{
  "timestamp": 1762929087.953246,
  "results": [
    {
      "task_name": "simple_qa",
      "model_name": "CompactAI-DynamicAllocation",
      "efficiency_score": 0.30000000000000004,
      "quality_score": 0.9494961192929362,
      "tokens_used": 35,
      "tokens_allocated": 50,
      "inference_time": 0.06999999999999999,
      "memory_usage": 28672.0,
      "output_text": "Simulated output for simple_qa: Paris...",
      "metadata": {
        "complexity": "simple",
        "category": "qa",
        "efficiency_enabled": true,
        "simulated": true
      }
    },
    {
      "task_name": "complex_qa",
      "model_name": "CompactAI-DynamicAllocation",
      "efficiency_score": 0.20666666666666667,
      "quality_score": 0.894283133713478,
      "tokens_used": 119,
      "tokens_allocated": 150,
      "inference_time": 0.21000000000000002,
      "memory_usage": 97484.8,
      "output_text": "Simulated output for complex_qa: Tokyo hosted the 2020 Summer Olympics. Tokyo's pop...",
      "metadata": {
        "complexity": "complex",
        "category": "qa",
        "efficiency_enabled": true,
        "simulated": true
      }
    },
    {
      "task_name": "simple_math",
      "model_name": "CompactAI-DynamicAllocation",
      "efficiency_score": 0.2666666666666667,
      "quality_score": 0.8340978960766522,
      "tokens_used": 22,
      "tokens_allocated": 30,
      "inference_time": 0.06999999999999999,
      "memory_usage": 18022.4,
      "output_text": "Simulated output for simple_math: x = 5...",
      "metadata": {
        "complexity": "simple",
        "category": "math",
        "efficiency_enabled": true,
        "simulated": true
      }
    },
    {
      "task_name": "complex_math",
      "model_name": "CompactAI-DynamicAllocation",
      "efficiency_score": 0.2666666666666667,
      "quality_score": 0.8916521172757099,
      "tokens_used": 88,
      "tokens_allocated": 120,
      "inference_time": 0.21000000000000002,
      "memory_usage": 72089.6,
      "output_text": "Simulated output for complex_math: Distance = 80\u00d72.5 + 60\u00d71.5 = 200 + 90 = 290 km. Av...",
      "metadata": {
        "complexity": "complex",
        "category": "math",
        "efficiency_enabled": true,
        "simulated": true
      }
    },
    {
      "task_name": "simple_code",
      "model_name": "CompactAI-DynamicAllocation",
      "efficiency_score": 0.31666666666666665,
      "quality_score": 0.9154023818640408,
      "tokens_used": 41,
      "tokens_allocated": 60,
      "inference_time": 0.06999999999999999,
      "memory_usage": 33587.200000000004,
      "output_text": "Simulated output for simple_code: def factorial(n):\n    if n == 0 or n == 1:\n       ...",
      "metadata": {
        "complexity": "simple",
        "category": "code",
        "efficiency_enabled": true,
        "simulated": true
      }
    },
    {
      "task_name": "complex_code",
      "model_name": "CompactAI-DynamicAllocation",
      "efficiency_score": 0.28500000000000003,
      "quality_score": 0.8527048306121557,
      "tokens_used": 143,
      "tokens_allocated": 200,
      "inference_time": 0.21000000000000002,
      "memory_usage": 117145.6,
      "output_text": "Simulated output for complex_code: class Node:\n    def __init__(self, value):\n       ...",
      "metadata": {
        "complexity": "complex",
        "category": "code",
        "efficiency_enabled": true,
        "simulated": true
      }
    },
    {
      "task_name": "short_summary",
      "model_name": "CompactAI-DynamicAllocation",
      "efficiency_score": 0.30000000000000004,
      "quality_score": 0.9458148621143496,
      "tokens_used": 28,
      "tokens_allocated": 40,
      "inference_time": 0.06999999999999999,
      "memory_usage": 22937.600000000002,
      "output_text": "Simulated output for short_summary: Machine learning uses algorithms and statistical m...",
      "metadata": {
        "complexity": "simple",
        "category": "summarization",
        "efficiency_enabled": true,
        "simulated": true
      }
    },
    {
      "task_name": "long_summary",
      "model_name": "CompactAI-DynamicAllocation",
      "efficiency_score": 0.26,
      "quality_score": 0.8806774324623109,
      "tokens_used": 74,
      "tokens_allocated": 100,
      "inference_time": 0.21000000000000002,
      "memory_usage": 60620.8,
      "output_text": "Simulated output for long_summary: The transformer architecture replaced RNNs with se...",
      "metadata": {
        "complexity": "complex",
        "category": "summarization",
        "efficiency_enabled": true,
        "simulated": true
      }
    },
    {
      "task_name": "simple_translation",
      "model_name": "CompactAI-DynamicAllocation",
      "efficiency_score": 0.4,
      "quality_score": 0.8706420673193482,
      "tokens_used": 15,
      "tokens_allocated": 25,
      "inference_time": 0.06999999999999999,
      "memory_usage": 12288.0,
      "output_text": "Simulated output for simple_translation: Bonjour, comment allez-vous aujourd'hui?...",
      "metadata": {
        "complexity": "simple",
        "category": "translation",
        "efficiency_enabled": true,
        "simulated": true
      }
    },
    {
      "task_name": "complex_translation",
      "model_name": "CompactAI-DynamicAllocation",
      "efficiency_score": 0.275,
      "quality_score": 0.9078664437710698,
      "tokens_used": 58,
      "tokens_allocated": 80,
      "inference_time": 0.21000000000000002,
      "memory_usage": 47513.600000000006,
      "output_text": "Simulated output for complex_translation: Das System zur dynamischen Token-Zuweisung optimie...",
      "metadata": {
        "complexity": "complex",
        "category": "translation",
        "efficiency_enabled": true,
        "simulated": true
      }
    }
  ]
}