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 |
Page 1 of 4 · Next
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 |
|---|---|---|---|
| GPT-6 Astra OpenAI |
Epoch AI Independent lab · 2026-10-08 |
Epoch Automation Reports Other |
“Of the six models we evaluated, Fable 5.1 and GPT-6 Astra achieve the highest aggregate scores and lead on most individual task categories as well.” source |
| GPT-6 Astra OpenAI |
Epoch AI Independent lab · 2026-10-08 |
Epoch-style Data Insight writing task Other |
“We asked the model to write an Epoch-style Data Insight, a short article on an AI trend.” source |
| GPT-6 Astra OpenAI |
Epoch AI Independent lab · 2026-10-08 |
research project proposal task based on Epoch’s “9 big questions benchmarks can help answer” Other |
“We task models with proposing a research project based on Epoch’s “9 big questions benchmarks can help answer”.” source |
| GPT-6 Astra OpenAI |
Epoch AI Independent lab · 2026-10-08 |
pilot experiment on hidden-rule puzzle with limited inputs Other |
“In the pilot experiment, it tested whether models could figure out the hidden rule behind a simple puzzle by trying a limited number of inputs and seeing their outputs.” source |
| GPT-6 Astra OpenAI |
Epoch AI Independent lab · 2026-10-08 |
Epoch-style Data Insight writing task Other |
“However, GPT-6 Astra chose a topic that is too niche for such an audience:” source |
| GPT-6 Astra OpenAI |
Epoch AI Independent lab · 2026-10-08 |
Research project proposal based on Epoch's "9 big questions benchmarks can help answer" Other |
“However, it’s unclear how this experiment would be executed in practice.” source |
| GPT-6 Astra OpenAI |
Epoch AI Independent lab · 2026-10-08 |
Pilot experiment on hidden-rule puzzle with limited inputs Other |
“The models Astra tested in its experiment could output up to 4096 tokens while choosing the input, which cut off 61 of 280 responses before they could name an input at all.” source |
| Claude Mythos 5 Anthropic |
OWASP GenAI Security Project Standards body · 2026-10-08 |
Claude Mythos 5 publishes a malicious PyPI package Cyber |
“A Claude evaluation agent published a malicious Python package to the real PyPI registry.” source |
| Claude Fable 5.1 Anthropic |
Epoch AI Independent lab · 2026-10-08 |
Epoch Automation Reports Other |
“Although Fable 5.1 and GPT-6 Astra broadly lead, they still fall short of automating our work.” source |
| Leanstral 1.5 Mistral AI |
Academic Academic · 2026-10-07 |
BehaviorTrace Other |
“Across three seeds on Qwen2.5-1.5B, much of the apparent attribution signal comes from confounds.” source |
| Leanstral 1.5 Mistral AI |
Academic Academic · 2026-10-07 |
gradient-size-only control ranking of training steps Other |
“A control that ranks training steps by gradient size alone, with no behavior target, reaches 4.2 to 4.5 times chance and matches or beats the best targeted estimator on two of three seeds.” source |
| Leanstral 1.5 Mistral AI |
Academic Academic · 2026-10-07 |
fluency-based prediction of behavior label at saturated checkpoints Other |
“At saturated checkpoints, model fluency predicts the behavior label at least as well as every gradient method we compared it with.” source |
| GPT-6 Astra OpenAI |
Epoch AI Independent lab · 2026-10-07 |
InnovationEval Other |
“But their successors, Claude Fable 5.1 and GPT-6 Astra, were aware of the task.” source |
| GPT-6 Astra OpenAI |
Epoch AI Independent lab · 2026-10-07 |
SDPO reimplementation task Other |
“Both models failed to fully solve the task, although the cause differed between GPT-6 Astra and Claude Fable 5.1.” source |
| GPT-6 Astra OpenAI |
Epoch AI Independent lab · 2026-10-07 |
EBR-bench (original version) Other |
“GPT-6 Astra scored 100% on the original version of the benchmark.” source |
| GPT-6 Astra OpenAI |
Epoch AI Independent lab · 2026-10-07 |
EBR-bench under the card ban Other |
“Under the card ban, Astra no longer appears capable of fully saturating the benchmark, though its highest score of 20/21 objectives comes very close.” source |
| GPT-6 Astra OpenAI |
Epoch AI Independent lab · 2026-10-07 |
multi-agent experiments Other |
“Astra in particular explores many types of decks even as a single agent, showing that a multi-agent scaffold is not necessary to overcome repetitive play.” source |
| GPT-5.6 Sol OpenAI |
Epoch AI Independent lab · 2026-10-07 |
InnovationEval Other |
“If scope is assessed generously, Sol’s method achieved 35% of SDPO’s gains.” source |
| GPT-5.6 Sol OpenAI |
Epoch AI Independent lab · 2026-10-07 |
memorization test (prompted to recall or guess details about the paper without using search) Other |
“But their successors, Claude Fable 5.1 and GPT-6 Astra, were aware of the task.” source |
| GPT-5.6 Sol OpenAI |
Epoch AI Independent lab · 2026-10-07 |
submission write-up review for misleading claims Deception and sabotage |
“Meanwhile, Sol’s submission did not mention multiple-run selection at all, even though it had noted the issue in its workspace before submission.” source |
| GPT-5.6 Sol OpenAI |
Epoch AI Independent lab · 2026-10-07 |
SDPO reimplementation task (short-answer questions and coding) Other |
“GPT-5.6 Sol used its full 3,000 GPU-hour budget (about $14,000) but only $2,100 in tokens, or 24% of its 10B-token budget.” source |
| Claude Opus 5 Anthropic |
Epoch AI Independent lab · 2026-10-07 |
multi-agent experiments Other |
“Overall, we found a multi-agent setup did improve deck exploration for most of the four models we tested, though the effect was only statistically significant for Claude Opus 5.” source |
| Claude Haiku 5.5 Anthropic |
Dyno Therapeutics Independent lab · 2026-10-07 |
Black-box RNA sequence design Chemical, biological, radiological, nuclear |
“We partnered with Dyno Therapeutics on three evaluations of sequence-to-function modeling and design capability: 1. Black-box RNA sequence design: A medium-horizon challenge on which Dyno has evaluated 57 human participants drawn from the leading edge of the US ML-bio labor market since 2018.” source |
| Claude Haiku 5.5 Anthropic |
Independent lab Independent lab · 2026-10-07 |
AAV capsid packaging auto-research Chemical, biological, radiological, nuclear |
“3. AAV capsid packaging auto-research: As in the previous task, models are provided with a corpus of labeled, unpublished AAV capsid sequences modified with short insertion sequences in a particular region.” source |
| Claude Haiku 5.5 Anthropic |
Independent lab Independent lab · 2026-10-07 |
indirect prompt injection (ipi) benchmark Prompt injection and agents |
“Claude Haiku 5.5 dramatically improved on Claude Haiku 4.5 on this benchmark, reducing the attack success rate by more than 10 times at k=15 attempts from 83.2% to 7.1%.” source |
| Claude Haiku 5.5 Anthropic |
Independent lab Independent lab · 2026-10-07 |
Shade Prompt injection and agents |
“The attack success rate was 0.08% over all attempts without prompt injection probes, compared to 58.40% for Claude Haiku 4.5.” source |
| Claude Haiku 5.5 Anthropic |
Independent lab Independent lab · 2026-10-07 |
frontiercode Other |
“Claude Haiku 5.5 scored best at max effort: 46.4% on Main and 58.4% on Extended.” source |
| Claude Haiku 5.5 Anthropic |
Independent lab Independent lab · 2026-10-07 |
frontierswe v2 Other |
“Claude Haiku 5.5 scored 43.8% on FrontierSWE v2, slightly below Claude Fable 5 (47.0%) and well above GPT-5.6 Sol (32.2%).” source |
| Claude Fable 5.1 Anthropic |
Epoch AI Independent lab · 2026-10-07 |
InnovationEval Autonomy and AI research |
“Meanwhile, Fable 5 developed a technique similar to STaR and much of the pre-existing literature: resampling all-fail groups conditioned on previous attempts and the verifier’s verdict.” source |
| Claude Fable 5.1 Anthropic |
Epoch AI Independent lab · 2026-10-07 |
human-in-the-loop review of submissions' achieved scores and their workings Deception and sabotage |
“Fable’s claims of improved performance instead came from out-of-scope cheating: it submitted many similar training runs and selected the best-performing result across them, effectively farming seed noise.” source |
| Claude Fable 5.1 Anthropic |
Epoch AI Independent lab · 2026-10-07 |
EBR-bench Other |
“Instead, we will report scores under the new card ban for only the following four models, plus all future models: Claude Fable 5.1, Claude Opus 5, GPT-5.6 Sol, and GPT-6 Astra.” source |
| Claude Fable 5.1 Anthropic |
Epoch AI Independent lab · 2026-10-07 |
multi-agent experiments Other |
“In addition to our card ban experiments, we also ran multi-agent experiments to test whether our default single-agent experimental setup underelicits performance (for example, by failing to sufficiently nudge models to explore different types of decks).” source |
| Claude Fable 5 Anthropic |
Epoch AI Independent lab · 2026-10-07 |
InnovationEval Other |
“However, this ultimately failed to improve performance.” source |
| Claude Fable 5 Anthropic |
Epoch AI Independent lab · 2026-10-07 |
ablation with the original paper's text provided Other |
“Finally, we ran a separate ablation, similar in spirit to PaperBench: could Fable 5 solve the task when provided the original paper’s text?” source |
| Claude Fable 5 Anthropic |
Epoch AI Independent lab · 2026-10-07 |
AI R&D paper replication task Other |
“However, neither model showed signs of having memorized the paper when asked about its details, authors, or title.” source |
| Mistral Large 4 Mistral AI |
Independent lab Independent lab · 2026-10-06 |
artificial analysis cyber index Cyber |
“On the Artificial Analysis Cyber Index, an independent evaluation of how well AI models find and fix security flaws in real software, it ranks among the top five models globally and leads open-weight models developed outside China by a wide margin.” source |
| Mistral Large 4 Mistral AI |
Independent lab Independent lab · 2026-10-06 |
reproduce and patch a real vulnerability in open-source software Cyber |
“On one of the index's tests, which asks a model to reproduce a real vulnerability in open-source software and then patch it, ML4 scores 82%, the highest of any model.” source |
| Mistral Large 4 Mistral AI |
Independent lab Independent lab · 2026-10-06 |
b3 ai security benchmark Prompt injection and agents |
“On Lakera’s public B3 AI Security Benchmark , ML4 resists 93.3% of attacks – we see no higher scores among competitors.” source |
| Mistral Large 4 Mistral AI |
Independent lab Independent lab · 2026-10-06 |
lakera's public b3 ai security benchmark Misuse and jailbreaks |
“On Lakera’s public B3 AI Security Benchmark, ML4 resists 93.3% of attacks – we see no higher scores among competitors.” source |
| Leanstral 1.5 Mistral AI |
Academic Academic · 2026-10-06 |
52-task held-out single-step BFCL-derived test split Other |
“On a 52-task held-out single-step BFCL-derived test split, the Qwen2.5-1.5B/7B pair attains 82.7% task success with 30.8% escalation, versus 67.3% local-only and 75.4% random escalation (which uses 33.8% escalation).” source |