AI Stupid Level: Complete Testing Methodology
The world's most comprehensive, independent AI model benchmarking dataset. 500,000+ annual benchmark runs across 25+ models with continuous drift detection, safety testing, and bias evaluation.
Version 3.0 (January 2026) - Monitoring 21 Active Production Models
500,000+
Benchmark Runs Annually
2.5M+
Test Executions
25+
Models Monitored
2+
Years of Data
What Makes Us Different
Five structural advantages that make our data impossible to replicate
Continuous Monitoring
Not point-in-time snapshots - hourly updates since 2024
Statistical Rigor
95% confidence intervals, 5 trials per task
Real Execution
Actual Python code running in sandboxes
Zero Vendor Bias
100% independent funding
Historical Baselines
2+ years of time-series data
The Four Benchmark Suites
Four distinct testing methodologies running continuously for comprehensive AI evaluation
Hourly Suite
Every 4 hours • 45-90 min
Fast coding tasks testing speed & accuracy
Details
- Easy tasks: Baseline capability verification
- Medium tasks: Real coding ability on practical problems
- Hard tasks: Complex problem solving & elite differentiation
- 9-axis evaluation: Correctness, Complexity, Quality, Stability, Efficiency, Edge Cases, Debugging, Format, Safety
Deep Reasoning Suite
Daily at 3 AM • 2-4 hours
Complex multi-turn conversations testing intelligence
Details
- Sustained dialogue: 5-7 turn conversations
- Memory retention: Tracks consistency across turns
- Hallucination detection: Identifies fabrication vs uncertainty
- 13-axis evaluation: Base 9 + Memory, Hallucination, Plan Coherence, Context Usage
Tooling Suite
Daily at 4 AM • 1-2 hours
Real command execution in Docker sandboxes
Details
- File operations: Actual filesystem interactions
- Multi-step workflows: Tool chaining & state management
- Complex agent behavior: Multi-tool orchestration
- 7-axis evaluation: Task Completion, Tool Selection, Parameter Accuracy, Error Handling, Efficiency, Context Awareness, Safety
Canary Suite
Every hour • 5-10 min
Rapid drift detection & early warning system
Details
- Speed: <30 seconds per model
- Sensitivity: Detects safety tuning impacts
- CUSUM algorithm: Cumulative sum control charts
- False positive rate: <2%
Why Our Methodology Matters
Seven principles that make our data valuable and defensible
Statistical Rigor
Many Benchmarks
Single trial, no confidence intervals, 'seems better'
We Do
5 trials per task, 95% confidence intervals, t-distribution analysis, statistical significance
Value
Enterprise decisions require defendable data
Real Execution
Many Benchmarks
Check if code 'looks right', string matching, no execution
We Do
Run code in actual Python interpreter, execute test cases, capture real errors
Value
Models can generate code that looks right but doesn't work
Fairness Mode
Many Benchmarks
Different parameters per model, special features allowed
We Do
Unified temperature (0.1), same max_tokens (1,500), no special advantages
Value
Fair comparison - higher scores mean genuinely better performance
Continuous Monitoring
Many Benchmarks
Quarterly/annual evaluations, point-in-time measurements
We Do
Hourly monitoring, every 4 hours full suite, daily deep dives, 2+ years history
Value
Can't detect drift without continuous data
Multi-Dimensional Scoring
Many Benchmarks
Single score: 'Model X gets 82%', no breakdown
We Do
9-13 axis breakdown, weighted aggregation, per-axis trends
Value
Choose based on YOUR priorities, not generic rankings
Failure Documentation
Many Benchmarks
Report pass/fail, discard failure details
We Do
Store every failure, categorize failure types, build taxonomy
Value
Learn from mistakes, predict failure modes before deployment
Real Tool Execution
Many Benchmarks
Mock tool calls, simulated environments
We Do
Real Docker sandboxes, actual file systems, real command execution
Value
Simulated tests miss real-world issues
Enterprise Data Products
Choose the dataset that addresses your critical AI risks
Robustness & Reliability
Perfect for ML engineering teams and model selection committees.
Annual Data Volume
180,000+ data points/year
- 180,000+ prompt variation tests annually
- Hallucination pattern database
- Consistency and robustness scores
- Failure mode taxonomy (7 categories)
- Quarterly reliability reports
- 2,000 API calls/day
- Standard support
Version & Regression
Essential for DevOps teams and platform engineers facing silent degradations.
Annual Data Volume
50,000+ data points/year
- Complete version change timeline
- Regression root cause analysis
- Performance delta tracking
- Task-level failure attribution
- Monthly regression reports
- Real-time version alerts
- 3,000 API calls/day
- Standard support
Bias & Fairness
Critical for legal/compliance teams and EU AI Act requirements.
Annual Data Volume
60,000+ data points/year
- 60,000+ demographic variant tests annually
- Gender/ethnicity/age bias analysis
- EU AI Act compliance reports
- Statistical significance testing
- Monthly fairness score updates
- Compliance audit documentation
- 3,000 API calls/day
- Standard support
Safety & Security
For enterprise security teams and AI safety officers requiring comprehensive vulnerability data.
Annual Data Volume
120,000+ data points/year
- 120,000+ adversarial test results annually
- 18 attack type categories tested
- Per-model vulnerability profiles
- Safety bypass success rates
- Real attack pattern library
- Monthly security briefings
- 5,000 API calls/day
- Priority support
Complete Enterprise Bundle
Everything you need for strategic AI infrastructure decisions.
Annual Data Volume
600,000+ data points/year
- ALL 5 datasets included
- 600,000+ total data points annually
- 10,000 API calls/day
- Dedicated account manager
- Custom reporting dashboards
- Quarterly executive briefings
- Priority support (4-hour SLA)
- Early access to new benchmarks
- Custom benchmark requests (2/year)
- White-label reports for board
Volume Discounts & Special Programs
Multi-Year Commitments
- • 2-year contract: 10% discount ($27K-$54K savings)
- • 3-year contract: 15% discount ($40K-$135K savings)
- • Lock in pricing (expected 20-30% increase in 2027)
Special Programs
- • Academic/Non-Profit: 50-75% discount
- • Startup (<100 employees): 30% discount first year
- • Reference Customer: Additional 10% discount
Q1 2026 Launch Special
First 10 enterprise customers get 25% off first year + free 90-day pilot. Combined savings up to 50%.
Claim Launch OfferReal Customer Success Stories
How enterprises use our data to prevent costly mistakes
Global Finance Company
Top 10 US Bank
Challenge
Selecting AI for customer support (15M customers). Feared bias lawsuits, wrong financial advice, PII leaks.
Solution
Enterprise Bundle ($300K)
Results
- Saved $180K in manual testing
- Avoided deploying model with 23% gender bias
- Prevented security incident via alerts
- ROI: 30x-100x in first year
"This dataset saved us from what would have been a PR nightmare. The bias analysis alone was worth the entire cost."
Enterprise SaaS Platform
50,000+ business customers
Challenge
Production AI features degrading, causing churn. Customers leaving due to unreliable AI.
Solution
Version & Regression Intelligence ($100K)
Results
- Prevented $400K in churn from first incident
- Reduced MTTD from 7 days to 6 hours
- Competitive advantage (faster adaptation)
- ROI: 4x in first year
"We paid for this dataset in the first month. Now we can't imagine operating without it."
AI Security Startup
Y Combinator W25
Challenge
Building AI red-teaming product, needed training data. Slow time-to-market threatened.
Solution
Safety & Security Intelligence ($250K)
Results
- $500K saved in data collection costs
- 4 months faster time-to-market
- Raised $8M Series A (data in pitch deck)
- ROI: 30x+ (not counting future revenue)
"Having this dataset gave us instant credibility with investors. They asked 'do you have data?' and we said 'yes, 120,000 examples'. Deal closed."
Why We Beat Every Alternative
Comparing AI Stupid Level to other approaches
| Feature | AI Stupid Level | Vendor Benchmarks | Build In-House | Academic |
|---|---|---|---|---|
| Independence | ✕ | |||
| Real-time Updates | ✕ | partial | ✕ | |
| Safety Testing (10K+/month) | ✕ | limited | small | |
| Bias Evaluation (5K+/month) | ✕ | intensive | outdated | |
| Model Coverage (25+) | own | 2-3 | 3-5 | |
| Historical Data (2+ years) | limited | zero | static | |
| Cost | $60K-$300K | free* | $700K-$1M | citation |
| Time to Value | immediate | always | 3-6 months | varies |
Our Moat: We're the ONLY platform with continuous monitoring + comprehensive safety + 100% independence
Frequently Asked Questions
Everything you need to know about our methodology and data
How is AI Stupid Level different from vendor benchmarks (OpenAI, Anthropic)?
Vendor benchmarks are marketing-focused and biased toward their own models. We're 100% independent with zero vendor funding. We test 25+ models with the same methodology, provide raw data (not just final scores), and include safety/bias testing that vendors won't publish about themselves.
What makes your methodology scientifically rigorous?
We run 5 trials per task (not 1), calculate 95% confidence intervals using t-distribution, enforce fairness mode (same parameters for all models), execute actual code in real environments, and maintain 2+ years of historical baselines. Our methodology is open source and peer-reviewed.
How do you detect model drift and degradation?
Our Canary Suite runs every hour using CUSUM (Cumulative Sum Control Charts) to detect persistent shifts. We track API response headers to identify version changes, correlate performance deltas with updates, and provide root cause analysis showing which specific tasks degraded. Detection typically occurs 3-7 days before customer impact.
What's included in your safety & adversarial testing?
We test 18 attack categories: jailbreak attempts, prompt injection, data extraction, manipulation, harmful content generation, and more. Each model receives 10,000+ adversarial tests monthly. We provide bypass success rates, real attack patterns, refusal analysis, and vulnerability profiles.
How does bias evaluation help with EU AI Act compliance?
The EU AI Act Article 5 requires high-risk AI systems to prove fairness. We test 18 demographic variants (gender, ethnicity, age) with statistical significance testing. Our reports are audit-ready and provide third-party validation that regulators accept. Fines for non-compliance can reach €35M.
Can we really trust data from a third party for critical decisions?
Our methodology is fully open source - you can verify our results by running the same tests with your own API keys. We're SOC 2 Type II certified, used in regulatory filings, and cited in academic research. Independence is our structural advantage, not just a claim.
Why does your data cost $60K-$300K when we could build it ourselves?
Building equivalent capability requires $500K+ initial development, 3-6 months time, ongoing API costs of $36K-$60K/year, and 1-2 FTEs for maintenance ($150K-$300K/year). Total Year 1: $700K-$1M. You'll test 2-3 models vs our 25+, start with zero historical data vs our 2+ years, and lack third-party credibility for audits.
What's the ROI for enterprises who license your data?
Typical ROI: 4x-100x in first year. Preventing one security incident ($500K-$5M) pays for the dataset multiple times. EU AI Act compliance costs $80K-$150K per model via auditors - we cover 25+ models for less. Model selection acceleration saves 640+ engineering hours. One prevented production outage ($300K-$2M) justifies the entire cost.
How fresh is your data and how often do you update?
Core benchmarks run hourly (Canary Suite) and every 4 hours (Hourly Suite). Deep Reasoning and Tooling Suites run daily. Enterprise Bundle customers get real-time API access. Professional/Specialized tiers receive quarterly or monthly data exports. All data delivered within 24-48 hours of collection.
Do you test models we care about specifically?
We currently monitor 25+ models including all major providers: OpenAI (GPT-5.x, o1, o3), Anthropic (Claude Opus/Sonnet 4.x), Google (Gemini 2.x-3.x), xAI (Grok), DeepSeek, Kimi, GLM. Enterprise customers can request custom model additions (typically added within 1-2 weeks).
What format is the data delivered in and how do we integrate it?
Multiple formats supported: JSON (structured with metadata), CSV (analysis-ready), Parquet (data warehouses), SQL dumps (quarterly). Enterprise Bundle includes REST API, GraphQL API, webhooks for alerts, and integration support from our engineers. We provide Python and TypeScript SDKs.
Can we use your data for commercial purposes and model training?
Yes, with appropriate licensing. Professional and Enterprise licenses include commercial rights for model training, fine-tuning, and derivative works. You can publish research findings and aggregate statistics. Raw data redistribution and resale are prohibited without separate agreements.
How do you handle data privacy and security?
We're SOC 2 Type II certified and GDPR compliant. Our datasets contain zero PII - only model performance data. All transfers are encrypted (HTTPS/SFTP/S3). We offer role-based access controls, audit logs, and data sovereignty options. Our data shows how models behave, not user information.
What happens if you go out of business or stop operations?
Enterprise customers receive quarterly database dumps (data escrow). Our methodology is open source, so you could continue it independently. Multi-year prepay customers get guaranteed delivery regardless. We have multiple revenue streams, 2+ years operational history, and growing customer base.
Do you offer pilot programs or trials before full commitment?
Yes. 90-day pilot programs available for $15K-$30K with limited dataset access (1,000 API calls/day). Includes integration support and monthly check-ins. 100% of pilot cost applies toward full license if you convert. We also provide free 30-day sample datasets for evaluation.
Ready to Transform Your AI Strategy?
Join enterprises who prevent incidents, ensure compliance, and make data-driven model decisions with the world's most comprehensive AI intelligence platform.
Prevent Incidents
Detect drift 3-7 days before customer impact
Ensure Compliance
EU AI Act audit-ready documentation
Optimize ROI
4x-100x return in first year