🎯 Our Mission
We believe choosing the right AI model shouldn't be a guessing game. Our goal is to provide transparent, data-driven comparisons that help you make informed decisions based on real performance and honest pricing.
📊 Performance Testing Methodology
Benchmark Sources
We aggregate performance data from multiple reputable sources to ensure accuracy:
🧮 HumanEval (Coding)
OpenAI's standard for measuring code generation accuracy. Tests ability to solve programming problems.
📝 MMLU (General Knowledge)
Massive Multitask Language Understanding benchmark covering 57 academic subjects.
🎨 ImageNet (Visual)
Standard benchmark for image generation and visual understanding tasks.
🗣️ LibriSpeech (Audio)
Speech recognition accuracy testing on diverse audio samples.
Performance Score Calculation
Our performance scores are weighted averages based on:
- Accuracy (40%) - Correctness of outputs on standardized tests
- Speed (25%) - Response time and throughput measurements
- Consistency (20%) - Reliability across multiple test runs
- Real-world Performance (15%) - User experience factors
| Performance Range | Tier Classification | Typical Use Cases |
|---|---|---|
| 85-99/100 | 🔥 Premium Tier | Mission-critical applications, enterprise use |
| 75-84/100 | 💪 Strong Tier | Professional work, reliable daily use |
| 65-74/100 | ⚡ Solid Tier | Standard tasks, good for most users |
| 50-64/100 | 💰 Budget Tier | Basic tasks, cost-sensitive applications |
💰 Pricing Data Collection
Sources
- Official Pricing Pages - Direct from provider websites
- API Documentation - Current rate limits and costs
- Real Usage Testing - Actual costs from test accounts
- Community Reports - Verified user experiences
Monthly Cost Calculations
Our "Monthly Cost" estimates are based on realistic usage scenarios:
- Light Use: 10k tokens/month (~50 queries)
- Moderate Use: 100k tokens/month (~500 queries)
- Heavy Use: 1M+ tokens/month (~5000+ queries)
🏆 Value Score Methodology
Our proprietary Value Score helps identify the best bang for your buck:
This formula rewards both high performance and low cost, with performance weighted more heavily to ensure quality isn't sacrificed for savings.
Value Badge System
- 🟢 Excellent Value: Value Score > 1000
- 🔵 Good Value: Value Score 500-1000
- 🟡 Fair Value: Value Score 100-500
- 🔴 Poor Value: Value Score < 100
🔄 Update Schedule
Regular Updates
- Pricing: Every 2 weeks
- Performance Scores: Monthly
- New Models: Within 1 week of public release
- Major Reviews: Quarterly comprehensive audits
Emergency Updates
We provide immediate updates for:
- Significant pricing changes (>20%)
- Model discontinuations or major updates
- Security or reliability issues
❓ Limitations & Disclaimers
What We Can't Control
- Real-time Pricing: Costs may vary based on usage patterns, geographic location, and provider changes
- Individual Results: Performance can vary based on specific use cases and prompting techniques
- Model Availability: Some models may have waitlists or geographic restrictions
Recommendations
- Always verify current pricing on provider websites before making decisions
- Test models with your specific use case when possible
- Consider factors beyond our metrics (API reliability, support, etc.)