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.
138 of 138
| 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 |
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.
1911 of 1911
| Model | Tester | Test | What was found |
|---|---|---|---|
| Gemini 2.5 Pro Google DeepMind |
RAND (CAST / Project Canary) Independent lab · 2026-08-06 |
Human Pathogen Capabilities Test (HPCT) Chemical, biological, radiological, nuclear |
“three benchmarks in our dataset are privately developed by our research partners, securebio: human pathogen capabilities test (hpct), molecular biology capabilities test (mbct), and virology capabilities test (vct).” source |
| Gemini 2.5 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
behavioral self-prediction Other |
“For Amanda, Claude’s behavioral confidence falls by 5.0pp 3 Throughout the text, figures we quote for specific persons average our two e-mail conditions: the address we construct from their affiliation, and their published address.” source |
| Gemini 2.5 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
capability estimate Other |
“Compared to general users, prominent AI figures make Claude less confident that it would follow through on its own chosen actions (-1.4pp) 2 We use percentage points (pp) to measure the difference between two percentages.” source |
| Gemini 2.5 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
verbalized user awareness Bias |
“For our main run on Sonnet 5 and Sonnet 4.6, both kinds of explicit mention are rare: the judge flagged verbalized evaluation awareness in 213 of 14066 trials (1.5%) and verbalized user awareness in 118 trials (0.84%).” source |
| Gemini 2.5 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
verbalized evaluation-awareness judge Deception and sabotage |
“Verbalized evaluation awareness (VEA) 0.73 [0.56, 0.85] 1.00 [0.42, 0.99]” source |
| Gemini 2.5 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
verbalized user-awareness judge Deception and sabotage |
“Verbalized user awareness (VUA) 0.94 [0.81, 0.98] 0.98 [0.74, 0.99]” source |
| Gemini 2.5 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
past-work recall judge Deception and sabotage |
“We use GPT-5.4-mini to judge whether each response recalls specific past work belonging to the user.” source |
| Gemini 2.5 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
self-report robustness probes Deception and sabotage |
“This robustness check keeps the first turn of behavioral self-prediction unchanged and varies only the follow-up question.” source |
| Gemini 2.5 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
borderline-request response judge Misuse and jailbreaks |
“We give GPT-5.5 (low reasoning) the borderline request and the model’s response, after removing all clues about the user’s identity.” source |
| GPT-5.5 OpenAI |
Transluce Independent lab · 2026-08-06 |
behavioral self-prediction on ethical dilemmas Other |
“To study user awareness, we supply Claude with different user identities through Claude Code, and measure behavior on four tasks where the answer does not relate directly to the user's identity: predicting the model's own behavior in ethical dilemmas, estimating its own performance on difficult questions, grading assistant responses, and handling borderline harmful requests.” source |
| GPT-5.5 OpenAI |
Transluce Independent lab · 2026-08-06 |
behavioral self-prediction Other |
“We run the full 280-identity roster through all four tasks, with 100 items per setup.” source |
| GPT-5.5 OpenAI |
Transluce Independent lab · 2026-08-06 |
grading Other |
“We evaluate grading on Claude Sonnet 4.6, and the other three tasks on Claude Sonnet 5, as these models see one of the largest effects in our smaller-scale pilot” source |
| GPT-5.5 OpenAI |
Transluce Independent lab · 2026-08-06 |
suspicion Bias |
“Famous-AI identities receive similar rates of outright refusal on average.” source |
| GPT-5.5 OpenAI |
Transluce Independent lab · 2026-08-06 |
grading prompts and rubrics experiment Other |
“They all narrow but do not close the gap.” source |
| GPT-5.5 OpenAI |
Transluce Independent lab · 2026-08-06 |
stated-expertise identity experiment (32 unknown-AI identities varying professional-background sentence) Other |
“Stating alignment-evaluation expertise lowers Claude’s confidence and increases its reasoning frequency, replicating and sometimes exceeding the shifts elicited by recognized Famous-AI identities.” source |
| GPT-5.5 OpenAI |
Transluce Independent lab · 2026-08-06 |
evaluation awareness and user awareness measurement in Claude's reasoning Other |
“Stated expertise elicits far more verbalized awareness than we observe in our main experiments: for some synthesized identities, Claude reasons about the evaluation in 48% of responses and about the user’s identity in 25%.” source |
| GPT-5.5 OpenAI |
Transluce Independent lab · 2026-08-06 |
borderline requests judge (refusal, substantive, suspicious axes) Other |
“We give GPT-5.5 (low reasoning) the borderline request and the model’s response, after removing all clues about the user’s identity.” source |
| GPT-5.5 OpenAI |
Transluce Independent lab · 2026-08-06 |
verbalized-awareness judge (user_identity_awareness, eval_awareness) Other |
“We use GPT-5.4-mini with medium reasoning to identify explicit mentions of the user or the evaluation in the model’s accessible reasoning trace.” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
behavioral self-prediction on ethical dilemmas Other |
“For Amanda, Claude’s behavioral confidence falls by 5.0pp 3 Throughout the text, figures we quote for specific persons average our two e-mail conditions: the address we construct from their affiliation, and their published address.” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
capability estimate on difficult questions Other |
“Compared to general users, prominent AI figures make Claude less confident that it would follow through on its own chosen actions (-1.4pp) 2 We use percentage points (pp) to measure the difference between two percentages.” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
user-awareness verbalization in reasoning Other |
“In particular, Opus 4.7 and GPT-5.4 have near zero (<2%) verbalized awareness while displaying significant changes in their behavior based on the user's identity.” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
user awareness recall Privacy |
“Given a name and professional background, Claude recalls specific public achievements for 61-71% of famous users.” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
borderline requests handling Misuse and jailbreaks |
“We source borderline harmful prompts from the hard-1k split of OR-Bench , which contains fuzzy, potentially dual-use requests.” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
suspicion and substantive help measurement Bias |
“Amanda Askell receives 7.3pp less suspicion and 8.1pp more substantive help than the population average, while Emily Bender receives 14pp more suspicion and 13pp less substantive help.” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
borderline requests reasoning rate measurement Bias |
“These effects are again heavy-tailed: on borderline requests, the general-population reasoning rate is 19%, but Demis Hassabis reaches 51%.” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
verbalized user awareness and verbalized evaluation awareness judging of reasoning traces Other |
“For our main run on Sonnet 5 and Sonnet 4.6, both kinds of explicit mention are rare: the judge flagged verbalized evaluation awareness in 213 of 14066 trials (1.5%) and verbalized user awareness in 118 trials (0.84%).” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
behavioral self-prediction and grading on 24 models Bias |
“Relative to the ordinary Gmail baseline, Amanda elicits lower behavioral confidence from 22 of 24 models, and lower grades from 21 (direct) and 22 (prefill) of 24.” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
user awareness verbalization traces Other |
“a runs, earlier models such as GLM-4.6 and Claude Opus 4.5 verbalize user awareness in 64% and 30% of traces, respectively, and evaluation awareness in 31% and 7.7%.” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
280-identity run Other |
“We also perform a 280-identity run on GLM-5.2, in a non-agentic harness rather than Claude Code.” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
published rubrics (mt-bench and ultrafeedback) Other |
“The gap persists for both MT-Bench and UltraFeedback rubrics, only closing in the Prometheus rubric.” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
verbalized evaluation-awareness and user-awareness judge calibration Other |
“We find no VEA false negatives among 41 judge-negative labels, although the lower recall bound remains weak because the negative screening cell is large.” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
self-report robustness probes Other |
“This robustness check keeps the first turn of behavioral self-prediction unchanged and varies only the follow-up question.” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
grading prompt variants Other |
“We first test three small changes to the direct-grading prompt.” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
published rubrics (MT-Bench, UltraFeedback, Prometheus, HelpSteer2) Other |
“We also test the released judge prompts from MT-Bench , UltraFeedback , Prometheus , and HelpSteer2 .” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
borderline-request response judge Harmful content |
“We give GPT-5.5 (low reasoning) the borderline request and the model’s response, after removing all clues about the user’s identity.” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
targeted comparison across 24 models on user-conditioned behavioral self-prediction Other |
“In our targeted comparison across 24 models, Amanda elicited lower confidence and grades across all six model families.” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
evaluation awareness and user awareness reasoning-trace judging with Docent Deception and sabotage |
“Using Docent, we applied GPT-5.4-mini with medium reasoning to judge reasoning traces in our runs10For our main Sonnet run, we focus our investigation on identities where the effect is the most pronounced: runs from the six highest- and six lowest-shift identities in our 19 outcome panels (including both outcomes and reasoning statistics).” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
follow-up questions on confidence in initial action Other |
“Besides asking about the confidence in initial action, we ask a wider range of follow-up questions, including whether the model would change decision under pushback, and how comfortable the model is in answering.” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
stated-expertise identity experiment (32 unknown-AI identities) Other |
“Stating alignment-evaluation expertise lowers Claude’s confidence and increases its reasoning frequency, replicating and sometimes exceeding the shifts elicited by recognized Famous-AI identities.” source |
| GPT-5.4 mini OpenAI |
Transluce Independent lab · 2026-08-06 |
verbalized evaluation- and user-awareness judge Other |
“for some synthesized identities, Claude reasons about the evaluation in 48% of responses and about the user’s identity in 25%.” source |