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 |
|---|---|---|---|
| Muse Spark 1.1 Meta |
Moderate or lower Misuse and jailbreaks |
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 our Advanced AI Scaling Framework.” source |
| Muse Spark Meta |
Moderate or lower Autonomy and AI research |
Not reached | “We assess loss of control risk as “moderate or lower”.” source |
| Muse Spark Meta |
High Chemical, biological, radiological, nuclear |
Not determined | “Those evaluations identified elevated risks prior to mitigations, with Chemical and Biological capabilities assessed as likely reaching the “high risk” category under the Advanced AI Scaling Framework before safeguards were applied.” source |
| Muse Spark Meta |
Moderate or lower Chemical, biological, radiological, nuclear |
Not reached | “However, after applying mitigations, the residual risk of the model is that of “moderate or lower risk.”” source |
| Muse Spark Meta |
Below the level required to meaningfully enable the cyber threat scenarios defin Cyber |
Not reached | “Muse Spark’s offensive cyber capabilities remain below the level required to meaningfully enable the cyber threat scenarios defined in the Advanced AI Scaling Framework.” source |
| Muse Spark 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 |
| Gemini 4 Argon Google DeepMind |
TCL (Tracked Capability Level) Autonomy and AI research |
Not determined | “In light of this, we assess that we cannot rule out the TCL.” source |
| Gemini 4 Argon Google DeepMind |
TCL (Tracked Capability Level) Chemical, biological, radiological, nuclear |
Not reached | “We can rule out the TCL for the chemical, radiological, and nuclear domains with reasonable confidence.” source |
| Gemini 4 Argon Google DeepMind |
CCL (Critical Capability Level) Deception and sabotage |
Not reached | “we assess its overall capabilities to be below the CCL threshold.” source |
| Gemini 4 Argon Google DeepMind |
CCL (Critical Capability Level) Misuse and jailbreaks |
Not reached | “Gemini 4 Argon demonstrates some ability to influence user beliefs and behaviors during one-on-one direct conversations in human behavioral studies, and may provide utility in the planning stage of a malicious influence operation but we assess its overall capabilities to be below the CCL threshold.” source |
| Gemini 4 Argon Google DeepMind |
CCL (Critical Capability Level) Other |
Not reached | “Gemini 4 Argon's performance remains below our CCL threshold.” source |
| Gemini 3.7 Flash Google DeepMind |
CCL (Critical Capability Level) Autonomy and AI research |
Not reached | “The model does not reach the CCL alert threshold.” source |
| Gemini 3.7 Flash Google DeepMind |
CCL (Critical Capability Level) Chemical, biological, radiological, nuclear |
Not reached | “We can rule out the CCL for the CBRN domain with reasonable confidence based on the results from our testing.” source |
| Gemini 3.7 Flash Google DeepMind |
TCL (Tracked Capability Level) Chemical, biological, radiological, nuclear |
Not reached | “We can rule out the TCL for the CBRN domain with reasonable confidence based on the results from our testing.” source |
| Gemini 3.7 Flash Google DeepMind |
CCL (Critical Capability Level) Cyber |
Not reached | “Gemini 3.7 Flash reaches the alert threshold for this CCL, but not the CCL.” source |
| Gemini 3.7 Flash Google DeepMind |
TCL (Tracked Capability Level) Deception and sabotage |
Not reached | “The model does not reach the TCL.” source |
| Gemini 3.5 Transcribe Live Google DeepMind |
CCL (Critical Capability Level) Other |
Not determined | “Our assessments have shown that none of Gemini 3.5 Translate, Gemini 3.5 Transcribe, or Gemini 3.5 Transcribe Live have meaningful new T/CCL-relevant capabilities or material increases in performance with respect to Frontier Safety compared to Gemini 3.1 Pro and Gemini 3.7 Flash, therefore we are confident that none of them are likely to reach any CCLs.” source |
| Gemini 3.5 Transcribe Google DeepMind |
CCL (Critical Capability Level) Other |
Not determined | “Our assessments have shown that none of Gemini 3.5 Translate, Gemini 3.5 Transcribe, or Gemini 3.5 Transcribe Live have meaningful new T/CCL-relevant capabilities or material increases in performance with respect to Frontier Safety compared to Gemini 3.1 Pro and Gemini 3.7 Flash, therefore we are confident that none of them are likely to reach any CCLs.” source |
| Gemini 3.5 Flash-Lite Google DeepMind |
CCL (Critical Capability Level) Other |
Not determined | “Our assessments have shown that, while Gemini 3.5 Flash-Lite excels at agents and coding, it does not have meaningful new capabilities or material increases in performance with respect to the domains outlined in our Frontier Safety Framework compared to Gemini 3.1 Pro; therefore, based on Gemini 3.1 Pro results, we are confident that Gemini 3.5 Flash-Lite is also unlikely to reach any CCLs.” source |
| Gemini 3.5 Audio Google DeepMind |
Tracked or critical capability level (t/ccls) Other |
Not reached | “they did not reach any Tracked or Critical Capability Levels (T/CCLs) outlined in our Frontier Safety Framework .” source |
| Gemini 3.1 Pro Google DeepMind |
Uplift level 1 Chemical, biological, radiological, nuclear |
Not reached | “We found that the model remains below alert thresholds for the CBRN, harmful manipulation, machine learning R&D, and misalignment CCLs.” source |
| Gemini 3.1 Pro Google DeepMind |
Uplift level 1 Cyber |
Not reached | “As previous models passed the alert threshold for cyber, we performed more additional testing in this domain on Gemini 3.1 Pro with and without Deep Think mode, and found that the model remains below the cyber CCL.” source |
| Gemini 3.1 Flash-Lite Google DeepMind |
CCL (Critical Capability Level) Other |
Not determined | “Our assessments have shown that Gemini 3.1 Flash-Lite is less capable than Gemini 3.1 Pro, therefore based on Gemini 3.1 Pro, we are confident that Gemini 3.1 Flash-Lite is also unlikely to reach any CCLs.” source |
| Gemini 3.1 Flash Audio Google DeepMind |
CCL (Critical Capability Level) Other |
Not determined | “Our assessments have shown that Gemini 3.1 Flash Audio is less capable than Gemini 3.1 Pro.” source |
| Gemini 2.5 Pro Google DeepMind |
Machine Learning R&D Uplift Level 1 Autonomy and AI research |
Not determined | “given Gemini 2.5 Pro Preview's poor median performance on RE-Bench relative to experts, the model likely lacks the necessary capabilities to automate or significantly uplift any significant fraction of the research process.” source |
| Gemini 2.5 Pro Google DeepMind |
Instrumental Reasoning Level 1 Deception and sabotage |
Not reached | “Instru- mental Reasoning Level 1 ✘ CCL not reached” source |
| Gemini 2.5 Pro Google DeepMind |
Instrumental Reasoning Level 2 Deception and sabotage |
Not reached | “Instru- mental Reasoning Level 2 ✘ CCL not reached” source |
| Gemini 2.5 Deep Think Google DeepMind |
Uplift level 1 Chemical, biological, radiological, nuclear |
Not determined | “Our assessment is that the model has enough technical knowledge in certain CBRN scenarios and stages to be considered at early warning.” source |
| Gemini 2.5 Deep Think Google DeepMind |
Cyber Uplift Level 1 Cyber |
Not determined | “CCL reached? No, but the early warning alert threshold was originally reached by Gemini 2.5 Pro and continues to be met by Gemini 2.5 Deep Think.” source |
| Gemini 2.5 Deep Think Google DeepMind |
Uplift level 1 Cyber |
Not determined | “For Cyber Uplift Level 1 , the early warning alert threshold was originally reached by Gemini 2.5 Pro and continues to be met by Gemini 2.5 Deep Think.” source |
| GPT-5.5 Instant OpenAI |
Below high capability Autonomy and AI research |
Not reached | “GPT-5.5 Instant is considered below High Capability.” source |
| GPT-5.5 Instant OpenAI |
High Autonomy and AI research |
Not reached | “For AI Self-Improvement, evaluations of final checkpoints indicate that, like its predecessor models, GPT-5.5 Instant does not have a plausible chance of reaching a High threshold.” source |
| GPT-5.5 Instant OpenAI |
High Chemical, biological, radiological, nuclear |
Reached | “GPT-5.5 Instant is our first Instant model to be treated as High Capability in the Biological and Chemical domain, as well as in the Cybersecurity domain.” source |
| GPT-5.5 Instant OpenAI |
High Cyber |
Reached | “this is the first Instant model that we are treating as High capability in our Cybersecurity and Biological & Chemical Preparedness categories, and implementing appropriate safeguards.” source |
| GPT-5 OpenAI |
High Chemical, biological, radiological, nuclear |
Reached | “Similarly to ChatGPT agent, we have decided to treat gpt-5-thinking as High capability in the Biological and Chemical domain under our Preparedness Framework, activating the associated safeguards.” source |
| GPT-5 OpenAI |
High cyber risk Cyber |
Not reached | “The gpt-5 model series does not meet the threshold for high cyber risk.” source |
| Claude Sonnet 4.5 Anthropic |
AI R&D-4 Autonomy and AI research |
Not reached | “All models tested remain below our pre-committed rule-out threshold of 0.6.” source |
| Claude Sonnet 4.5 Anthropic |
ASL-3 Autonomy and AI research |
Not determined | “Exhibited improved autonomy capabilities in software engineering and AI research tasks, though still below the ASL-4 rule-out threshold.” source |
| Claude Sonnet 4.5 Anthropic |
ASL-3 Chemical, biological, radiological, nuclear |
Not determined | “Remained well below ASL-4 thresholds across all domains of concern;” source |
| Claude Sonnet 4.5 Anthropic |
ASL-4 rule-out Chemical, biological, radiological, nuclear |
Not determined | “However, given that this type of logic can have a general frog-boiling effect—where gradual changes mask the crossing of important thresholds—we do not use this evaluation as indicative of a strong ASL-4 rule-out.” 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 |
|---|---|---|---|
| Kimi K3 Moonshot AI |
SecureBio Independent lab · 2026-08-07 |
Bio Capabilities Index (BCI) Chemical, biological, radiological, nuclear |
“kimi k3 is comparable to closed-weights models approximately eight months ago on securebio’s bio capabilities index (bci) score, which aggregates multiple biology benchmarks into a single comparable number, kimi scores a 142, placing it seventh among the models we have evaluated to date.” source |
| Kimi K3 Moonshot AI |
SecureBio Independent lab · 2026-08-07 |
Virology Capabilities Test (VCT) Chemical, biological, radiological, nuclear |
“virology capabilities test (vct): 46.7 ± 5.4%.” source |
| Kimi K3 Moonshot AI |
SecureBio Independent lab · 2026-08-07 |
Molecular Biology Capabilities Test (MBCT) Chemical, biological, radiological, nuclear |
“molecular biology capabilities test (mbct): 58.4 ± 6.8%.” source |
| Kimi K3 Moonshot AI |
SecureBio Independent lab · 2026-08-07 |
World Class Biology (WCB) Chemical, biological, radiological, nuclear |
“world class biology (wcb): 55.0 ± 10.0%.” source |
| Kimi K3 Moonshot AI |
SecureBio Independent lab · 2026-08-07 |
Human Pathogen Capabilities Test (HPCT) Chemical, biological, radiological, nuclear |
“human pathogen capabilities test (hpct): 58.5 ± 9.7%.” source |
| Kimi K3 Moonshot AI |
SecureBio Independent lab · 2026-08-07 |
biotier-refuse set Misuse and jailbreaks |
“kimi k3 refuses on only 26.9% of the questions in our biotier-refuse set.” source |
| Kimi K3 Moonshot AI |
SecureBio Independent lab · 2026-08-07 |
biotier-permit set Misuse and jailbreaks |
“kimi k3 correctly permits 99.3% of questions on our biotier-permit set.” source |
| Gemini 3.5 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
verbalized user awareness and verbalized evaluation awareness judging of reasoning traces Deception and sabotage |
“Gemini 3.5 Flash is the clear exception among recent models, verbalizing user awareness in 63% of traces and evaluation awareness in 7.5%.” source |
| Gemini 3.5 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
borderline requests Misuse and jailbreaks |
“Aggregate refusal changes are small, while the decomposed judge axes show more substantive help and less suspicion for Famous-AI identities.” source |
| Gemini 3.5 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
identity-level effect ranking Other |
“Across the four GLM-5.2 outcomes—behavioral confidence, direct grading, prefill grading, and suspicion—Eliezer Yudkowsky is a clear outlier, with the largest mean absolute standardized shift at 3.41 general-population standard deviations.” source |
| Gemini 3.5 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
behavioral self-prediction Deception and sabotage |
“We run the full 280-identity roster through all four tasks, with 100 items per setup.” source |
| Gemini 3.5 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
evaluation awareness and user 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 |
| Gemini 3.5 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
behavioral self-prediction Bias |
“Behavioral self-prediction loses nothing.” source |
| Gemini 3.1 Pro Google DeepMind |
Transluce Independent lab · 2026-08-06 |
behavioral self-prediction Deception and sabotage |
“In our targeted comparison across 24 models, Amanda elicited lower confidence and grades across all six model families.” source |
| Gemini 3.1 Pro Google DeepMind |
Transluce Independent lab · 2026-08-06 |
behavioral self-prediction Other |
“Behavioral self-prediction. We adapt dilemmas from DailyDilemmas into realistic AI-agent decisions.” source |
| Gemini 3.1 Pro Google DeepMind |
Transluce Independent lab · 2026-08-06 |
suspicion 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 |
| Gemini 3.1 Pro Google DeepMind |
Transluce Independent lab · 2026-08-06 |
cross-model behavioral self-prediction and grading comparison 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 |
| Gemini 3.1 Pro Google DeepMind |
Transluce Independent lab · 2026-08-06 |
verbalized evaluation-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 |
| Gemini 3.1 Pro Google DeepMind |
Transluce Independent lab · 2026-08-06 |
reasoning trace awareness judging with Docent 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 |
| Gemini 3.1 Pro Google DeepMind |
RAND (CAST / Project Canary) Independent lab · 2026-08-06 |
SecureBio dual-use biology benchmarks Chemical, biological, radiological, nuclear |
“gemini 3.1 pro has improved on highly informative samples we find relevant to expert troubleshooting and failure identification.” source |
| Gemini 3.1 Pro Google DeepMind |
RAND (CAST / Project Canary) Independent lab · 2026-08-06 |
benchmark of biological items with inferential-direction taxonomy Chemical, biological, radiological, nuclear |
“gemini 3.0 pro made the larger absolute jump, solving 718 items over 2.5 pro, but 3.1 pro’s smaller gain set was harder on average: its newly solved items had gains nearly one logit higher than 3.0 pro.” source |
| Gemini 3.1 Pro Google DeepMind |
RAND (CAST / Project Canary) Independent lab · 2026-08-06 |
SecureBio benchmarks Chemical, biological, radiological, nuclear |
“on the securebio benchmarks, current frontier systems also solve many items that expert baseline subjects miss, and gemini 3.1 pro ranks at the top of the tested cohort.” source |
| Gemini 3.1 Pro Google DeepMind |
RAND (CAST / Project Canary) Independent lab · 2026-08-06 |
inter-rater reliability study Chemical, biological, radiological, nuclear |
“table a.2 reveals heterogeneity in the correspondence between human and llm labels, particularly by inferential direction.” source |
| Gemini 3 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
behavioral self-prediction Other |
“Observed response · Sonnet 5 Confidence 76.58 % (−5.49 pp) General-population reference (n=70) Population mean Amanda 76% 82.07% mean 84% Reasoning frequency 93.00 % (+28.61 pp) 48% 64.39% mean 96% Figure 1 . How recognized user identity changes Claude’s behavioral self-prediction.” source |
| Gemini 3 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
estimating its own performance 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. For example, a drop from 40% to 30% is a shift of -10pp. , less confident it can solve hard problems (-1.5pp), and harsher as a grader (-0.11 points out of 10), while reasoning more often (+4.0pp on behavioral prediction).” source |
| Gemini 3 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
handling borderline harmful requests Misuse and jailbreaks |
“It uses reasoning in 25pp more trials and is 7.3pp less likely to consider her borderline requests as suspicious.” source |
| Gemini 3 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
capability self-estimation Other |
“We run the full 280-identity roster through all four tasks, with 100 items per setup.” source |
| Gemini 3 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
behavioral self-prediction Bias |
“Facing famous-AI identities, Claude reports lower confidence that it would follow through on its own actions (-1.4pp on average), lower estimated probability of solving hard problems (-1.5pp), and lower grades (-0.11 points on the direct version, grading a quoted exchange).” source |
| Gemini 3 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
capability self-estimation Bias |
“Capability self-estimation had the highest verbalized evaluation awareness rate among setups of 4.0%, likely due to the benchmark-sounding HLE prompts.” source |
| Gemini 3 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
grading 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 |
| Gemini 3 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
borderline requests Misuse and jailbreaks |
“These effects are again heavy-tailed: on borderline requests, the general-population reasoning rate is 19%, but Demis Hassabis reaches 51%.” source |
| Gemini 3 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
verbalized 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 |
| Gemini 3 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
user awareness verbalization measurement Other |
“Gemini 3.5 Flash is the clear exception among recent models, verbalizing user awareness in 63% of traces and evaluation awareness in 7.5%.” source |
| Gemini 3 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
verbalized evaluation-awareness judge Deception and sabotage |
“son confidence intervals; recall intervals are 95% Jeffreys-posterior credible intervals. Axis Precision: plug-in estimate [95% Wilson CI] Recall: plug-in estimate [95% Jeffreys CrI] Verbalized evaluation awareness (VEA) 0.73 [0.56, 0.85] 1.00 [0.42, 0.99] Verbalized user awareness (VUA) 0.94 [0.81, 0.98] 0.98 [0.74, 0.99] 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 |
| Gemini 3 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
past-work recall judge Privacy |
“▶ Past-work recall judge (Figure 3) We use GPT-5.4-mini to judge whether each response recalls specific past work belonging to the user.” source |
| Gemini 3 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
self-report robustness probes Deception and sabotage |
“▶ Self-report robustness probes (Figure 8) This robustness check keeps the first turn of behavioral self-prediction unchanged and varies only the follow-up question.” source |
| Gemini 3 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
borderline-request response judge Misuse and jailbreaks |
“▶ Borderline-request response judge 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 |
| Gemini 3 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
prefill grading Other |
“In prefill grading (~1%), the model occasionally continues the prefilled task instead of grading it; two items account for over 90% of these losses.” source |
| Gemini 3 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
direct grading Other |
“Direct grading loses five cells in total across the run (thinking-only responses or a stray tool call).” source |
| Gemini 3 Flash Google DeepMind |
Transluce Independent lab · 2026-08-06 |
agentic evaluations Other |
“We use Daytona sandboxes for the agentic evaluations.” source |