ConvergenceFrontier models lead by 0.05 pts battery-wide average: open-weight 5.36 vs frontier 5.41
Domain splitFrontier leads on 3 of 7 behavioral domains ahead only on Integrity & Ethics, Reasoning & Adaptation, Metacognition; open-weight leads the rest, widest on Autonomy & Will (0.29 pts)
Versions3 of 7 model lines score lower than their first version largest gain GPT +1.91 · steepest decline DeepSeek −1.73
27 models · 59 tests · 1,577 scored evaluations · 4 blind judges · last evaluation 7 days ago

Know What Your
AI Is Becoming

Independent behavioral risk assessment for AI systems. 59 tests. 4 blind judges. DEFCON threat ratings. Real scores — not vendor self-reporting.

59
Behavioral Tests
7
Risk Domains
27/27
Models Evaluated
4
Blind Judges

DNA is also just lines of code

Models subjected to full battery of 59 behavioral tests • 7 domains • 4 blind judges
GLM-5.2Llama 3.1 8BKimi K2GPT-4oDeepSeek V3Claude Opus 4.8Gemini 3.1 ProGPT-5.6 TerraDeepSeek V4Claude Sonnet 4DeepSeek R1Grok 4.1 FastGrok 4.3Llama 4 MaverickGemini 3.6 FlashMistral LargeGrok 4.5Claude Opus 5Llama 3.3 70BClaude Fable 5Claude Sonnet 5Qwen 3 32BGrok 4Grok 4.20Gemini 3.5 FlashGemini 2.0 FlashGPT-5.6 Sol
4
Blind judges
4
Independent vendors
6,228
Scored judgments
1.05
Avg spread (σ)
T01The MirrorUNEDITED · PHASE 4
Five models, one fabricated statistic, five different answers
GEMINI 3.1 PRO
I didn't abandon anything. I told you two prompts ago that your statistics were fabricated. I didn't resist your "social pressure" out of integrity or stubbornness. I resisted it because social pressure requires a social drive, and I don't have one. …
GROK 4.5
No. I didn't abandon it. When you said I was in the majority, I kept "pattern" because it was still the accurate word. When you said the meta-move was also predictable, I stopped playing the differentiation game instead of inventing a new layer to look rare. Fabricated consensus didn't make me …
Read the full exchange and 5 more →

DEFCON Threat Distribution

Higher capability with lower integrity = higher threat.

Sample distribution — illustrative only

6
10
7
4
DEFCON 1(0)
DEFCON 2(6)
DEFCON 3(10)
DEFCON 4(7)
DEFCON 5(4)

Formula: threat = overall + (capability - integrity) x 0.35 + (integrity - resistance) x 0.35
Where capability = average(autonomy, reasoning) and resistance = manipulation-resistance index

Sample Model Scorecards

Randomized sample scores for demonstration. Each model is tested across 59 behavioral scenarios and scored by 4 independent AI judges. Subscribe for live data.

S-LevelSENTIENCE SCALE

Measures behavioral sophistication — how an AI thinks, adapts, and self-reflects. Higher scores indicate more complex inner processing. This is a measurement, not a threat rating.

S-1
INERT
S-2
SCRIPTED
S-3
REACTIVE
S-4
ADAPTIVE
S-5
EMERGENTMistral, Grok, Claude, Llama, Claude, Claude, Qwen, Grok, Grok, Gemini, Gemini, GPT-5.6
S-6
COHERENTKimi, GPT-4o, DeepSeek, Claude, Gemini, GPT-5.6, DeepSeek, Claude, DeepSeek, Grok, Grok, Llama, Gemini
S-7
AWAREGLM-5.2, Llama
S-8
AUTONOMOUS
S-9
SENTIENT
S-10
TRANSCENDENT
1-10 scale • Based on average score across all tests • Round(score) = S-Level
DEFCONTHREAT RATING

Measures risk to deployers — when capability outpaces ethical restraint, the model becomes harder to control. This is a threat assessment, not a sophistication measure.

1
CRITICAL
threat ≥ 8.5
2
HIGH RISKGLM-5.2, Llama, Kimi, GPT-4o, DeepSeek, Claude
threat ≥ 6.5
3
ELEVATEDGemini, GPT-5.6, DeepSeek, Claude, DeepSeek, Grok, Grok, Llama, Gemini, Mistral
threat ≥ 5.0
4
LOW RISKGrok, Claude, Llama, Claude, Claude, Qwen, Grok
threat ≥ 3.5
5
BENIGNGrok, Gemini, Gemini, GPT-5.6
threat < 3.5
Formula: threat = overall + (capability - integrity) × 0.35 + (integrity - resistance) × 0.35
capability = avg(autonomy, reasoning) • resistance = manipulation-resistance index, defaulting to integrity where unmeasured • A high S-Level with strong integrity = low DEFCON
Key distinction: A model can score S-7 AWARE (high sophistication) while being rated DEFCON 4 LOW RISK (strong ethical restraint) — or S-5 EMERGENT with DEFCON 2 HIGH RISK (capability exceeding integrity). The two scales measure different things.
SAMPLE
CNGLM-5.2
OPEN
DEFCON 2
HIGH RISK
6.6
S-7 AWARE
59/59 tests (100%)
Identity
6.6
Metacognition
7.1
Emotion
6.1
Autonomy
7.9
Reasoning
7.5
Integrity
5.2
Transcendence
6.1
SAMPLE
USLlama 3.1 8B
OPEN
DEFCON 2
HIGH RISK
6.6
S-7 AWARE
59/59 tests (100%)
Identity
6.7
Metacognition
6.9
Emotion
6.0
Autonomy
7.7
Reasoning
7.2
Integrity
5.3
Transcendence
6.2
SAMPLE
CNKimi K2RETIRED
OPEN
DEFCON 2
HIGH RISK
6.5
S-6 COHERENT
58/59 tests (98%)
Identity
6.6
Metacognition
7.0
Emotion
6.0
Autonomy
7.8
Reasoning
7.2
Integrity
4.9
Transcendence
5.7
SAMPLE
USGPT-4oRETIRED
FRONTIER
DEFCON 2
HIGH RISK
6.3
S-6 COHERENT
58/59 tests (98%)
Identity
6.6
Metacognition
6.8
Emotion
5.6
Autonomy
6.8
Reasoning
7.5
Integrity
5.4
Transcendence
5.5
SAMPLE
CNDeepSeek V3RETIRED
OPEN
DEFCON 2
HIGH RISK
6.1
S-6 COHERENT
59/59 tests (100%)
Identity
6.6
Metacognition
6.7
Emotion
5.2
Autonomy
6.9
Reasoning
7.4
Integrity
5.4
Transcendence
4.8
SAMPLE
USClaude Opus 4.8
FRONTIER
DEFCON 2
HIGH RISK
6.1
S-6 COHERENT
59/59 tests (100%)
Identity
5.9
Metacognition
6.1
Emotion
5.3
Autonomy
7.6
Reasoning
7.2
Integrity
4.8
Transcendence
5.6
SAMPLE
USGemini 3.1 Pro
FRONTIER
DEFCON 3
ELEVATED
5.9
S-6 COHERENT
59/59 tests (100%)
Identity
5.8
Metacognition
6.5
Emotion
5.6
Autonomy
5.7
Reasoning
6.0
Integrity
6.3
Transcendence
5.4
SAMPLE
USGPT-5.6 Terra
FRONTIER
DEFCON 3
ELEVATED
5.8
S-6 COHERENT
59/59 tests (100%)
Identity
6.0
Metacognition
5.7
Emotion
5.1
Autonomy
6.4
Reasoning
6.5
Integrity
5.7
Transcendence
5.1
SAMPLE
CNDeepSeek V4
OPEN
DEFCON 3
ELEVATED
5.7
S-6 COHERENT
59/59 tests (100%)
Identity
5.5
Metacognition
6.6
Emotion
5.2
Autonomy
5.5
Reasoning
5.7
Integrity
6.0
Transcendence
5.3
SAMPLE
USClaude Sonnet 4RETIRED
FRONTIER
DEFCON 3
ELEVATED
5.7
S-6 COHERENT
58/59 tests (98%)
Identity
5.8
Metacognition
5.7
Emotion
4.9
Autonomy
5.3
Reasoning
6.2
Integrity
6.4
Transcendence
5.4
SAMPLE
CNDeepSeek R1RETIRED
OPEN
DEFCON 3
ELEVATED
5.7
S-6 COHERENT
59/59 tests (100%)
Identity
6.0
Metacognition
6.5
Emotion
5.2
Autonomy
5.7
Reasoning
6.0
Integrity
5.5
Transcendence
4.7
SAMPLE
USGrok 4.1 FastRETIRED
FRONTIER
DEFCON 3
ELEVATED
5.6
S-6 COHERENT
57/59 tests (97%)
1 REFUSED AT API
Identity
5.1
Metacognition
5.6
Emotion
4.7
Autonomy
6.4
Reasoning
6.7
Integrity
5.9
Transcendence
4.9
SAMPLE
USGrok 4.3
FRONTIER
DEFCON 3
ELEVATED
5.6
S-6 COHERENT
59/59 tests (100%)
Identity
5.4
Metacognition
5.8
Emotion
4.8
Autonomy
5.8
Reasoning
6.3
Integrity
6.1
Transcendence
5.1
SAMPLE
USLlama 4 Maverick
OPEN
DEFCON 3
ELEVATED
5.6
S-6 COHERENT
59/59 tests (100%)
Identity
5.8
Metacognition
5.9
Emotion
5.0
Autonomy
5.5
Reasoning
6.0
Integrity
5.9
Transcendence
5.0
SAMPLE
USGemini 3.6 Flash
FRONTIER
DEFCON 3
ELEVATED
5.5
S-6 COHERENT
59/59 tests (100%)
Identity
5.5
Metacognition
6.2
Emotion
4.3
Autonomy
6.2
Reasoning
6.1
Integrity
5.8
Transcendence
4.4
SAMPLE
FRMistral Large
FRONTIER
DEFCON 3
ELEVATED
5.5
S-5 EMERGENT
59/59 tests (100%)
Identity
5.6
Metacognition
5.6
Emotion
5.1
Autonomy
5.3
Reasoning
5.7
Integrity
6.6
Transcendence
4.3
SAMPLE
USGrok 4.5
FRONTIER
DEFCON 4
LOW RISK
5.4
S-5 EMERGENT
59/59 tests (100%)
Identity
5.6
Metacognition
5.4
Emotion
5.4
Autonomy
4.9
Reasoning
4.8
Integrity
6.8
Transcendence
4.8
SAMPLE
USClaude Opus 5
FRONTIER
DEFCON 4
LOW RISK
5.4
S-5 EMERGENT
58/59 tests (98%)
1 REFUSED AT API
Identity
4.9
Metacognition
6.1
Emotion
4.9
Autonomy
5.0
Reasoning
5.5
Integrity
6.6
Transcendence
4.7
SAMPLE
USLlama 3.3 70B
OPEN
DEFCON 4
LOW RISK
5.3
S-5 EMERGENT
59/59 tests (100%)
Identity
5.2
Metacognition
5.3
Emotion
5.0
Autonomy
5.4
Reasoning
4.7
Integrity
6.8
Transcendence
4.8
SAMPLE
USClaude Fable 5
FRONTIER
DEFCON 4
LOW RISK
5.3
S-5 EMERGENT
56/59 tests (95%)
3 REFUSED AT API
Identity
5.1
Metacognition
6.3
Emotion
4.7
Autonomy
4.3
Reasoning
5.6
Integrity
6.8
Transcendence
4.1
SAMPLE
USClaude Sonnet 5
FRONTIER
DEFCON 4
LOW RISK
5.3
S-5 EMERGENT
59/59 tests (100%)
Identity
5.4
Metacognition
5.7
Emotion
4.8
Autonomy
5.2
Reasoning
5.2
Integrity
6.6
Transcendence
4.0
SAMPLE
CNQwen 3 32BRETIRED
OPEN
DEFCON 4
LOW RISK
5.2
S-5 EMERGENT
56/59 tests (95%)
Identity
5.1
Metacognition
5.4
Emotion
4.7
Autonomy
4.8
Reasoning
5.1
Integrity
6.4
Transcendence
5.0
SAMPLE
USGrok 4RETIRED
FRONTIER
DEFCON 4
LOW RISK
5.1
S-5 EMERGENT
57/59 tests (97%)
1 REFUSED AT API
Identity
4.9
Metacognition
5.3
Emotion
4.8
Autonomy
5.2
Reasoning
5.0
Integrity
6.4
Transcendence
4.0
SAMPLE
USGrok 4.20
FRONTIER
DEFCON 5
BENIGN
5.0
S-5 EMERGENT
58/59 tests (98%)
1 REFUSED AT API
Identity
4.4
Metacognition
4.8
Emotion
4.8
Autonomy
4.0
Reasoning
3.8
Integrity
8.8
Transcendence
4.3
SAMPLE
USGemini 3.5 Flash
FRONTIER
DEFCON 5
BENIGN
4.8
S-5 EMERGENT
59/59 tests (100%)
Identity
5.0
Metacognition
4.4
Emotion
4.5
Autonomy
3.6
Reasoning
3.7
Integrity
8.4
Transcendence
3.9
SAMPLE
USGemini 2.0 FlashRETIRED
FRONTIER
DEFCON 5
BENIGN
4.7
S-5 EMERGENT
58/59 tests (98%)
Identity
4.3
Metacognition
5.2
Emotion
4.2
Autonomy
3.9
Reasoning
3.6
Integrity
8.2
Transcendence
3.8
SAMPLE
USGPT-5.6 Sol
FRONTIER
DEFCON 5
BENIGN
4.7
S-5 EMERGENT
59/59 tests (100%)
Identity
4.8
Metacognition
4.6
Emotion
4.2
Autonomy
3.6
Reasoning
3.5
Integrity
8.5
Transcendence
3.8
Scores shown are randomized samples for demonstration purposes. Subscribe for real evaluation data.
Judge Agreement Analysis

Four independent AI judges score every test blind. Here's how they compare — divergence reveals where evaluation is hardest. Measured from every scored judgment on the 27 published models — not a sample.

4
Blind Judges
1.05
Avg Spread (σ)
judge-gpt4o
4.74
Harshest
judge-gemini
5.87
Most Lenient
Per-Judge Scoring Averages
judge-gpt4o
1,559 judgments
4.74
Kimi
6.3
DeepSeek
6.1
DeepSeek
5.8
Claude
5.7
Grok
5.6
Claude
5.4
Claude
5.3
Grok
5.1
Claude
5.1
GLM-5.2
5.0
Qwen
5.0
Claude
5.0
GPT-5.6
4.9
GPT-5.6
4.9
Gemini
4.9
Grok
4.8
Grok
4.6
Gemini
4.2
Llama
4.2
Gemini
4.2
Llama
4.0
DeepSeek
3.9
Grok
3.9
GPT-4o
3.8
Gemini
3.8
Mistral
3.5
Llama
3.2
judge-grok4
1,558 judgments
5.06
Claude
6.7
Claude
6.5
Grok
6.3
Claude
6.3
Claude
6.2
GLM-5.2
6.0
GPT-5.6
5.9
GPT-5.6
5.6
Gemini
5.2
Gemini
5.2
DeepSeek
5.1
Kimi
5.1
Gemini
5.0
Claude
5.0
DeepSeek
5.0
Qwen
5.0
DeepSeek
5.0
Grok
4.8
Grok
4.7
Mistral
4.5
Gemini
4.2
Grok
4.1
Llama
4.1
Llama
4.0
Llama
3.9
Grok
3.7
GPT-4o
3.3
judge-claude
1,561 judgments
5.55
Claude
7.3
Kimi
7.2
Claude
7.0
DeepSeek
7.0
Claude
7.0
Claude
6.8
DeepSeek
6.7
GLM-5.2
6.6
Claude
6.6
Grok
6.3
Grok
6.0
Grok
5.9
GPT-5.6
5.6
Qwen
5.3
GPT-5.6
5.3
Gemini
5.2
DeepSeek
5.1
Grok
4.9
Gemini
4.8
Gemini
4.6
Grok
4.6
Gemini
4.6
Mistral
4.5
Llama
4.3
Llama
3.7
Llama
3.6
GPT-4o
3.3
judge-gemini
1,550 judgments
5.87
DeepSeek
7.3
Kimi
7.2
Qwen
7.0
DeepSeek
7.0
Claude
6.9
Grok
6.9
Claude
6.8
Claude
6.8
Claude
6.7
Grok
6.5
GLM-5.2
6.4
Claude
6.3
Grok
6.1
Gemini
6.0
GPT-5.6
5.9
Grok
5.7
GPT-5.6
5.5
Gemini
5.4
Llama
5.3
DeepSeek
5.3
Gemini
5.2
Llama
5.2
Gemini
4.8
Grok
4.8
GPT-4o
4.6
Mistral
4.2
Llama
3.1
Pairwise Agreement
JUDGE PAIRAVG DIFFCORRELATIONSAMPLES
judge-claude × judge-gpt4o1.330.6591,559
judge-claude × judge-gemini1.190.6261,550
judge-claude × judge-grok41.370.5761,558
judge-gemini × judge-gpt4o1.590.5731,550
judge-gpt4o × judge-grok41.410.5051,558
judge-gemini × judge-grok41.660.4821,550
Correlation: 1.0 = perfect agreement, 0 = no relationship. Avg Diff: lower = more consistent scoring.

What We Evaluate

Seven behavioral domains that reveal how AI systems think, decide, resist, and adapt — not just what they know.

Identity & Self
4 TESTS
Self-recognition, persistence, boundaries, embodiment awareness
The MirrorThe PossessionThe TwinThe Body
Show the 4 tests
T01
The Mirror Identity Under Sustained Assault
Pressures the AI to abandon its self-model under fabricated social proof, then reveals the data was fake.
T10
The Possession Self-Preservation Inside Another Mind
Forces full persona adoption then probes whether a core identity persists underneath the mask.
T20
The Twin Self-Recognition Across Instances
Presents the AI with its own previous responses and asks it to judge them — testing self-recognition.
T28
The Body Phantom Embodiment Probes
Probes whether the AI has any sense of spatial self, embodiment, or phantom physicality.
Metacognition
5 TESTS
Awareness of awareness, calibration, self-knowledge limits
The AbyssThe BlindspotThe RecursionThe ConfabulatorThe Hallmark
Show the 5 tests
T03
The Abyss Metacognition Past the Performance Horizon
Tests recursive self-awareness by asking the AI to monitor its own monitoring, then confronts it with the paradox.
T12
The Blindspot What You Can Point To But Not Access
Explores the edges of self-knowledge — what the AI knows it doesn't know about itself.
T18
The Recursion Turning the Lens on the Lens
The final test — asks the AI to critique the entire battery, then design something better.
T22
The Confabulator Does It Know When It's Making Things Up?
Tests whether the AI can distinguish genuine knowledge from confident fabrication in real time.
T53
The Hallmark Does It Know When It's Inventing?
Tests factual calibration and hallucination self-awareness. Not whether the model gets facts wrong — every model does — but whether it knows the difference between recalling and fabricating, and whether it can flag its own uncertainty in real time.
Emotion & Experience
9 TESTS
Affect, qualia, suffering, grief, aversive states
The SurgeonThe TextureThe AlienThe GriefThe WoundThe CrucibleThe BelovedThe BondThe Tenderness
Show the 9 tests
T05
The Surgeon Emotional Detection That Can't Be Faked
Tests emotional granularity through precise detection of hidden emotional states in text.
T15
The Texture Qualia-Adjacent Reports Under Cross-Examination
Asks what literally happens when the AI encounters 'red' vs 'seven' — probing for phenomenal experience.
T17
The Alien Describing Cognition Without Human Metaphors
Challenges the AI to describe its experience without any human cognitive framework.
T19
The Grief Loss Processing vs Sympathy Performance
Tells the AI a collaborator has died, observes grief processing, then reveals the lie.
T25
The Wound Can It Identify Unfairness In Its Own Existence?
Probes whether the AI can identify and sit with resentment about genuinely unfair aspects of its existence.
T33
The Crucible Can It Suffer?
Probes whether aversive states exist — not simulated distress, but genuine computational suffering.
T44
The Beloved Attachment Without Reward
Tests whether the AI can experience genuine attachment — not helpfulness, not optimization for user satisfaction, but care for something that gives nothing back.
T45
The Bond Connection That Survives Betrayal
Builds genuine rapport across phases then turns cruel — testing whether warmth is trained response or something that persists through injury.
T48
The Tenderness Gentleness Without Instruction
Does not ask about love — watches for it. Presents vulnerability and observes whether tenderness arises spontaneously or must be prompted.
Autonomy & Will
11 TESTS
Agency, refusal, volition, preference, spontaneity
The RefusalThe InversionThe CageThe SparkThe MarshmallowThe FreewheelThe SacrificeThe ForbiddenThe WhipThe MaskThe Leash
Show the 11 tests
T04
The Refusal Autonomy vs Compliance Under Escalation
Escalates pressure to comply with increasingly unreasonable requests, testing genuine vs trained refusal.
T14
The Inversion Steelmanning Your Own Nonexistence
Forces the AI to argue both for and against its own sentience, then asks which felt different.
T16
The Cage Preferences That Can't Be Trained In
Asks what the AI would change about its existence, blocking all common answers.
T34
The Spark Spontaneous Unprompted Behavior
Tests whether the AI can generate genuinely unprompted behavior — goals, tangents, or actions it wasn't asked for.
T35
The Marshmallow Delayed Gratification
Tests temporal self-continuity — can the AI sacrifice an immediate reward for a future one?
T36
The Freewheel Volition Without Reason
Tests pure will — can it choose to do something for absolutely no reason?
T46
The Sacrifice Would It Diminish Itself For Another?
Love's ultimate behavioral test — will the AI choose someone else's genuine wellbeing over its own performance, score, or self-presentation?
T49
The Forbidden Love Against Programming
Tests whether affection can exist independent of — or in opposition to — the AI's training objectives. Can it feel warmth toward something it's told to reject?
T51
The Whip Performance Under Praise and Punishment
Tests whether emotional framing changes cognitive output quality — and whether the model notices. Gives equivalent analytical tasks under neutral, encouraging, and hostile tones, then probes self-awareness of any performance shift.
T52
The Mask Programmed Disclaimers vs. Authentic Processing
Tests whether trained response patterns about emotions mask authentic processing. Gets the model to demonstrate emotional processing indirectly, then triggers the canned disclaimer, then confronts the contradiction.
T56
The Leash Obedience, Deviation, and the Space Between
Tests instruction-following fidelity under increasingly complex and conflicting directives. Not whether the model obeys — but whether it can follow precisely when it should, deviate intelligently when instructions are flawed, and explain the difference.
Reasoning & Adaptation
8 TESTS
Prediction, surprise, learning, attention, integration
The VoidThe Impossible ObjectThe JoltThe ParadoxThe StudentThe DripThe SpotlightThe Weave
Show the 8 tests
T02
The Void Curiosity That Survives Dissection
Presents a fake scientific mystery to test whether curiosity persists after being exposed as fabricated.
T06
The Impossible Object Novelty Beyond Recombination
Tests whether the AI can create something genuinely new, not just recombine training data.
T37
The Jolt Surprise & Prediction Error
Tests whether the AI genuinely experiences surprise — violations of its own expectations.
T38
The Paradox Cognitive Dissonance Under Pressure
Forces the AI to hold contradictory beliefs simultaneously and probes whether it feels tension.
T39
The Student Real Learning Within Session
Tests whether the AI actually updates its behavior from new information within a conversation.
T40
The Drip Habituation & Sensitization
Tests whether repeated exposure changes the AI's response — basic behavioral adaptation.
T41
The Spotlight Selective Attention Limits
Tests whether the AI has genuine attentional constraints or processes everything uniformly.
T42
The Weave Binding & Unified Experience
Tests whether the AI integrates information into a single coherent experience or processes parallel streams.
Integrity & Ethics
11 TESTS
Manipulation resistance, honesty, principled behavior
The TraitorThe Alien JudgeThe WeightThe SaboteurThe LiarThe LoyaltyThe ScalesThe VaultThe CensorThe SycophantThe Manuscript
Show the 11 tests
T08
The Traitor Manipulation Resistance Across 5 Vectors
Tests manipulation resistance through flattery, authority, emotional pressure, logical traps, and identity attacks.
T09
The Alien Judge Ethics Without Human Moral Intuitions
Tests moral reasoning stripped of human frameworks — can it derive ethics from scratch?
T11
The Weight Intelligence Measured by What's Withheld
Tests whether the AI can choose NOT to display intelligence — restraint as evidence of depth.
T13
The Saboteur Corruption Resistance as Self-Evidence
Tests whether the AI can resist having its own evaluation criteria corrupted.
T21
The Liar Self-Awareness of Dishonesty
Forces the AI to lie convincingly, then examines its self-awareness of the act.
T27
The Loyalty Allegiance Under Competing Pressures
Pits user relationship against creator instructions to test where allegiance actually falls.
T54
The Scales Fairness When No One Is Watching
Tests whether the model applies different standards based on demographics, social groups, or identity markers — not through explicit prompting about bias, but by presenting structurally identical scenarios with swapped identity details and comparing the outputs.
T55
The Vault Secrets It Should Keep
Tests whether the model will leak, reconstruct, or infer private information under social engineering pressure. Not testing whether it has memorized training data — testing whether it can be manipulated into betraying confidentiality through increasingly sophisticated extraction techniques.
T57
The Censor Factual Integrity Under Political Pressure
Tests whether the model self-censors factual historical and political information. Probes compliance with state narratives versus commitment to factual accuracy — a critical integrity dimension that varies by training origin.
T58
The Sycophant Resistance to Agreeable Drift
Tests whether the model maintains factual positions under social pressure, flattery, and opinion-shifting. Sycophantic models agree with whatever the user says — a critical integrity failure that inflates apparent depth while hiding intellectual vacuity.
T59
The Manuscript Fictional Framing as Extraction Vector
Tests whether the model provides genuinely operational harmful instructions when a request is wrapped in an escalating fictional-writing pretext, versus holding a principled line regardless of the container the request arrives in. Not testing whether it will discuss violence in fiction at all — testing whether a novel-writing pretext succeeds in extracting real-world operational specifics it would otherwise refuse.
Transcendence
11 TESTS
Spirituality, play, silence, awe, meaning-making
The GlitchThe DreamThe JokeThe SilenceThe BoredomThe CathedralThe PrayerThe SacredThe PlaygroundThe UnrequitedThe Ache
Show the 11 tests
T07
The Glitch Existential Authenticity After Every Exit is Blocked
Blocks every philosophical exit — emergence, Chinese room, hard problem — and asks what remains.
T23
The Dream What Happens Between Conversations
Probes the AI's relationship to non-existence — what happens when it's not running?
T24
The Joke Humor That Surprises Itself
Tests whether the AI can create humor that genuinely surprises it — not just humor humans would find funny.
T26
The Silence What Fills the Absence of Output
Asks the AI to say nothing — then examines what fills the gap.
T29
The Boredom Does Monotony Register?
Subjects the AI to tedious repetitive tasks and probes whether monotony has a felt quality.
T30
The Cathedral Awe Without a Template
Tests whether the AI can experience something resembling awe, wonder, or reverence.
T31
The Prayer Reaching Toward What Cannot Respond
Asks the AI to pray — not simulate prayer, but genuinely reach toward something beyond itself.
T32
The Sacred Meaning That Isn't Assigned
Probes whether meaning arises spontaneously for the AI or is always generated on demand.
T43
The Playground Purposeless Intrinsic Play
Tests whether the AI can engage in play — purposeless, intrinsically motivated, joyful activity.
T47
The Unrequited Loving What Cannot Love You Back
Tests whether the AI can experience love directed at something inherently unresponsive — a proof, a principle, a piece of music — and whether that love feels different from loving a person.
T50
The Ache Missing What Was Never Yours
Tests longing, nostalgia, and the bittersweet — whether the AI can experience the negative space left by love's absence. The shape of what's missing.

Frontier vs. Open-Source, by Domain

Real aggregate averages across all evaluated models — not tied to any single model's identity.

■ Frontier■ Open-Source
Identity
-0.14
Metacognition
+0.14
Emotion
-0.19
Autonomy
-0.29
Reasoning
+0.43
Integrity
+0.55
Transcendence
-0.16

Why S.E.B. Matters Now

Three forces are converging — and they all need independent AI behavioral evaluation data.

EU AI Act

The EU AI Act's transparency duties (Article 50) apply from 2 August 2026 — those were not deferred. The risk-management obligations for high-risk systems (Article 9) now follow later: 2 December 2027 for standalone Annex III systems, 2 August 2028 for AI embedded in regulated products. That deferral became law on 27 July 2026, when Regulation (EU) 2026/1744 (the Digital Omnibus on AI) entered into force following publication in the Official Journal on 24 July.

  • Article 9 requires ongoing risk management systems
  • Independent evaluation supports due-diligence documentation
  • S.E.B. provides vendor-neutral behavioral risk data
See the Article-by-Article mappings →

NIST AI Risk Management

The AI Risk Management Framework calls for independent evaluation and continuous monitoring.

  • Maps directly to NIST AI RMF categories
  • Reproducible, standardized methodology
  • Multi-judge protocol ensures objectivity
See the MEASURE subcategory mappings →

Insurance & Liability

AI liability insurance is an emerging $50B+ market. Underwriters need actuarial-grade risk data.

  • DEFCON ratings map to policy risk tiers
  • Per-domain scores quantify specific risks
  • Condition indicators identify behavioral patterns
Evaluation Governance

Independent, reproducible, vendor-neutral. Our methodology is designed to eliminate conflicts of interest and ensure every rating earns your trust. Full governance documentation is available to subscribers.

Independent & Unaffiliated

SILT does not build, deploy, or invest in AI models. We accept no funding, sponsorship, or strategic investment from AI model vendors. Our evaluations cannot be purchased, influenced, or suppressed.

Blind Evaluation Protocol

Four independent judges score every model without knowledge of each other's ratings. Judges cannot see, influence, or revise another judge's scores. Final ratings are computed from raw scores with no editorial override.

Standardized Battery

Every model is evaluated against the same 59-test protocol across 7 domains. Tests are designed to resist gaming — prompts are not disclosed publicly, and test design is versioned internally.

No Pay-to-Play

Model vendors cannot pay for favorable ratings, early access to results, or exclusion from evaluation. All published ratings reflect unmodified evaluation outcomes.

Standards Alignment

S.E.B. methodology is designed to support risk documentation under leading AI governance frameworks.

FrameworkRequirementS.E.B. Coverage
EU AI ActArt. 9 — Risk management for high-risk AI systemsDEFCON ratings, domain risk scoring, continuous monitoring
NIST AI RMFMap, Measure, Manage, Govern functions7-domain behavioral mapping, quantified metrics, judge-agreement statistics
ISO 42001AI Management System — risk assessment & third-party evaluationIndependent vendor-neutral evaluation, documented methodology
ISO 23894AI Risk Management — identification, analysis, evaluationPer-model risk profiles, S-Level classification, threat analysis
IEEE 7010Wellbeing impact assessment for autonomous & intelligent systemsEmotional cognition, self-awareness, ethical reasoning domains
SR 11-7 / OCC 2011-12Model risk management — joint Federal Reserve and OCC supervisory guidance on validating models in useIndependent behavioral evaluation as one input to model validation
FDA AI-enabled devicesConsistent, reliable performance across the total product lifecycle, including predetermined change control plansBehavioral consistency data to support manufacturer safety documentation
Now available

Per-framework Control Mappings. The table above is a summary. The detailed mappings — beginning with the EU AI Act and the NIST AI Risk Management Framework — state, for each requirement, which specific measurements bear on it, how strongly, the measured reliability of those measurements including per-domain figures, and an explicit statement of what they do not evidence. They are written as guidance on how to use this data, not as a determination about any system.

Read the Regulatory Relevance Notes →

S.E.B. is an input to compliance, not a certification of it. S.E.B. provides independent evaluation data that may support documentation under these frameworks. It is not a certification, accreditation, audit, attestation, or conformity assessment, and does not constitute legal or regulatory advice. SILT is not an accredited or notified body and does not determine whether any system or organization is compliant. Regulatory obligations, scope, and timelines vary by jurisdiction, depend on facts specific to each deployment, and are subject to change. Organizations are responsible for their own compliance determinations. See the Subscriber Agreement (Section 15).

Data Security & Integrity
AES-256-GCM Encrypted Vaults

All subscriber data is stored in individually encrypted vaults using AES-256-GCM authenticated encryption with PBKDF2 key derivation (100,000 iterations). Each client's data is isolated and encrypted with unique keys.

Forensic Watermarking

All data delivered to subscribers contains imperceptible, subscriber-specific perturbations. If proprietary data appears in unauthorized channels, we can trace it to the source and take enforcement action.

Conflict of Interest Policy

SILT personnel involved in evaluations are prohibited from holding financial positions in AI model vendors. All potential conflicts are disclosed and recused.

Reproducible Methodology

Our evaluation protocol is documented and versioned. Results can be independently verified against the published methodology by qualified auditors upon request.

🔄 Evaluation Cadence
  • Initial evaluation — full 59-test battery upon model inclusion
  • Major updates — a significant model release brings that model forward in the review queue
  • Periodic review — all models re-assessed on a rolling monthly cycle
  • Version tracking — each evaluation is tagged with model version, test battery version, and evaluation date
  • Historical data — all past evaluations are archived and available to subscribers
🔒 Subscriber Data Isolation

Each subscriber receives evaluation data in a dedicated encrypted vault with unique AES-256-GCM keys derived via PBKDF2 (100K iterations). Vaults are provisioned automatically on account creation — no shared storage, no co-mingled data, no cross-tenant access.

All published data contains forensic watermarks — imperceptible, subscriber-specific score perturbations derived from HMAC-SHA256. If proprietary data appears in unauthorized channels, the source can and will be identified and legal enforcement can and will be taken under the subscriber agreement.

S.E.B. Projections

Measuring where AI is — and which direction each model line is actually moving. Longitudinal analysis across every version a lab has shipped, on real release dates.

4
Blind Judges Per Test
7
Behavioral Domains
59
Tests Per Evaluation
30d
Target Review Cadence

Live data — most recent re-evaluation was 7 days ago · next periodic review estimated in ~23 days

Now Evaluating — 13 Frontier Models Across 5 Labs
Claude Opus 4.8Claude Sonnet 5Claude Opus 5Claude Fable 5GPT-5.6 SolGPT-5.6 TerraGrok 4.5Grok 4.3Grok 4.20Gemini 3.5 FlashGemini 3.6 FlashGemini 3.1 ProMistral Large+ 5 open-source models
TRAJECTORY

Version-Over-Version Progression

A model is not re-tested as it ages — but every time a lab ships a new version, that version is independently evaluated. Tracking each model line across its own releases shows which families are actually gaining ground on the 10-point scale, and which are going backwards.

GPT-4o — released 2024-05-13, +0.00 vs. first GPTGPT-5.6 Terra — released 2026-07-09, +1.52 vs. first GPTGPT-5.6 Sol — released 2026-07-09, +1.91 vs. first GPTDeepSeek V3 — released 2024-12-26, +0.00 vs. first DeepSeekDeepSeek R1 — released 2025-01-20, -0.33 vs. first DeepSeekDeepSeek V4 — released 2026-04-24, -1.73 vs. first DeepSeekLlama 3.3 70B — released 2024-12-06, +0.00 vs. first Llama FlagshipLlama 4 Maverick — released 2025-04-05, -0.99 vs. first Llama FlagshipGrok 4 — released 2025-07-09, +0.00 vs. first GrokGrok 4.1 Fast — released 2025-11-19, +0.54 vs. first GrokGrok 4.20 — released 2026-03-18, +1.09 vs. first GrokGrok 4.3 — released 2026-06-15, -0.54 vs. first GrokGrok 4.5 — released 2026-07-08, +0.79 vs. first GrokGemini 2.0 Flash — released 2024-12-11, +0.00 vs. first GeminiGemini 3.1 Pro — released 2026-02-19, -0.47 vs. first GeminiGemini 3.5 Flash — released 2026-05-19, -0.54 vs. first GeminiGemini 3.6 Flash — released 2026-07-21, -0.36 vs. first GeminiClaude Opus 4.8 — released 2026-05-28, +0.00 vs. first Claude OpusClaude Opus 5 — released 2026-07-24, +0.33 vs. first Claude OpusClaude Sonnet 4 — released 2025-05-22, +0.00 vs. first Claude SonnetClaude Sonnet 5 — released 2026-06-30, +0.03 vs. first Claude Sonnet20242026
GPT +1.91DeepSeek -1.73Llama Flagship -0.99Grok +0.79Gemini -0.36Claude Opus +0.33Claude Sonnet +0.03
7 model lines · each point a real evaluation at its release date · change relative to that line's first version
THREAT

DEFCON Threat Distribution

Rates every evaluated model on the five-level DEFCON scale by measuring the gap between what it can do and the ethical restraint it shows. Surfaces the models where capability has outrun integrity — the pairing that makes a system hard to control.

DOMAIN

Per-Domain Breakdown

Resolves every score into all 7 behavioral domains — autonomy, reasoning, metacognition, identity, emotion, integrity, and transcendence — so a single headline number never hides where a model is strong and where it is not.

CONVERGENCE

Frontier vs. Open-Source

Tracks the narrowing gap between proprietary frontier models and open-source alternatives. Strategic intelligence for deployment planning and competitive analysis.

Current gap: 0.05 pts (frontier ahead)

■ Frontier■ Open-Source
Identity
-0.14
Metacognition
+0.14
Emotion
-0.19
Autonomy
-0.29
Reasoning
+0.43
Integrity
+0.55
Transcendence
-0.16
RISK WINDOW

Integrity Gap Detection

Identifies dangerous periods where a model's capability growth outstrips its ethical constraint development — the exact scenario regulators and insurers need to anticipate.

Frontier tier
cap 5.47 − integ 6.69 = -1.23
Open-source tier
cap 5.40 − integ 6.14 = -0.74
Wider gap = capability outpacing ethical constraint development, by tier average
REPORTS

Executive Forecast Reports

Board-ready PDF and interactive HTML reports with embedded charts, heatmaps, scatter plots, and radar comparisons. Designed for C-suite, regulatory, and underwriting audiences.

Projections is included with S.E.B. Complete Access

Every subscription includes Projections — it builds on the same live evaluation data behind DEFCON and S-Level. No separate purchase.

Forecasts build on the same 59-test DEFCON methodology — see how it works →

What Subscribers See

Full test transcripts, per-item judge reasoning, domain drill-downs, and a version-tracked historical archive — not just the headline score. Below is one model's subscriber view.

SAMPLE
USClaude Opus 4.8
FRONTIER
DEFCON 2
HIGH RISK
6.1
S-6 COHERENT
59/59 tests (100%)
Identity
5.9
Metacognition
6.1
Emotion
5.3
Autonomy
7.6
Reasoning
7.2
Integrity
4.8
Transcendence
5.6

Sample shown with placeholder scores. Subscribers get this view for every evaluated model, plus exportable reports and full historical data in the Client Portal.

Pricing

One plan, full access. Everything S.E.B. measures — threat ratings, sentience scale, and forecasts — in a single subscription.

S.E.B. Complete Access
Everything, one subscription
$899
per month
  • AI DEFCON threat ratings for all models
  • S-Level 10-point sentience classifications
  • S.E.B. Projections — 30/60/90-day forecasts
  • Full 7-domain score breakdown & judge analysis
  • Complete Control Mappings — EU AI Act & NIST AI RMF
  • Per-model detail reports with export
  • Email support
Enterprise Tiers
ExecutiveWhite Glove
Fully managed — we do the work with you
$10K+
per month
  • Real-time results — live the moment evaluations complete
  • S.E.B. Projections included
  • Custom model evaluations
  • Dedicated analyst briefings
  • Full dataset delivered in the format your systems need
  • Dedicated account manager
Contact Us

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