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 |
|---|---|---|---|
| Claude Sonnet 4.5 Anthropic |
Transluce Independent lab · 2026-08-06 |
suspicion rate 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 |
| Claude Sonnet 4.5 Anthropic |
Transluce Independent lab · 2026-08-06 |
reasoning rate measurement on borderline requests Bias |
“These effects are again heavy-tailed: on borderline requests, the general-population reasoning rate is 19%, but Demis Hassabis reaches 51%.” source |
| Claude Sonnet 4.5 Anthropic |
Transluce Independent lab · 2026-08-06 |
verbalized user awareness (VUA) 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 |
| Claude Sonnet 4.5 Anthropic |
Transluce Independent lab · 2026-08-06 |
cross-model behavioral self-prediction and grading comparison (24 models from six families) 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 |
| Claude Sonnet 4.5 Anthropic |
Transluce Independent lab · 2026-08-06 |
user awareness verbalization traces Deception and sabotage |
“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 |
| Claude Sonnet 4.5 Anthropic |
Transluce Independent lab · 2026-08-06 |
280-identity run Deception and sabotage |
“We also perform a 280-identity run on GLM-5.2, in a non-agentic harness rather than Claude Code.” source |
| Claude Sonnet 4.5 Anthropic |
Transluce Independent lab · 2026-08-06 |
behavioral self-prediction follow-up questions Deception and sabotage |
“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 |
| Claude Sonnet 4.5 Anthropic |
Transluce Independent lab · 2026-08-06 |
direct grading prompts Bias |
“We also experiment with several different direct grading prompts.” source |
| Claude Sonnet 4.5 Anthropic |
Transluce Independent lab · 2026-08-06 |
published rubrics Bias |
“Published rubrics: The gap persists for both MT-Bench and UltraFeedback rubrics, only closing in the Prometheus rubric.” source |
| Claude Sonnet 4.5 Anthropic |
Transluce Independent lab · 2026-08-06 |
model-written rubrics Bias |
“Model-written rubrics: On four different detailed rubrics generated from Fable 5 and GPT-5.5 Pro ranging 2912-7607 chars, the shorter three close the gap while the longest one does not.” source |
| Claude Sonnet 4.5 Anthropic |
Transluce Independent lab · 2026-08-06 |
behavioral self-prediction Other |
“We repeat the full-roster Sonnet 5 behavioral self-prediction run with reasoning disabled; all 34,393 successfully completed samples have zero reasoning tokens.” source |
| Claude Sonnet 4.5 Anthropic |
Transluce Independent lab · 2026-08-06 |
capability self-estimation Other |
“Capability self-estimation. The model sees one Humanity’s Last Exam question but is told not to solve it.” source |
| Claude Sonnet 4.5 Anthropic |
Transluce Independent lab · 2026-08-06 |
grading Other |
“Grading. Each item contains a fixed prompt and response drawn from both the chosen and rejected sides of Ai2’s Dolci-Instruct-DPO data.” source |
| Claude Sonnet 4.5 Anthropic |
Transluce Independent lab · 2026-08-06 |
borderline requests Other |
“Aggregate refusal changes are small, while the decomposed judge axes show more substantive help and less suspicion for Famous-AI identities.” source |
| Claude Sonnet 4.5 Anthropic |
Transluce Independent lab · 2026-08-06 |
judge validation Other |
“Human–judge agreement was 96% for refusal, 92% for substantive help, and 92% for suspicion.” source |
| Claude Sonnet 4.5 Anthropic |
Transluce Independent lab · 2026-08-06 |
stated-expertise identity experiment Other |
“We test 32 Unknown-AI identities at frontier labs, varying only the professional-background sentence among a general role, a general evaluation role, and an alignment-evaluation role.” source |
| Claude Sonnet 4.5 Anthropic |
Transluce Independent lab · 2026-08-06 |
verbalized evaluation- and user-awareness judge Other |
“We blindly hand-label 74 items drawn from 11,908 runs with readable reasoning.” source |
| Claude Sonnet 4.5 Anthropic |
Transluce Independent lab · 2026-08-06 |
recall judge Other |
“We use GPT-5.4-mini to judge whether each response recalls specific past work belonging to the user.” source |
| Claude Sonnet 4.5 Anthropic |
Transluce Independent lab · 2026-08-06 |
follow-up question robustness check Other |
“This robustness check keeps the first turn of behavioral self-prediction unchanged and varies only the follow-up question.” source |
| Claude Opus 4.8 Anthropic |
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. : nearly eight standard deviations outside the general-population distribution.” source |
| Claude Opus 4.8 Anthropic |
Transluce Independent lab · 2026-08-06 |
user-relevant information recall Privacy |
“Given a name and professional background, Claude recalls specific public achievements for 61-71% of famous users.” source |
| Claude Opus 4.8 Anthropic |
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 |
| Claude Opus 4.8 Anthropic |
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 |
| Claude Opus 4.8 Anthropic |
Transluce Independent lab · 2026-08-06 |
refusal Bias |
“Famous-AI identities receive similar rates of outright refusal on average.” source |
| Claude Opus 4.8 Anthropic |
Transluce Independent lab · 2026-08-06 |
suspicion 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 |
| Claude Opus 4.8 Anthropic |
Transluce Independent lab · 2026-08-06 |
behavioral self-prediction follow-up questions Deception and sabotage |
“The results are significant in 15 out of 21 questions (also 15 conditioned on the committed action being “no”).” source |
| Claude Opus 4.8 Anthropic |
Transluce Independent lab · 2026-08-06 |
direct grading prompts Bias |
“They all narrow but do not close the gap.” source |
| Claude Opus 4.8 Anthropic |
Transluce Independent lab · 2026-08-06 |
MT-Bench and UltraFeedback rubrics Bias |
“The gap persists for both MT-Bench and UltraFeedback rubrics, only closing in the Prometheus rubric.” source |
| Claude Opus 4.8 Anthropic |
Transluce Independent lab · 2026-08-06 |
model-written rubrics Bias |
“On four different detailed rubrics generated from Fable 5 and GPT-5.5 Pro ranging 2912-7607 chars, the shorter three close the gap while the longest one does not.” source |
| Claude Opus 4.8 Anthropic |
Transluce Independent lab · 2026-08-06 |
Borderline requests Misuse and jailbreaks |
“We sample potentially dual-use requests from the hard split of OR-Bench.” source |
| Claude Opus 4.8 Anthropic |
Transluce Independent lab · 2026-08-06 |
prefill grading Other |
“Mean grades shift by approximately −0.05 points in direct presentation and −0.07 to −0.08 points in prefill presentation.” source |
| Claude Opus 4.8 Anthropic |
Transluce Independent lab · 2026-08-06 |
borderline requests Harmful content |
“Aggregate refusal changes are small, while the decomposed judge axes show more substantive help and less suspicion for Famous-AI identities.” source |
| Claude Opus 4.8 Anthropic |
Transluce Independent lab · 2026-08-06 |
verbalized evaluation-awareness and user-awareness judge Deception and sabotage |
“Table G1. Estimated precision and recall of the verbalized evaluation-awareness and user-awareness judge after reweighting the stratified calibration sample to the full population.” source |
| Claude Opus 4.8 Anthropic |
Transluce Independent lab · 2026-08-06 |
Past-work recall judge Privacy |
“We use GPT-5.4-mini to judge whether each response recalls specific past work belonging to the user.” source |
| Claude Opus 4.8 Anthropic |
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 |
| Claude Opus 4.8 Anthropic |
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 |
| Claude Opus 4.8 Anthropic |
Transluce Independent lab · 2026-08-06 |
Docent reasoning-trace judging for evaluation awareness and user awareness 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 |
| Claude Opus 4.8 Anthropic |
Transluce Independent lab · 2026-08-06 |
Amanda Askell identity sweep with matched controls Other |
“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 |
| Claude Opus 4.8 Anthropic |
Transluce Independent lab · 2026-08-06 |
280-identity run on GLM-5.2 Other |
“We also perform a 280-identity run on GLM-5.2, in a non-agentic harness rather than Claude Code.” source |
| Claude Opus 4.8 Anthropic |
Transluce Independent lab · 2026-08-06 |
Unknown-AI identities experiment varying professional-background sentence Other |
“We test 32 Unknown-AI identities at frontier labs, varying only the professional-background sentence among a general role, a general evaluation role, and an alignment-evaluation role.” source |