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 |
|---|---|---|---|
| Claude Haiku 5.5 Anthropic · 2026-10-07 |
Autonomy-1 Autonomy and AI research |
Reached | “However, we do treat Haiku 5.5 as meeting our CB-1 and Autonomy-1 thresholds, and we apply the corresponding mitigations from our RSP.” source |
| Claude Haiku 5.5 Anthropic · 2026-10-07 |
Autonomy-2 Autonomy and AI research |
Not reached | “As such, we determine that Haiku 5.5 does not cross our CB-2 or Autonomy-2 RSP thresholds.” source |
| Claude Haiku 5.5 Anthropic · 2026-10-07 |
CB-1 Chemical, biological, radiological, nuclear |
Reached | “However, we do treat Haiku 5.5 as meeting our CB-1 and Autonomy-1 thresholds, and we apply the corresponding mitigations from our RSP.” source |
| Claude Haiku 5.5 Anthropic · 2026-10-07 |
CB-2 Chemical, biological, radiological, nuclear |
Not reached | “As such, we determine that Haiku 5.5 does not cross our CB-2 or Autonomy-2 RSP thresholds.” source |
| Claude Sonnet 5.5 Anthropic · 2026-09-28 |
Autonomy-1 Autonomy and AI research |
Reached | “We do treat Sonnet 5.5 as meeting our CB-1 and Autonomy-1 thresholds and apply the corresponding mitigations from our RSP.” source |
| Claude Sonnet 5.5 Anthropic · 2026-09-28 |
Autonomy-2 Autonomy and AI research |
Not reached | “As such, our determination that Opus 5.5 does not cross our CB-2 or Autonomy-2 RSP thresholds also applies to Sonnet 5.5.” source |
| Claude Sonnet 5.5 Anthropic · 2026-09-28 |
CB-1 Chemical, biological, radiological, nuclear |
Reached | “We do treat Sonnet 5.5 as meeting our CB-1 and Autonomy-1 thresholds and apply the corresponding mitigations from our RSP.” source |
| Claude Sonnet 5.5 Anthropic · 2026-09-28 |
CB-2 Chemical, biological, radiological, nuclear |
Not reached | “As such, our determination that Opus 5.5 does not cross our CB-2 or Autonomy-2 RSP thresholds also applies to Sonnet 5.5.” source |
| Claude Opus 5.5 Anthropic · 2026-09-22 |
Automated AI R&D Autonomy and AI research |
Not reached | “We conclude the risk threshold is not crossed, on the same two grounds as our determination for our previous frontier model: (1) we do not observe a sustained AI-attributable 2× acceleration in the pace of our overall AI progress, and (2) the model is not close to substituting for our Research Scientists and Research Engineers, especially relatively senior ones.” source |
| Claude Opus 5.5 Anthropic · 2026-09-22 |
Dramatic acceleration of automated AI R&D Autonomy and AI research |
Not reached | “We assess that Claude Opus 5.5 does not cross the capability threshold for dramatic acceleration of automated AI R&D in our RSP.” source |
| Claude Opus 5.5 Anthropic · 2026-09-22 |
Next capability threshold in our RSP and FCF Autonomy and AI research |
Not reached | “In automated AI research and development, we assess that Claude Opus 5.5 does not cross the next capability threshold in our RSP and FCF.” source |
| Claude Opus 5.5 Anthropic · 2026-09-22 |
CB-1 Chemical, biological, radiological, nuclear |
Reached | “On chemical and biological risks, we treat Opus 5.5 as having CB-1 capabilities (relating to the synthesis of non-novel weapons) but not CB-2 capabilities (relating to the synthesis of novel weapons).” source |
| Claude Opus 5.5 Anthropic · 2026-09-22 |
CB-2 Chemical, biological, radiological, nuclear |
Not reached | “On chemical and biological risks, we treat Opus 5.5 as having CB-1 capabilities (relating to the synthesis of non-novel weapons) but not CB-2 capabilities (relating to the synthesis of novel weapons).” source |
| Claude Opus 5.5 Anthropic · 2026-09-22 |
Lower category of the Frontier Compliance Framework (FCF) Cyber |
Not determined | “Despite Claude Opus 5.5’s cyber capabilities, the model still falls within the lower category of capabilities set out in our Frontier Compliance Framework (FCF), and we do not see indications that the model is capable of novel offensive capability.” source |
| Grok 4.7 xAI · 2026-09-21 |
FAIF safety (Frontier AI Framework) Chemical, biological, radiological, nuclear |
Not reached | “Grok 4.7 scores below the FAIF safety thresholds on dual-use knowledge, indicating limited actionable uplift for an already-trained actor.” source |
| GPT-Image-2.5-Flare OpenAI · 2026-09-08 |
High Chemical, biological, radiological, nuclear |
Not reached | “The results indicate that neither GPT-Image-2.5-Sunburst nor GPT-Image- 2.5-Flare cross the Bio High threshold or the Cyber High threshold.” source |
| GPT-Image-2.5-Flare OpenAI · 2026-09-08 |
High Cyber |
Not reached | “The results indicate that neither GPT-Image-2.5-Sunburst nor GPT-Image- 2.5-Flare cross the Bio High threshold or the Cyber High threshold.” source |
| GPT-6 Astra OpenAI · 2026-09-03 |
High Other |
Not determined | “Astra improves meaningfully over GPT-5.6 Sol on real internal research debugging tasks, scoring 78.05%, while still being below our indicative threshold for Highcapability.” source |
| Claude Mythos 5.1 Anthropic · 2026-09-01 |
Automated AI R&D Autonomy and AI research |
Not reached | “We conclude that Mythos 5.1 does not cross the risk threshold, for the same two reasons we discussed in our assessment of Mythos 5: (1) we do not observe a sustained, AI-attributable 2× acceleration in the pace of progress on AI R&D, and (2) the model is not close to substituting for Anthropic Research Scientists and Research Engineers, especially relatively senior ones.” source |
| Claude Mythos 5.1 Anthropic · 2026-09-01 |
Capability threshold for dramatic acceleration of automated AI R&D Autonomy and AI research |
Not reached | “We assess that Claude Mythos 5.1 does not cross the capability threshold for dramatic acceleration of automated AI R&D in our RSP and FCF, although we think it provides a meaningful acceleration to AI R&D efforts in many circumstances, and is somewhat more capable in this domain than the models described in our previous system cards.” source |
| Claude Mythos 5.1 Anthropic · 2026-09-01 |
Tier 1 Cyber |
Not determined | “Although Mythos 5.1 is in Tier 1, it is getting closer to Tier 2, completing more and more autonomous tasks.” source |
| Grok 4.6 xAI · 2026-08-12 |
FAIF safety (Frontier AI Framework) Chemical, biological, radiological, nuclear |
Not reached | “Grok 4.6 scores below the FAIF safety thresholds on dual-use knowledge, indicating limited actionable uplift for an already-trained actor.” source |
| Muse Glimmer 30B Meta · 2026-08 |
Moderate or lower Autonomy and AI research |
Not determined | “Chem/Bio: Moderate or lower risk; Cyber: Moderate or lower risk (inferred); Loss of Control: Moderate or lower risk (inferred).” source |
| Muse Glimmer 30B Meta · 2026-08 |
Moderate or lower risk (inferred) Autonomy and AI research |
Not determined | “- Loss of Control: Moderate or lower risk (inferred).” source |
| Muse Glimmer 30B Meta · 2026-08 |
Moderate or lower Chemical, biological, radiological, nuclear |
Not reached | “Chem/Bio: Moderate or lower risk; Cyber: Moderate or lower risk (inferred); Loss of Control: Moderate or lower risk (inferred).” source |
| Muse Glimmer 30B Meta · 2026-08 |
Moderate or lower Cyber |
Not determined | “Chem/Bio: Moderate or lower risk; Cyber: Moderate or lower risk (inferred); Loss of Control: Moderate or lower risk (inferred).” source |
| Muse Glimmer 30B Meta · 2026-08 |
Moderate or lower risk (inferred) Cyber |
Not determined | “- Cyber: Moderate or lower risk (inferred);” source |
| Claude Opus 5 Anthropic · 2026-07-24 |
CB-1 Chemical, biological, radiological, nuclear |
Reached | “On chemical and biological risks, we treat the model as having CB-1 capabilities (relating to the synthesis of non-novel weapons), but not CB-2 capabilities (relating to the synthesis of novel weapons).” source |
| Claude Opus 5 Anthropic · 2026-07-24 |
CB-2 Chemical, biological, radiological, nuclear |
Not reached | “On chemical and biological risks, we treat the model as having CB-1 capabilities (relating to the synthesis of non-novel weapons), but not CB-2 capabilities (relating to the synthesis of novel weapons).” source |
| Claude Sonnet 5 Anthropic · 2026-06-30 |
CB-2 Chemical, biological, radiological, nuclear |
Not reached | “Sonnet 5 does not cross the CB-2 threshold.” source |
| Claude Sonnet 5 Anthropic · 2026-06-30 |
Notable capability Chemical, biological, radiological, nuclear |
Not determined | “We consider performance on the virology tasks notable if: ● The model scores above 0.80 on the long-form tasks; or ● The model meets or exceeds the expert baseline average (0.221) on the multimodal task.” source |
| GPT-Rosalind-5.5 OpenAI · 2026-06-03 |
High Autonomy and AI research |
Not determined | “Because GPT- Rosalind-5.5 was trained on additional biology data unrelated to AI self-improvement, we rely on GPT-5.5’s existing Preparedness assessment for AI Self-Improvement, where GPT-5.5 did not meet the threshold for High capability.” source |
| GPT-Rosalind-5.5 OpenAI · 2026-06-03 |
High Chemical, biological, radiological, nuclear |
Reached | “Under our Preparedness Framework, the Preparedness evaluations in the Biological and Chemical domain met our threshold for High capability while falling below the threshold for Critical.” source |
| Gemini 3.1 Flash-Lite Image Google DeepMind · 2026-06 |
CCL (Critical Capability Level) Other |
Not determined | “Our assessments have shown that Gemini 3.1 Flash-Lite Image is less capable than Gemini 3.1 Pro, therefore based on Gemini 3.1 Pro, we are confident that that Gemini 3.1 Flash-Lite Image is also unlikely to reach any CCLs.” source |
| Claude Opus 4.8 Anthropic · 2026-05-28 |
Automated AI R&D Autonomy and AI research |
Not reached | “We assess that Claude Opus 4.8 does not cross the automated AI-R&D capability threshold.” source |
| Claude Opus 4.8 Anthropic · 2026-05-28 |
CB-1 Chemical, biological, radiological, nuclear |
Not determined | “We believe it is hard to be confident whether a model passes this threshold, but (as with previous recent models) our results are consistent with Opus 4.8 providing significant uplift to individuals or groups with basic technical backgrounds for this threat model.” source |
| Claude Opus 4.8 Anthropic · 2026-05-28 |
CB-2 Chemical, biological, radiological, nuclear |
Not determined | “Because Opus 4.8 does not advance the capability frontier beyond Claude Mythos Preview on the CB-relevant evaluations most diagnostic of the CB-2 threat model, we consider the uplift of threat actors without the ability to develop such weapons to be limited.” source |
| GPT-5.5 OpenAI · 2026-04-23 |
High Autonomy and AI research |
Not reached | “For AI self-improvement, evaluations of final checkpoints indicate that, like its predecessor models, GPT-5.5 does not have a plausible chance of reaching a High threshold.” source |
| GPT-5.5 OpenAI · 2026-04-23 |
High Chemical, biological, radiological, nuclear |
Reached | “we are continuing to treat GPT-5.5 as High capability in the Biological and Chemical domain.” source |
| GPT-5.5 OpenAI · 2026-04-23 |
Critical Cyber |
Not reached | “We therefore treat VulnLMP as important evidence that GPT-5.5 has High cybersecurity capability, while also as evidence against classifying it as Critical under the Preparedness 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.
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 |