Comprehensive platform for evaluating and comparing multiple AI models through a unified API proxy. Benchmark performance, accuracy, cost, and efficiency across different AI providers and model families.
Real-time performance metrics and comparative analysis across major AI models
Comprehensive analysis across multiple evaluation dimensions
| Model | Accuracy | Speed | Cost Efficiency | Context Length | Overall Rating |
|---|---|---|---|---|---|
| GPT-4 Turbo | 94.8% | 1.2s | High | 128K tokens | |
| Claude 3 Opus | 93.2% | 1.8s | Medium | 200K tokens | |
| Gemini Pro | 91.5% | 0.9s | Very High | 32K tokens | |
| Llama 3 70B | 89.7% | 2.1s | High | 8K tokens | |
| Mixtral 8x7B | 87.3% | 1.5s | Very High | 32K tokens |
# Model comparison API client
import json
from typing import Dict, List
import asyncio
class ModelComparator:
def __init__(self, api_key: str):
self.api_key = api_key
self.base_url = "https://api.modelcompare.com/v1"
self.models = [
"gpt-4-turbo",
"claude-3-opus",
"gemini-pro",
"llama-3-70b",
"mixtral-8x7b"
]
async def compare_models(self, prompt: str) -> Dict[str, Dict]:
"""Compare multiple models on the same prompt"""
results = {}
for model in self.models:
try:
response = await self.call_model(model, prompt)
analysis = await self.analyze_response(response)
results[model] = {
"response": response,
"analysis": analysis,
"performance": self.calculate_metrics(analysis),
"cost": self.estimate_cost(response)
}
except Exception as e:
results[model] = {"error": str(e)}
# Generate comparison report
comparison_report = self.generate_report(results)
return comparison_reportConnect with complementary platforms for enhanced model evaluation capabilities
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