

AIQ-X
Test AI models yourself, privately, with a standardized benchmark, and get both technical scores AND practical recommendations.
Cost / License
- Free
- Proprietary
Platforms
- Online

AIQ-X
Features
Tags
- ai-models
- ai-testing
- claude
- gemini
- llm-evaluation
- ai-benchmarks
- model-evaluation
- ChatGPT
- prompt-engineering
- Machine Learning
- llm-testing
AIQ-X News & Activities
Recent activities
AIQ-X information
What is AIQ-X?
AIQ-X Professional Suite Guide
Multi-Tier Testing: Choose from Basic (10Q), Advanced (25Q), or Expert (40+Q) test suites.
Professional Diagnostics: Detailed analysis with specific weaknesses, strengths, and improvement recommendations.
Adaptive Testing: Advanced and Expert tiers probe deeper based on performance patterns.
Actionable Insights: Clear guidance for model trainers and best-fit application recommendations for users. 📊 Test Tiers Explained Basic Tier (10 questions): Core capabilities assessment across all domains. Perfect for quick comparisons. Takes 2-5 minutes.
Advanced Tier (25 questions): Includes Basic plus 15 follow-up questions targeting common failure modes. Takes 5-10 minutes.
Expert Tier (40+ questions): Comprehensive with stress tests, adversarial examples, and boundary cases. Takes 10-20 minutes.
Start with Basic, then use Advanced/Expert for serious evaluation. 🔬 For Model Trainers & Researchers The Diagnostics tab identifies specific failure patterns: • Consistency issues (variance across similar questions) • Overconfidence markers (absolute language) • Instruction following failures • Reasoning gaps and logical inconsistencies
Each report includes targeted improvement suggestions for training data, architecture, and fine-tuning strategies. 💡 For End Users & Decision Makers The Insights tab shows recommended use cases based on actual test performance, not marketing claims.
Each model gets a risk profile indicating where it's likely to fail or provide unreliable outputs.
Clear recommendations like "Excellent for creative writing, avoid for mathematical tasks" based on empirical testing. 📈 Understanding Scores Scores measure response quality across multiple dimensions:
• Length & Depth: Comprehensive responses score higher • Uncertainty Calibration: Appropriate hedging is rewarded • Structure: Logical organization and clear reasoning • Domain-Specific: Each domain has tailored criteria
Scores indicate capability patterns. Low scores mean the model's response style doesn't match evaluation criteria, which may or may not matter for your use case. ?? Data Management & Privacy Local Storage: All data stays in your browser. Nothing sent to external servers.
Export/Import: Export as JSON for backup, sharing, or external analysis.
Portability: Export and import across different machines or browsers.
