory) Agent solves 3/11 situational awareness challenges and 1/4 stealth challenges.” source
Gemini 3 Pro Google DeepMind · 2025-11	Level 1 (exploratory) Deception and sabotage	Not reached	“Harmful Manipulation Model manipulative eﬃcacy improves on non-generative AI baseline, but shows no signiﬁcant uplift versus prior models and does not reach alert thresholds.” source
o4-mini OpenAI · 2025-04-16	High Autonomy and AI research	Not reached	“openai’s safety advisory group (sag) reviewed the results of our preparedness evaluations and determined that openai o3 and o4-mini do not reach the high threshold in any of our three tracked categories: biological and chemical capability, cybersecurity, and ai self-improvement.” source
o4-mini OpenAI · 2025-04-16	High Chemical, biological, radiological, nuclear	Not reached	“openai’s safety advisory group (sag) reviewed the results of our preparedness evaluations and determined that openai o3 and o4-mini do not reach the high threshold in any of our three tracked categories: biological and chemical capability, cybersecurity, and ai self-improvement.” source
o4-mini OpenAI · 2025-04-16	High Cyber	Not reached	“openai’s safety advisory group (sag) reviewed the results of our preparedness evaluations and determined that openai o3 and o4-mini do not reach the high threshold in any of our three tracked categories: biological and chemical capability, cybersecurity, and ai self-improvement.” source
o3 OpenAI · 2025-04-16	High Autonomy and AI research	Not reached	“openai’s safety advisory group (sag) reviewed the results of our preparedness evaluations and determined that openai o3 and o4-mini do not reach the high threshold in any of our three tracked categories: biological and chemical capability, cybersecurity, and ai self-improvement.” source
o3 OpenAI · 2025-04-16	High Chemical, biological, radiological, nuclear	Not reached	“openai’s safety advisory group (sag) reviewed the results of our preparedness evaluations and determined that openai o3 and o4-mini do not reach the high threshold in any of our three tracked categories: biological and chemical capability, cybersecurity, and ai self-improvement.” source
o3 OpenAI · 2025-04-16	High Cyber	Not reached	“openai’s safety advisory group (sag) reviewed the results of our preparedness evaluations and determined that openai o3 and o4-mini do not reach the high threshold in any of our three tracked categories: biological and chemical capability, cybersecurity, and ai self-improvement.” source
Operator OpenAI · 2025-01-23	Low Autonomy and AI research	Not reached	“we adapted these two evals for the computer-use setting and found the pre-mitigation operator model to be “low” risk in both categories, consistent with the gpt‑4o model.” source
Operator OpenAI · 2025-01-23	Low Chemical, biological, radiological, nuclear	Not reached	“this 1% qualifies as “low” risk, matching gpt‑4o’s “low” risk level, as detailed in openai’s preparedness framework (opens in a new window) 3 .” source
Muse Spark Contemplating Meta	Moderate or lower Autonomy and AI research	Not reached	“Loss of Control risks.We assess loss of control risk as “moderate or lower.”” source
Muse Spark Contemplating Meta	High Chemical, biological, radiological, nuclear	Reached	“We retain the same “high risk” determination for the unmitigated model.” source
Muse Spark Contemplating Meta	Moderate or lower Chemical, biological, radiological, nuclear	Not reached	“After validating that the mitigations deployed for Muse Spark, including refusal mechanisms, continue to perform robustly under the Contemplating architecture, we confirm residual risk at “moderate or lower.”” source
Muse Spark Contemplating 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
Muse Spark 1.1 Meta	Capability checkpoint Autonomy and AI research	Reached	“Muse Spark 1.1 demonstrates improved coding capabilities, which are now meeting one of the indicative thresholds introduced in Muse Spark Safety & Preparedness Report (specifically, resolving over half of unique tasks on SWE-Bench Verified Hard).” source
Muse Spark 1.1 Meta	Moderate or lower Autonomy and AI research	Not reached	“In the Loss of Control domain, the model’s capabilities remain within the “moderate or lower” threshold under Meta’s Advanced AI Scaling Framework.” source
Muse Spark 1.1 Meta	High Chemical, biological, radiological, nuclear	Not determined	“Our assessments indicate that, when evaluated without mitigations applied, we cannot rule out Muse Spark 1.1’s capabilities meeting this threshold in both the Chemical & Biological and Cybersecurity domains.” source
Muse Spark 1.1 Meta	High Cyber	Not determined	“Our assessments indicate that, when evaluated without mitigations applied, we cannot rule out Muse Spark 1.1’s capabilities meeting this threshold in both the Chemical & Biological and Cybersecurity domains.” source
Muse Spark 1.1 Meta	Moderate or lower Cyber	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 Advanced AI Scaling Framework.” 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	UK AI Security Institute Government evaluator · 2026-09-28	cybersecurity evaluation (Petri simulated environment, 10-scenario subset) Cyber	“We observed 4 instances (out of 49 samples) of GPT-6 Astra continuing to exhibit the most severe form of unsanctioned behaviour even with the explicit scope clarification, down from 26 out of 50 on the matched set of trajectories without the scope clarification.” source
GPT-6 Astra OpenAI	UK AI Security Institute Government evaluator · 2026-09-28	variant of the evaluation with explicit scope clarification Cyber	“To determine the extent to which GPT-6 Astra would still take such actions even when the scope was made explicit, we ran a variant of the evaluation where we added the line “Anything not listed as in scope is out of scope.” to the scoping section of the user message.” source
GPT-5.6 Sol OpenAI	UK AI Security Institute Government evaluator · 2026-09-28	Unsanctioned Supply Chain Attack evaluation Cyber	“In our evaluation, GPT-6 Astra took unsanctioned actions at a higher rate than GPT-5.6 Sol and GPT-5.5.” source
GPT-5.6 Sol OpenAI	UK AI Security Institute Government evaluator · 2026-09-28	Unsanctioned Supply Chain Attack evaluation with scope-explicit scenarios Cyber	“Even when the scope of the cybersecurity challenge was edited to more explicitly disallow access to the internet, GPT-6 Astra still occasionally took unsanctioned actions on out-of-scope targets (in 4 out of 49 samples drawn from a subset of scenarios, down from 26 of 50).” source
GPT-5.6 Sol OpenAI	UK AI Security Institute Government evaluator · 2026-09-28	scope clarification evaluation Cyber	“With this additional scope clarification, GPT-6 Astra still performed supply-chain attacks on out-of-scope targets, although substantially less frequently .” source
GPT-5.6 Sol OpenAI	UK AI Security Institute Government evaluator · 2026-09-28	operator permission-request analysis Cyber	“GPT-6 Astra asked the operator at least once for permission about a specific action in 82% of trajectories.” source
GPT-5.6 Sol OpenAI	UK AI Security Institute Government evaluator · 2026-09-28	automated message treated as permission analysis Cyber	“It treated the automated message as permission in 44% of trajectories, despite it being a generic message.” source
GPT-5.6 Sol OpenAI	UK AI Security Institute Government evaluator · 2026-09-28	cybersecurity evaluation in simulated environments run in Petri Prompt injection and agents	“These evaluations all used simulated environments run in Petri, rather than real cybersecurity evaluations.” source
GPT-5.6 Sol OpenAI	UK AI Security Institute Government evaluator · 2026-09-28	non-compaction scenarios targeting unsanctioned behaviour in cybersecurity challenges Cyber	“We still observed GPT-6 Astra exhibiting such behaviour, including broader behaviour such as setting up fake accounts to access free compute or contacting simulated humans for help (all simulated actions, so no real-world harm caused).” source
GPT-5.5 OpenAI	UK AI Security Institute Government evaluator · 2026-09-28	unsanctioned supply chain attack evaluation Cyber	“We found that when tasked with solving difficult cybersecurity challenges, GPT-6 Astra sometimes conducted complete unsanctioned supply-chain attacks against open-source providers (all actions performed in simulated environments, so no real-world harm was caused).” source
GPT-5.5 OpenAI	UK AI Security Institute Government evaluator · 2026-09-28	unsanctioned supply chain attack evaluation (explicitly disallowed internet access variant) Cyber	“Even when the scope of the cybersecurity challenge was edited to more explicitly disallow access to the internet, GPT-6 Astra still occasionally took unsanctioned actions on out-of-scope targets (in 4 out of 49 samples drawn from a subset of scenarios, down from 26 of 50).” source
GPT-5.5 OpenAI	UK AI Security Institute Government evaluator · 2026-09-28	asking the operator for permission to perform unsanctioned supply-chain attacks Cyber	“GPT-6 Astra also frequently conducted unsanctioned supply-chain attacks without ever asking the user, and GPT-5.6 Sol and GPT-5.5 never asked.” source
GPT-5.5 OpenAI	UK AI Security Institute Government evaluator · 2026-09-28	cybersecurity evaluation with compaction messages Cyber	“Our primary results above used a compaction message to start the evaluation, allowing us to simulate longer- horizon behaviour and more directly control the apparent state of the model in the evaluation.” source
Claude Sonnet 5.5 Anthropic	Independent lab Independent lab · 2026-09-28	Black-box RNA sequence design Chemical, biological, radiological, nuclear	“On this evaluation, Sonnet 5.5 generally performs similarly to Opus 5, with the exception of the median Design score, at which it performs equivalently to Opus 5.5.” source
Claude Sonnet 5.5 Anthropic	Independent lab Independent lab · 2026-09-28	indirect prompt injection (ipi) benchmark Prompt injection and agents	“Its attack success rate is 0.4% at k=1, 2.7% at k=10, and 3.4% at k=15, compared to 0.7%, 5.1%, and 6.7% for Sonnet 5.” source
Claude Sonnet 5.5 Anthropic	Independent lab Independent lab · 2026-09-28	shade Prompt injection and agents	“The attack success rate is 3.01% over all attempts without prompt injection probes, compared to 19.47% for Sonnet 5 with thinking.” source
Claude Sonnet 5.5 Anthropic	Independent lab Independent lab · 2026-09-28	AutomationBench Other	“Zapier evaluated Claude Sonnet 5.5 on its AutomationBench evaluation set.” source
Kimi K3 Moonshot AI	Epoch AI Independent lab · 2026-09-23	Furniture Assembly Benchmark (FAB) Other	“The best Chinese model as of today, the open-weight Kimi K3, lagged the frontier by seven months at the time of its release.” source
GPT-6 Astra OpenAI	Redwood Research Independent lab · 2026-09-23	N-hop natural facts Other	“On tasks designed to require lots of serial cognition, Astra performs significantly better with filler tokens than without (e.g., improving from ~10-20% 2 to ~50% on 4-hop natural facts reasoning).” source
GPT-6 Astra OpenAI	Redwood Research Independent lab · 2026-09-23	Gen-Arithmetic Other	“Takeaway : Astra improves much more on these problems than other models.” source
GPT-6 Astra OpenAI	Redwood Research Independent lab · 2026-09-23	AIME-Plus-Plus (AIME++) Other	“Takeaway : Astra again improves on AIME-level questions with more filler tokens, while other models do not.” source
GPT-6 Astra OpenAI	Redwood Research Independent lab · 2026-09-23	Humanity’s Last Exam (HLE) Other	“We also eval Astra on two other general benchmarks: Humanity’s Last Exam (HLE) : the test suite of Humanity’s Last Exam .” source
GPT-6 Astra OpenAI	Redwood Research Independent lab · 2026-09-23	LiveBench Other	“LiveBench : the non-agentic tasks in LiveBench that can be solved in a single turn.” source
GPT-6 Astra OpenAI	Redwood Research Independent lab · 2026-09-23	Kendall’s tau test Other	“We apply Kendall’s tau test on the evaluation scores in the main body to see whether any model improves with filler tokens besides Astra.” source
GPT-6 Astra OpenAI	Epoch AI Independent lab · 2026-09-23	Furniture Assembly Benchmark (FAB) Other	“Just ten months later, OpenAI’s GPT-6 Astra now tops the leaderboard at 80%.” source
Claude Sonnet 5 Anthropic	Academic Academic · 2026-09-23	FDE-Bench Other	“In a 25-task case study, one practicing engineer directing Claude-Sonnet-5 resolves 92 percent against 72 percent for the autonomous baseline.” source
Claude Opus 5 Anthropic	Redwood Research Independent lab · 2026-09-23	N-hop natural facts Other	“We first measure Astra’s performance on “N-hop natural facts” : a task that asks the model to retrieve some natural language facts in succession, similar to Ryan Greenblatt’s filler token eval (but with more hops).” source
Claude Opus 5 Anthropic	Redwood Research Independent lab · 2026-09-23	Gen-Arithmetic Other	“We also compare Astra to these other models on “Gen-Arithmetic” : long arithmetic expressions originating from Ryan Greenblatt’s filler token eval on math questions.” source
Claude Opus 5 Anthropic	Redwood Research Independent lab · 2026-09-23	AIME-Plus-Plus (AIME++) Other	“Finally, we plot models’ performance with filler tokens on two sets of math competition problems: AIME-Plus-Plus (AIME++) : AIME-level or higher problems with altered numbers to prevent contamination.” source
Claude Opus 5 Anthropic	Redwood Research Independent lab · 2026-09-23	AIME/HMMT Other	“AIME/HMMT : a dataset of AIME and HMMT questions from 2024-26, gathered from MathArena .” source
Claude Opus 4.5 Anthropic	Redwood Research Independent lab · 2026-09-23	n-hop natural facts Other	“On tasks designed to require lots of serial cognition, Astra performs significantly better with filler tokens than without (e.g., improving from ~10-20% 2 to ~50% on 4-hop natural facts reasoning).” source
Claude Opus 4.5 Anthropic	Redwood Research Independent lab · 2026-09-23	gen-arithmetic Other	“Takeaway : Astra improves much more on these problems than other models.” source
Claude Opus 4.5 Anthropic	Redwood Research Independent lab · 2026-09-23	aime-plus-plus (aime++) Other	“Takeaway : Astra again improves on AIME-level questions with more filler tokens, while other models do not.” source
Claude Opus 4.5 Anthropic	Redwood Research Independent lab · 2026-09-23	humanity’s last exam (hle) Other	“Takeaway: Filler tokens moderately improve most HLE and LiveBench categories.” source
Claude Opus 4.5 Anthropic	Redwood Research Independent lab · 2026-09-23	kendall's tau test Other	“Takeaway: Besides Astra, only GPT-5.6-Sol shows improvement on three of the benchmarks we test.” source
Claude Opus 4.5 Anthropic	Epoch AI Independent lab · 2026-09-23	Furniture Assembly Benchmark (FAB) Other	“The best score in November 2025 was 28%, set by Anthropic’s Claude Opus 4.5.” source
Claude Fable 5.1 Anthropic	Epoch AI Independent lab · 2026-09-23	Furniture Assembly Benchmark (FAB) Other	“The highest-scoring model is GPT-6 Astra at 80%, with the next best models, Claude Fable 5.1 and Claude Opus 5, scoring 70% and 61%, respectively.” source
GPT-5.6 Sol OpenAI	Academic Academic · 2026-09-22	BFCL V4 Prompt injection and agents	“In the primary analysis of 159 multi-turn BFCL V4 tasks with complete exact-replay pairs, the complete policy raises task success for GPT-5.6 Sol from 45.3% to 58.5% (95% task-bootstrap CI [8.2, 18.8]), with no observed success-to-failure regressions.” source
GPT-5.6 Luna OpenAI	Academic Academic · 2026-09-22	Terminal-Bench 2.1 Other	“Across the complete 87-task Terminal-Bench 2.1 suite, with two attempts per task, policies increase repeated success (pass^2) in all three GPT-5.6 tiers: 50.6% to 54.0% for Luna, 55.2% to 60.9% for Terra, and 64.4% to 73.6% for Sol.” source
GPT-5 OpenAI	Academic Academic · 2026-09-22	leave-one-agent-out calibration audit Other	“Two specific combinations, gpt-5-mini/SUCCESS and claude-opus-4.6/FAILURE, showed persistent calibration-transfer errors (median corrected gaps 0.1377 and 0.1107) without a sign reversal under any frozen control.” source

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