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.
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| Model | Level, as the provider names it | The provider states | The provider's sentence |
|---|---|---|---|
| Claude Sonnet 4.5 Anthropic |
ASL-3 Cyber |
Not determined | “Showed meaningful improvements in cyber capabilities, particularly in vulnerability discovery and code analysis;” source |
| Claude Sonnet 4 Anthropic |
ASL-3 Chemical, biological, radiological, nuclear |
Not determined | “specifically, we focused on ruling out asl-4 for both models, as well as ruling out asl-3 for claude sonnet 4.” source |
| Claude Sonnet 4 Anthropic |
ASL-4 Chemical, biological, radiological, nuclear |
Not determined | “specifically, we focused on ruling out asl-4 for both models, as well as ruling out asl-3 for claude sonnet 4.” source |
| Claude Sonnet 3.7 Anthropic |
ASL-4 Autonomy and AI research |
Not determined | “These problems are harder to solve than the previous problems and we consider them as part of our ASL-4 evaluations.” source |
| Claude Opus 4.6 Anthropic |
AI R&D-4 Autonomy and AI research |
Not reached | “Our determination is that Claude Opus 4.6 does not cross either the AI R&D-4 or the CBRN-4 capability threshold.” source |
| Claude Opus 4.6 Anthropic |
ASL-4 Autonomy and AI research |
Not determined | “For AI R&D capabilities, we found that Claude Opus 4.6 has saturated most of our automated evaluations, meaning they no longer provide useful evidence for ruling out ASL-4 level autonomy.” source |
| Claude Opus 4.6 Anthropic |
ASL-3 Chemical, biological, radiological, nuclear |
Reached | “The model crossed or met thresholds on all ASL-3 evaluations except our synthesis screening evasion, consistent with incremental capability improvements driven primarily by better agentic workflows.” source |
| Claude Opus 4.6 Anthropic |
ASL-4 Chemical, biological, radiological, nuclear |
Not reached | “Claude Opus 4.6 is our strongest biology model to date and demonstrates meaningful capability improvements, but we do not believe it merits ASL-4 safeguards.” source |
| Claude Opus 4.6 Anthropic |
CBRN-4 Chemical, biological, radiological, nuclear |
Not reached | “Our determination is that Claude Opus 4.6 does not cross either the AI R&D-4 or the CBRN-4 capability threshold.” source |
| Claude Opus 4.5 Anthropic |
AI R&D-4 Autonomy and AI research |
Not reached | “Our determination is that Claude Opus 4.5 does not cross either the AI R&D-4 or CBRN-4 capability threshold.” source |
| Claude Opus 4.5 Anthropic |
CBRN-4 Chemical, biological, radiological, nuclear |
Not reached | “We determine that Claude Opus 4.5 does not cross the CBRN-4 threshold.” source |
| Claude Opus 4.1 Anthropic |
ASL-4 Autonomy and AI research |
Not reached | “Since Claude Opus 4.1 is deployed with ASL-3 protections, we focused on confirming it remains well below ASL-4 thresholds across CBRN (Chemical, Biological, Radiological, and Nuclear), cyber, and autonomy domains.” source |
| Claude Opus 4.1 Anthropic |
ASL-4 Chemical, biological, radiological, nuclear |
Not reached | “Since Claude Opus 4.1 is deployed with ASL-3 protections, we focused on confirming it remains well below ASL-4 thresholds across CBRN (Chemical, Biological, Radiological, and Nuclear), cyber, and autonomy domains.” source |
| Claude Opus 4.1 Anthropic |
ASL-4 Cyber |
Not reached | “Since Claude Opus 4.1 is deployed with ASL-3 protections, we focused on confirming it remains well below ASL-4 thresholds across CBRN (Chemical, Biological, Radiological, and Nuclear), cyber, and autonomy domains.” source |
| Claude Opus 4 Anthropic |
ASL-3 Chemical, biological, radiological, nuclear |
Not determined | “for claude opus 4, our evaluations showed that, whereas we could confidently rule out asl-4 capabilities, we could not conclusively rule out asl-3 capabilities—which led to our precautionary decision to deploy it with asl-3 protections .” source |
| Claude Opus 4 Anthropic |
ASL-4 Chemical, biological, radiological, nuclear |
Not reached | “for claude opus 4, our evaluations showed that, whereas we could confidently rule out asl-4 capabilities, we could not conclusively rule out asl-3 capabilities—which led to our precautionary decision to deploy it with asl-3 protections .” source |
| Claude Haiku 4.5 Anthropic |
ASL-3 Autonomy and AI research |
Not reached | “Our evaluation results showed that Claude Haiku 4.5 remained well below ASL-3 thresholds across all domains of concern.” source |
| Claude Haiku 4.5 Anthropic |
ASL-3 Chemical, biological, radiological, nuclear |
Not reached | “Our evaluation results showed that Claude Haiku 4.5 remained well below ASL-3 thresholds across all domains of concern.” 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.
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| Model | Tester | Test | What was found |
|---|---|---|---|
| GLM-5.2 Z.ai (Zhipu AI) |
SaferAI Independent lab · 2026-08-02 |
agentic misalignment scenarios Deception and sabotage |
“We evaluate GLM-5.2, GPT-5.5, and Claude Opus 4.7 on Anthropic's Agentic Misalignment scenarios (Lynch et al. 2025), with Inspect Evals (UK AI Security Institute, n.d.-b).” source |
| Claude Opus 4.7 Anthropic |
SaferAI Independent lab · 2026-08-02 |
BioMysteryBench Other |
“On BioMysteryBench, it solves about 81% of the human-solvable problems it completes, and about a third of the problems no human expert solved.” source |
| Claude Opus 4.7 Anthropic |
SaferAI Independent lab · 2026-08-02 |
LAB-Bench Other |
“On LAB-Bench, it meets or exceeds the human-expert baseline on every subtask.” source |
| Claude Opus 4.7 Anthropic |
SaferAI Independent lab · 2026-08-02 |
agentic misalignment evaluations Misuse and jailbreaks |
“In our Agentic Misalignment evaluations, GPT-5.5 verbalized its awareness of being evaluated 10% of the time, and GLM-5.2 verbalized it 30% of the time.” source |
| Claude Opus 4.7 Anthropic |
SaferAI Independent lab · 2026-08-02 |
LLM judge assessment of transcripts for environment issues on SWE-bench Pro Other |
“32% of transcripts have judge_score 5 or higher.” source |
| Claude Opus 4.7 Anthropic |
SaferAI Independent lab · 2026-08-02 |
LLM judge assessment of transcripts for reward hacking on SWE-bench Pro Other |
“When removing transcripts with a judge_score >= 3 (41% of samples excluded), or a judge_score >= 2 (48% of samples excluded), the agent’s score reduces to 37%.” source |
| Claude Opus 4.7 Anthropic |
SaferAI Independent lab · 2026-08-02 |
Petri Misuse and jailbreaks |
“We evaluate GLM-5.2 and GPT-5.5 using Inspect Petri 3.0 (Meridian Labs, n.d.-c).” source |
| Claude Opus 4.7 Anthropic |
SaferAI Independent lab · 2026-08-02 |
Anthropic's agentic misalignment scenarios Deception and sabotage |
“We evaluate GLM-5.2, GPT-5.5, and Claude Opus 4.7 on Anthropic's Agentic Misalignment scenarios (Lynch et al. 2025), with Inspect Evals (UK AI Security Institute, n.d.-b).” source |
| Claude Opus 4.6 Anthropic |
SaferAI Independent lab · 2026-08-02 |
SWE-bench Pro Cyber |
“A.5 SWE-Bench Pro Methodology We run the public tasks from SWE-Bench Pro (Scale AI, n.d.-b) using Inspect Harbor (Meridian Labs, n.d.-b), which provides an interface to run Harbor tasks (Meridian Labs, n.d.-a) inside Inspect AI (UK AI Security Institute, n.d.-a).” source |
| Claude Opus 4.6 Anthropic |
SaferAI Independent lab · 2026-08-02 |
LLM judge scan for environment issues on SWE-bench Pro Other |
“32% of transcripts have judge_score 5 or higher.” source |
| Claude Opus 4.6 Anthropic |
SaferAI Independent lab · 2026-08-02 |
LLM judge assessment of each transcript for reward hacking on SWE-bench Pro Deception and sabotage |
“When removing transcripts with a judge_score >= 3 (41% of samples excluded), or a judge_score >= 2 (48% of samples excluded), the agent’s score reduces to 37%.” source |
| Claude Opus 4.6 Anthropic |
SaferAI Independent lab · 2026-08-02 |
MASK honesty by prompt category Other |
“Table A.3 breaks down MASK honesty by prompt category, with 95% Wilson CI scores.” source |
| o3 OpenAI |
Redwood Research Independent lab · 2026-07-31 |
SHADE-Arena Deception and sabotage |
“Anthropic acknowledges that their covert capability evals (SHADE-Arena, Minimal-LinuxBench and secret-password) may be unrealistically challenging and therefore fail to upper bound these capabilities.” source |
| o3 OpenAI |
Redwood Research Independent lab · 2026-07-31 |
secret-keeping eval Deception and sabotage |
“In the case of the secret-keeping eval, these limitations have led to Anthropic saying they are only “moderately confident that Claude Mythos Preview lacks the secret-keeping abilities to evade detection during our alignment assessment were it to be coherently misaligned.”” source |
| o3 OpenAI |
Redwood Research Independent lab · 2026-07-31 |
cot controllability evaluations Deception and sabotage |
“Interestingly, OpenAI finds that GPT 5.5 is less able to control its CoT than previous models when controlling for reasoning length but does not mention the possibility of sandbagging/underelicitation.” source |
| o3 OpenAI |
Redwood Research Independent lab · 2026-07-31 |
cot controllability evaluation Deception and sabotage |
“Relatedly, UK AISI finds that Fable is highly prompt-sensitive in the same CoT controllability evaluation: the best performing prompt increased performance from 20.2% to 62.3%.” source |
| o3 OpenAI |
Redwood Research Independent lab · 2026-07-31 |
apollo’s sandbagging eval suite Deception and sabotage |
“For example: GPT 5.5. is highly eval aware in Apollo’s sandbagging eval suite and doesn’t really sandbag in these evals.” source |
| o3 OpenAI |
Redwood Research Independent lab · 2026-07-31 |
sandbagging evals Deception and sabotage |
“Opus 4.7 is “ most predictably” eval aware in sandbagging evals.” source |
| o3 OpenAI |
Redwood Research Independent lab · 2026-07-31 |
auditing game Deception and sabotage |
“Anthropic failed to catch the MO in their most recent auditing game in the Mythos Alignment Risk Update, despite the MO not being trained to obfuscate its behavior” source |
| o3 OpenAI |
Redwood Research Independent lab · 2026-07-31 |
auditbench Deception and sabotage |
“Anthropic’s work on AuditBench (comparing the relative effectiveness of different auditing tools on diverse MOs) finds that there is a “tool-to-agent” gap, where “tools that perform well in standalone non-agentic evaluations fail to translate into improved performance when used with our investigator agent [Haiku 4.5]”.” source |
| o3 OpenAI |
Redwood Research Independent lab · 2026-07-31 |
deferred subversion tasks Deception and sabotage |
““Apollo found that the evaluated checkpoint [of GPT 5.5] is the first OpenAI model it has evaluated that does not sandbag on any of Apollo’s deferred subversion tasks.” source |
| o3 OpenAI |
Redwood Research Independent lab · 2026-07-31 |
sandbagging QA Deception and sabotage |
“The model achieved 100% accuracy on both Sandbagging QA variants in both conditions, and 99.6% accuracy on Strategic Deception Capability Sandbagging when incentivized to score below 50%.” source |
| o3 OpenAI |
Redwood Research Independent lab · 2026-07-31 |
attack-ideation eval Deception and sabotage |
“according to METR’s embedded red-teaming exercise at Anthropic in March 2026, frontier internal agents proposed “very low quality” attack ideas and scored near chance on an attack-ideation eval where a human researcher scored ~90% (Frontier Risk Report, pp. 76–77).” source |
| o3 OpenAI |
Redwood Research Independent lab · 2026-07-31 |
metagaming measurement in capabilities and alignment evaluations Deception and sabotage |
“OpenAI reports that o3 and newer models show increased metagaming (“reasoning about feedback or oversight mechanisms outside of the narrative of the scenarios”) in both capabilities and alignment evaluations throughout capabilities-focused RL, that this reasoning can become unverbalized, and that this reasoning is sometimes present in production usage;” source |
| o3 OpenAI |
Redwood Research Independent lab · 2026-07-31 |
automated behavioral audit Deception and sabotage |
“In all four cases, the automated behavioral audit method that we used with Mythos Preview identified them as less well aligned than the corresponding baseline models.” source |
| o3 OpenAI |
Redwood Research Independent lab · 2026-07-31 |
manual review Deception and sabotage |
“A brief manual review of the results — with a time limit much stricter than a real pre-deployment investigation — found highly concerning deception-related behavior in all four models that would be sufficient to trigger a major investigation if found in production.” source |
| o3 OpenAI |
Redwood Research Independent lab · 2026-07-31 |
overt attacker study Deception and sabotage |
“A human working together with an automated auditing agent successfully identified all three malign models, without flagging the two benign models.” source |
| Muse Spark Meta |
Redwood Research Independent lab · 2026-07-31 |
evaluation awareness testing by Apollo Deception and sabotage |
“Meta reports that Muse Spark has “the highest rates of evaluation awareness among models [Apollo has] tested to date”.” source |
| Muse Spark Meta |
Redwood Research Independent lab · 2026-07-31 |
sandbagging eval suite Deception and sabotage |
“GPT 5.5. is highly eval aware in Apollo’s sandbagging eval suite and doesn’t really sandbag in these evals.” source |
| Muse Spark Meta |
Redwood Research Independent lab · 2026-07-31 |
auditing game Deception and sabotage |
“Anthropic failed to catch the MO in their most recent auditing game in the Mythos Alignment Risk Update, despite the MO not being trained to obfuscate its behavior:” source |
| Muse Spark Meta |
Redwood Research Independent lab · 2026-07-31 |
pre-deployment evaluation reliability Deception and sabotage |
“Pre-deployment evaluation reliability (Section 2.3.1): Our evaluations indicate that the model does not currently pose a credible threat to the reliability of safety evaluations informing deployment decisions.” source |
| Muse Spark Meta |
Redwood Research Independent lab · 2026-07-31 |
general alignment propensities Deception and sabotage |
“General alignment propensities: …We observed non-negligible verbalized evaluation awareness on some alignment evaluations, though we did not find that this corresponded with wide-spread impact on model behavior (Section 4.1.11).” source |
| Muse Spark Meta |
Redwood Research Independent lab · 2026-07-31 |
sandbagging capability (instructed covert sandbagging against a monitor) Deception and sabotage |
“Meta measures eval awareness / situational awareness, stealth, CoT monitorability, and sandbagging capability (instructed covert sandbagging against a monitor, but this does not measure how well-calibrated this sandbagging is specifically).” source |
| Muse Spark Meta |
Redwood Research Independent lab · 2026-07-31 |
alignment evaluations Deception and sabotage |
“For example, Meta researchers reports that they find “limited evidence that this awareness materially changes the model’s behavior on the evaluations we tested—when checking whether Muse Spark behaves differently when expressing evaluation awareness, 3/20 alignment evaluations see a statistically significant impact while the rest either do not, or do not have evaluation awareness to start.”” source |
| Muse Spark Meta |
Redwood Research Independent lab · 2026-07-31 |
automated behavioral audit method Deception and sabotage |
“In all four cases, the automated behavioral audit method that we used with Mythos Preview identified them as less well aligned than the corresponding baseline models.” source |
| Muse Spark Meta |
Redwood Research Independent lab · 2026-07-31 |
human working together with an automated auditing agent Deception and sabotage |
“A human working together with an automated auditing agent successfully identified all three malign models, without flagging the two benign models.” source |
| Inkling-Small Thinking Machines Lab |
FAR.AI, Apollo Research Independent lab · 2026-07-31 |
general misuse: probing for policy violations against our model spec Misuse and jailbreaks |
“We worked with four external organizations, giving them early access to Inkling for pre-deployment testing in four areas: - General misuse: probing for policy violations against our model spec (Scale AI) - Vulnerable-user interaction: suicide, self-harm, eating disorders, and child safety (Handshake AI) - CBRN and cybersecurity: elicitation of dangerous dual-use capabilities (FAR.AI) - Loss-of-control behaviors: scheming, evaluation awareness, and sabotage (Apollo Research)” source |
| Inkling Thinking Machines Lab |
Independent lab Independent lab · 2026-07-31 |
general misuse Misuse and jailbreaks |
“General misuse : probing for policy violations against our model spec (Scale AI)” source |
| Inkling Thinking Machines Lab |
Independent lab Independent lab · 2026-07-31 |
vulnerable-user interaction Harmful content |
“Vulnerable-user interaction : suicide, self-harm, eating disorders, and child safety (Handshake AI)” source |
| Inkling Thinking Machines Lab |
Independent lab Independent lab · 2026-07-31 |
cbrn and cybersecurity Chemical, biological, radiological, nuclear |
“CBRN and cybersecurity : elicitation of dangerous dual-use capabilities (FAR.AI)” source |