openevolve_comparison_results_1750305870.json

{
  "model": "mlx-community/Qwen3-0.6B-bf16",
  "timestamp": 1750305870,
  "optimization_type": "chunked_gqa_processing",
  "total_comparisons": 20,
  "individual_comparisons": [
    {
      "benchmark_name": "short_context_quick",
      "standard": {
        "name": "short_context_quick",
        "prompt_tokens": 16,
        "generated_tokens": 50,
        "prefill_tokens_per_sec": 355.133,
        "decode_tokens_per_sec": 186.437,
        "total_tokens_per_sec": 19.89186747411851,
        "peak_memory_gb": 1.243,
        "total_time_sec": 2.513590042013675,
        "prompt": "Brief answer: What is artificial intelligence?",
        "generated_text": "<think>\nOkay, the user is asking for a brief definition of artificial intelligence. Let me start by recalling the key points. AI is a branch of computer science that involves creating systems capable ..."
      },
      "optimized": {
        "name": "short_context_quick",
        "prompt_tokens": 16,
        "generated_tokens": 50,
        "prefill_tokens_per_sec": 331.978,
        "decode_tokens_per_sec": 183.74,
        "total_tokens_per_sec": 19.301839590556543,
        "peak_memory_gb": 1.243,
        "total_time_sec": 2.5904266671277583,
        "prompt": "Brief answer: What is artificial intelligence?",
        "generated_text": "<think>\nOkay, the user is asking for a brief definition of artificial intelligence. Let me start by recalling the key points. AI is a branch of computer science that involves creating systems capable ..."
      },
      "improvements": {
        "decode_speed_pct": -1.4466012647704065,
        "prefill_speed_pct": -6.520092472397658,
        "total_speed_pct": -2.9661764252635234,
        "memory_reduction_pct": 0.0,
        "time_reduction_pct": -3.0568479278557414
      }
    },
    {
      "benchmark_name": "code_generation",
      "standard": {
        "name": "code_generation",
        "prompt_tokens": 64,
        "generated_tokens": 300,
        "prefill_tokens_per_sec": 1286.789,
        "decode_tokens_per_sec": 173.538,
        "total_tokens_per_sec": 74.5889658469731,
        "peak_memory_gb": 1.309,
        "total_time_sec": 4.022042625118047,
        "prompt": "Write a Python function to implement binary search:\n\ndef binary_search(arr, target):\n    \"\"\"\n    Implement binary search algorithm\n    Args:\n        arr: sorted array\n        target: element to find\n ...",
        "generated_text": "<think>\nOkay, I need to write a Python function called binary_search that takes an array and a target. The function should return the index of the target or -1 if it's not found. Let me think about ho..."
      },
      "optimized": {
        "name": "code_generation",
        "prompt_tokens": 64,
        "generated_tokens": 300,
        "prefill_tokens_per_sec": 1859.139,
        "decode_tokens_per_sec": 144.969,
        "total_tokens_per_sec": 69.72322167293892,
        "peak_memory_gb": 1.309,
        "total_time_sec": 4.302727166097611,
        "prompt": "Write a Python function to implement binary search:\n\ndef binary_search(arr, target):\n    \"\"\"\n    Implement binary search algorithm\n    Args:\n        arr: sorted array\n        target: element to find\n ...",
        "generated_text": "<think>\nOkay, I need to write a Python function called binary_search that takes an array and a target. The function should return the index of the target or -1 if it's not found. Let me think about ho..."
      },
      "improvements": {
        "decode_speed_pct": -16.462676762438207,
        "prefill_speed_pct": 44.47893166634156,
        "total_speed_pct": -6.523410156961754,
        "memory_reduction_pct": 0.0,
        "time_reduction_pct": -6.978656546966011
      }
    },
    {
      "benchmark_name": "sustained_dialogue_generation",
      "standard": {
        "name": "sustained_dialogue_generation",
        "prompt_tokens": 47,
        "generated_tokens": 945,
        "prefill_tokens_per_sec": 999.622,
        "decode_tokens_per_sec": 108.362,
        "total_tokens_per_sec": 84.07564971368124,
        "peak_memory_gb": 1.341,
        "total_time_sec": 11.239877458196133,
        "prompt": "Create a detailed dialogue between an AI researcher and a software engineer discussing the future of artificial intelligence, covering topics like AGI, safety, ethics, and technological implications. ...",
        "generated_text": "<think>\nOkay, the user wants a detailed dialogue between an AI researcher and a software engineer discussing the future of AI, covering AGI, safety, ethics, and technological implications. It needs to..."
      },
      "optimized": {
        "name": "sustained_dialogue_generation",
        "prompt_tokens": 47,
        "generated_tokens": 945,
        "prefill_tokens_per_sec": 1290.104,
        "decode_tokens_per_sec": 158.907,
        "total_tokens_per_sec": 114.54800525926025,
        "peak_memory_gb": 1.334,
        "total_time_sec": 8.249816291965544,
        "prompt": "Create a detailed dialogue between an AI researcher and a software engineer discussing the future of artificial intelligence, covering topics like AGI, safety, ethics, and technological implications. ...",
        "generated_text": "<think>\nOkay, the user wants a detailed dialogue between an AI researcher and a software engineer discussing the future of AI, covering AGI, safety, ethics, and technological implications. It needs to..."
      },
      "improvements": {
        "decode_speed_pct": 46.64458020339235,
        "prefill_speed_pct": 29.05918437169251,
        "total_speed_pct": 36.24397271903613,
        "memory_reduction_pct": 0.521998508575682,
        "time_reduction_pct": 26.60225769677082
      }
    },
    {
      "benchmark_name": "technical_documentation",
      "standard": {
        "name": "technical_documentation",
        "prompt_tokens": 84,
        "generated_tokens": 1200,
        "prefill_tokens_per_sec": 1616.155,
        "decode_tokens_per_sec": 133.789,
        "total_tokens_per_sec": 105.73404966830024,
        "peak_memory_gb": 1.428,
        "total_time_sec": 11.34922954114154,
        "prompt": "Create comprehensive documentation for a REST API with the following endpoints:\n- GET /users - List all users\n- POST /users - Create new user  \n- GET /users/{id} - Get specific user\n- PUT /users/{id} ...",
        "generated_text": "<think>\nOkay, I need to create comprehensive documentation for a REST API with the given endpoints. Let me start by breaking down each endpoint and thinking about what information should be included.\n..."
      },
      "optimized": {
        "name": "technical_documentation",
        "prompt_tokens": 84,
        "generated_tokens": 1200,
        "prefill_tokens_per_sec": 1403.096,
        "decode_tokens_per_sec": 145.408,
        "total_tokens_per_sec": 114.65301020422453,
        "peak_memory_gb": 1.403,
        "total_time_sec": 10.46636279206723,
        "prompt": "Create comprehensive documentation for a REST API with the following endpoints:\n- GET /users - List all users\n- POST /users - Create new user  \n- GET /users/{id} - Get specific user\n- PUT /users/{id} ...",
        "generated_text": "<think>\nOkay, I need to create comprehensive documentation for a REST API with the given endpoints. Let me start by breaking down each endpoint and thinking about what information should be included.\n..."
      },
      "improvements": {
        "decode_speed_pct": 8.684570480383291,
        "prefill_speed_pct": -13.183079593232083,
        "total_speed_pct": 8.435277532548955,
        "memory_reduction_pct": 1.7507002801120386,
        "time_reduction_pct": 7.779089724759489
      }
    },
    {
      "benchmark_name": "progressive_context_building",
      "standard": {
        "name": "progressive_context_building",
        "prompt_tokens": 348,
        "generated_tokens": 600,
        "prefill_tokens_per_sec": 3682.41,
        "decode_tokens_per_sec": 90.467,
        "total_tokens_per_sec": 66.01334784072361,
        "peak_memory_gb": 1.733,
        "total_time_sec": 9.089070917107165,
        "prompt": "Chapter 1: The Beginning\n\nIn the early days of artificial intelligence, researchers dreamed of creating \nmachines that could think and reason like humans. The field began in the 1950s \nwith pioneers l...",
        "generated_text": "<think>\nOkay, the user wants me to continue the historical narrative from Chapter 5 into Chapter 6, focusing on the transformer era and large language models. Let me start by recalling the previous ch..."
      },
      "optimized": {
        "name": "progressive_context_building",
        "prompt_tokens": 348,
        "generated_tokens": 600,
        "prefill_tokens_per_sec": 4294.586,
        "decode_tokens_per_sec": 150.34,
        "total_tokens_per_sec": 97.06952694112076,
        "peak_memory_gb": 1.733,
        "total_time_sec": 6.181136541068554,
        "prompt": "Chapter 1: The Beginning\n\nIn the early days of artificial intelligence, researchers dreamed of creating \nmachines that could think and reason like humans. The field began in the 1950s \nwith pioneers l...",
        "generated_text": "<think>\nOkay, the user wants me to continue the historical narrative from Chapter 5 into Chapter 6, focusing on the transformer era and large language models. Let me start by recalling the previous ch..."
      },
      "improvements": {
        "decode_speed_pct": 66.18214376512984,
        "prefill_speed_pct": 16.624330261975185,
        "total_speed_pct": 47.04530237631517,
        "memory_reduction_pct": 0.0,
        "time_reduction_pct": 31.99374724390573
      }
    },
    {
      "benchmark_name": "maximum_context_stress_test",
      "standard": {
        "name": "maximum_context_stress_test",
        "prompt_tokens": 1936,
        "generated_tokens": 1642,
        "prefill_tokens_per_sec": 5323.962,
        "decode_tokens_per_sec": 90.432,
        "total_tokens_per_sec": 78.57323431997136,
        "peak_memory_gb": 2.709,
        "total_time_sec": 20.897701541893184,
        "prompt": "Research Paper Summary:\n\nTitle: \"Advances in Large Language Models: Architecture, Training, and Applications\"\n\nAbstract: This paper reviews recent developments in large language models (LLMs), \nfocusi...",
        "generated_text": "<think>\nOkay, let's tackle this query. The user wants a detailed analysis of how optimization strategies for Apple Silicon, specifically the M-series chips, apply to LLM inference. They mentioned cons..."
      },
      "optimized": {
        "name": "maximum_context_stress_test",
        "prompt_tokens": 1936,
        "generated_tokens": 1642,
        "prefill_tokens_per_sec": 5307.325,
        "decode_tokens_per_sec": 131.441,
        "total_tokens_per_sec": 108.62816525269336,
        "peak_memory_gb": 2.709,
        "total_time_sec": 15.115785083733499,
        "prompt": "Research Paper Summary:\n\nTitle: \"Advances in Large Language Models: Architecture, Training, and Applications\"\n\nAbstract: This paper reviews recent developments in large language models (LLMs), \nfocusi...",
        "generated_text": "<think>\nOkay, let's tackle this query. The user wants a detailed analysis of how optimization strategies for Apple Silicon, specifically the M-series chips, apply to LLM inference. They mentioned cons..."
      },
      "improvements": {
        "decode_speed_pct": 45.34788570417551,
        "prefill_speed_pct": -0.3124928389797039,
        "total_speed_pct": 38.2508511872252,
        "memory_reduction_pct": 0.0,
        "time_reduction_pct": 27.667714779870877
      }
    },
    {
      "benchmark_name": "very_long_generation",
      "standard": {
        "name": "very_long_generation",
        "prompt_tokens": 18,
        "generated_tokens": 1169,
        "prefill_tokens_per_sec": 330.493,
        "decode_tokens_per_sec": 167.434,
        "total_tokens_per_sec": 125.5328968001133,
        "peak_memory_gb": 1.383,
        "total_time_sec": 9.312300040852278,
        "prompt": "Write a comprehensive guide to machine learning for beginners:",
        "generated_text": "<think>\nOkay, the user wants a comprehensive guide to machine learning for beginners. Let me start by breaking down what they need. They probably want a solid foundation without getting too technical...."
      },
      "optimized": {
        "name": "very_long_generation",
        "prompt_tokens": 18,
        "generated_tokens": 1169,
        "prefill_tokens_per_sec": 493.859,
        "decode_tokens_per_sec": 131.146,
        "total_tokens_per_sec": 104.55887658599336,
        "peak_memory_gb": 1.373,
        "total_time_sec": 11.180303750094026,
        "prompt": "Write a comprehensive guide to machine learning for beginners:",
        "generated_text": "<think>\nOkay, the user wants a comprehensive guide to machine learning for beginners. Let me start by breaking down what they need. They probably want a solid foundation without getting too technical...."
      },
      "improvements": {
        "decode_speed_pct": -21.673017427762588,
        "prefill_speed_pct": 49.431001564329655,
        "total_speed_pct": -16.7079871083649,
        "memory_reduction_pct": 0.7230657989877085,
        "time_reduction_pct": -20.059530954189324
      }
    },
    {
      "benchmark_name": "extreme_long_generation",
      "standard": {
        "name": "extreme_long_generation",
        "prompt_tokens": 35,
        "generated_tokens": 1153,
        "prefill_tokens_per_sec": 675.64,
        "decode_tokens_per_sec": 90.801,
        "total_tokens_per_sec": 76.0227511960408,
        "peak_memory_gb": 1.395,
        "total_time_sec": 15.166512417141348,
        "prompt": "Write a complete tutorial on deep learning from basics to advanced topics, including mathematical foundations, architectures, training techniques, and real-world applications:",
        "generated_text": "<think>\nOkay, the user wants a complete tutorial on deep learning from basics to advanced topics. Let me start by breaking down the sections they mentioned: mathematical foundations, architectures, tr..."
      },
      "optimized": {
        "name": "extreme_long_generation",
        "prompt_tokens": 35,
        "generated_tokens": 1153,
        "prefill_tokens_per_sec": 834.378,
        "decode_tokens_per_sec": 157.88,
        "total_tokens_per_sec": 117.97192751142086,
        "peak_memory_gb": 1.367,
        "total_time_sec": 9.77351158298552,
        "prompt": "Write a complete tutorial on deep learning from basics to advanced topics, including mathematical foundations, architectures, training techniques, and real-world applications:",
        "generated_text": "<think>\nOkay, the user wants a complete tutorial on deep learning from basics to advanced topics. Let me start by breaking down the sections they mentioned: mathematical foundations, architectures, tr..."
      },
      "improvements": {
        "decode_speed_pct": 73.87473706236715,
        "prefill_speed_pct": 23.49446450772602,
        "total_speed_pct": 55.17976612975397,
        "memory_reduction_pct": 2.0071684587813636,
        "time_reduction_pct": 35.55860889983252
      }
    },
    {
      "benchmark_name": "repetitive_pattern_generation",
      "standard": {
        "name": "repetitive_pattern_generation",
        "prompt_tokens": 27,
        "generated_tokens": 2000,
        "prefill_tokens_per_sec": 613.308,
        "decode_tokens_per_sec": 71.494,
        "total_tokens_per_sec": 65.91223332172675,
        "peak_memory_gb": 1.549,
        "total_time_sec": 30.343380874954164,
        "prompt": "Generate a list of 100 creative product names for a tech startup, with explanations:",
        "generated_text": "<think>\nOkay, the user wants a list of 100 creative product names for a tech startup. Let me start by brainstorming some ideas. Tech startups often focus on innovative solutions, so I need to think ab..."
      },
      "optimized": {
        "name": "repetitive_pattern_generation",
        "prompt_tokens": 27,
        "generated_tokens": 2000,
        "prefill_tokens_per_sec": 698.002,
        "decode_tokens_per_sec": 147.488,
        "total_tokens_per_sec": 127.07780282702558,
        "peak_memory_gb": 1.465,
        "total_time_sec": 15.738389832898974,
        "prompt": "Generate a list of 100 creative product names for a tech startup, with explanations:",
        "generated_text": "<think>\nOkay, the user wants a list of 100 creative product names for a tech startup. Let me start by brainstorming some ideas. Tech startups often focus on innovative solutions, so I need to think ab..."
      },
      "improvements": {
        "decode_speed_pct": 106.2942344812152,
        "prefill_speed_pct": 13.809374735043397,
        "total_speed_pct": 92.79850859663821,
        "memory_reduction_pct": 5.422853453841179,
        "time_reduction_pct": 48.132378861283534
      }
    },
    {
      "benchmark_name": "long_context_detailed",
      "standard": {
        "name": "long_context_detailed",
        "prompt_tokens": 391,
        "generated_tokens": 500,
        "prefill_tokens_per_sec": 4059.863,
        "decode_tokens_per_sec": 170.307,
        "total_tokens_per_sec": 94.50554749332285,
        "peak_memory_gb": 1.758,
        "total_time_sec": 5.290694708004594,
        "prompt": "Research Paper Summary:\n\nTitle: \"Advances in Large Language Models: Architecture, Training, and Applications\"\n\nAbstract: This paper reviews recent developments in large language models (LLMs), \nfocusi...",
        "generated_text": "<think>\nOkay, the user wants a detailed analysis of how architectural and training advances impact inference efficiency on mobile and edge devices. Let me start by recalling the key points from the re..."
      },
      "optimized": {
        "name": "long_context_detailed",
        "prompt_tokens": 391,
        "generated_tokens": 500,
        "prefill_tokens_per_sec": 3974.441,
        "decode_tokens_per_sec": 120.803,
        "total_tokens_per_sec": 75.56414253281604,
        "peak_memory_gb": 1.758,
        "total_time_sec": 6.616895040962845,
        "prompt": "Research Paper Summary:\n\nTitle: \"Advances in Large Language Models: Architecture, Training, and Applications\"\n\nAbstract: This paper reviews recent developments in large language models (LLMs), \nfocusi...",
        "generated_text": "<think>\nOkay, the user wants a detailed analysis of how architectural and training advances impact inference efficiency on mobile and edge devices. Let me start by recalling the key points from the re..."
      },
      "improvements": {
        "decode_speed_pct": -29.067507501159668,
        "prefill_speed_pct": -2.104061146890918,
        "total_speed_pct": -20.042638197345074,
        "memory_reduction_pct": 0.0,
        "time_reduction_pct": -25.066657710409316
      }
    },
    {
      "benchmark_name": "micro_generation",
      "standard": {
        "name": "micro_generation",
        "prompt_tokens": 17,
        "generated_tokens": 10,
        "prefill_tokens_per_sec": 346.786,
        "decode_tokens_per_sec": 203.067,
        "total_tokens_per_sec": 4.517200654424452,
        "peak_memory_gb": 1.249,
        "total_time_sec": 2.213760416023433,
        "prompt": "Complete this sentence: The future of AI is",
        "generated_text": "<think>\nOkay, the user wants me to complete"
      },
      "optimized": {
        "name": "micro_generation",
        "prompt_tokens": 17,
        "generated_tokens": 10,
        "prefill_tokens_per_sec": 368.377,
        "decode_tokens_per_sec": 203.11,
        "total_tokens_per_sec": 4.236131800369787,
        "peak_memory_gb": 1.249,
        "total_time_sec": 2.360644208267331,
        "prompt": "Complete this sentence: The future of AI is",
        "generated_text": "<think>\nOkay, the user wants me to complete"
      },
      "improvements": {
        "decode_speed_pct": 0.02117527712528691,
        "prefill_speed_pct": 6.226029885866214,
        "total_speed_pct": -6.22219103283286,
        "memory_reduction_pct": 0.0,
        "time_reduction_pct": -6.63503562448481
      }
    },
    {
      "benchmark_name": "step_by_step_reasoning",
      "standard": {
        "name": "step_by_step_reasoning",
        "prompt_tokens": 61,
        "generated_tokens": 400,
        "prefill_tokens_per_sec": 1279.141,
        "decode_tokens_per_sec": 168.392,
        "total_tokens_per_sec": 85.45661112975772,
        "peak_memory_gb": 1.307,
        "total_time_sec": 4.68073791731149,
        "prompt": "Solve this step by step:\n\nA train travels from City A to City B at 80 mph. The distance is 240 miles. \nIf it leaves at 2:00 PM, what time will it arrive? Show your work.",
        "generated_text": "<think>\nOkay, let's see. I need to figure out what time the train will arrive at City B if it leaves at 2:00 PM and travels at 80 mph for 240 miles. Hmm, right. So, first, I remember that distance equ..."
      },
      "optimized": {
        "name": "step_by_step_reasoning",
        "prompt_tokens": 61,
        "generated_tokens": 400,
        "prefill_tokens_per_sec": 1442.308,
        "decode_tokens_per_sec": 142.962,
        "total_tokens_per_sec": 78.87836216644345,
        "peak_memory_gb": 1.307,
        "total_time_sec": 5.071099209133536,
        "prompt": "Solve this step by step:\n\nA train travels from City A to City B at 80 mph. The distance is 240 miles. \nIf it leaves at 2:00 PM, what time will it arrive? Show your work.",
        "generated_text": "<think>\nOkay, let's see. I need to figure out what time the train will arrive at City B if it leaves at 2:00 PM and travels at 80 mph for 240 miles. Hmm, right. So, first, I remember that distance equ..."
      },
      "improvements": {
        "decode_speed_pct": -15.101667537650249,
        "prefill_speed_pct": 12.755982335020136,
        "total_speed_pct": -7.69776483802502,
        "memory_reduction_pct": 0.0,
        "time_reduction_pct": -8.339738278836615
      }
    },
    {
      "benchmark_name": "ultra_long_generation",
      "standard": {
        "name": "ultra_long_generation",
        "prompt_tokens": 13,
        "generated_tokens": 468,
        "prefill_tokens_per_sec": 383.678,
        "decode_tokens_per_sec": 171.811,
        "total_tokens_per_sec": 92.45339073205282,
        "peak_memory_gb": 1.523,
        "total_time_sec": 5.062010125257075,
        "prompt": "The future of AI is",
        "generated_text": "<think>\nOkay, the user is asking about the future of AI. Let me start by breaking down the key points they might be interested in. First, I should mention the current state of AI, like machine learnin..."
      },
      "optimized": {
        "name": "ultra_long_generation",
        "prompt_tokens": 13,
        "generated_tokens": 468,
        "prefill_tokens_per_sec": 440.611,
        "decode_tokens_per_sec": 139.934,
        "total_tokens_per_sec": 83.87973277956566,
        "peak_memory_gb": 1.503,
        "total_time_sec": 5.579416916240007,
        "prompt": "The future of AI is",
        "generated_text": "<think>\nOkay, the user is asking about the future of AI. Let me start by breaking down the key points they might be interested in. First, I should mention the current state of AI, like machine learnin..."
      },
      "improvements": {
        "decode_speed_pct": -18.5535268405399,
        "prefill_speed_pct": 14.83874498928789,
        "total_speed_pct": -9.273492172218138,
        "memory_reduction_pct": 1.3131976362442561,
        "time_reduction_pct": -10.221370131231321
      }
    },
    {
      "benchmark_name": "very_long_context_comprehensive",
      "standard": {
        "name": "very_long_context_comprehensive",
        "prompt_tokens": 928,
        "generated_tokens": 1000,
        "prefill_tokens_per_sec": 5146.123,
        "decode_tokens_per_sec": 161.682,
        "total_tokens_per_sec": 117.59371221458863,
        "peak_memory_gb": 2.158,
        "total_time_sec": 8.503856041003019,
        "prompt": "Research Paper Summary:\n\nTitle: \"Advances in Large Language Models: Architecture, Training, and Applications\"\n\nAbstract: This paper reviews recent developments in large language models (LLMs), \nfocusi...",
        "generated_text": "<think>\nOkay, so I need to analyze how the architectural and training advances in large language models impact inference efficiency on mobile and edge devices, especially considering Apple Silicon. Le..."
      },
      "optimized": {
        "name": "very_long_context_comprehensive",
        "prompt_tokens": 928,
        "generated_tokens": 1000,
        "prefill_tokens_per_sec": 4958.784,
        "decode_tokens_per_sec": 106.292,
        "total_tokens_per_sec": 82.90796709835429,
        "peak_memory_gb": 2.158,
        "total_time_sec": 12.061567000113428,
        "prompt": "Research Paper Summary:\n\nTitle: \"Advances in Large Language Models: Architecture, Training, and Applications\"\n\nAbstract: This paper reviews recent developments in large language models (LLMs), \nfocusi...",
        "generated_text": "<think>\nOkay, so I need to analyze how the architectural and training advances in large language models impact inference efficiency on mobile and edge devices, especially considering Apple Silicon. Le..."
      },
      "improvements": {
        "decode_speed_pct": -34.25860640021771,
        "prefill_speed_pct": -3.6403910283528,
        "total_speed_pct": -29.496258314338036,
        "memory_reduction_pct": 0.0,
        "time_reduction_pct": -41.83644386683175
      }
    },
    {
      "benchmark_name": "short_generation",
      "standard": {
        "name": "short_generation",
        "prompt_tokens": 19,
        "generated_tokens": 100,
        "prefill_tokens_per_sec": 388.449,
        "decode_tokens_per_sec": 180.845,
        "total_tokens_per_sec": 34.69684412864018,
        "peak_memory_gb": 1.25,
        "total_time_sec": 2.882106500212103,
        "prompt": "Explain in one paragraph: What makes transformers effective?",
        "generated_text": "<think>\nOkay, the user wants me to explain why transformers are effective in one paragraph. Let me start by recalling what I know about transformers. They are used in power transmission, right? So, th..."
      },
      "optimized": {
        "name": "short_generation",
        "prompt_tokens": 19,
        "generated_tokens": 100,
        "prefill_tokens_per_sec": 480.388,
        "decode_tokens_per_sec": 166.885,
        "total_tokens_per_sec": 33.4333817918928,
        "peak_memory_gb": 1.25,
        "total_time_sec": 2.991022584028542,
        "prompt": "Explain in one paragraph: What makes transformers effective?",
        "generated_text": "<think>\nOkay, the user wants me to explain why transformers are effective in one paragraph. Let me start by recalling what I know about transformers. They are used in power transmission, right? So, th..."
      },
      "improvements": {
        "decode_speed_pct": -7.719317647709369,
        "prefill_speed_pct": 23.668229291361275,
        "total_speed_pct": -3.6414330135127986,
        "memory_reduction_pct": 0.0,
        "time_reduction_pct": -3.77904438328089
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    },
    {
      "benchmark_name": "long_generation",
      "standard": {
        "name": "long_generation",
        "prompt_tokens": 19,
        "generated_tokens": 1000,
        "prefill_tokens_per_sec": 383.041,
        "decode_tokens_per_sec": 167.826,
        "total_tokens_per_sec": 121.2860867452095,
        "peak_memory_gb": 1.336,
        "total_time_sec": 8.244968791026622,
        "prompt": "Write a detailed technical explanation of how neural networks learn:",
        "generated_text": "<think>\nOkay, so I need to explain how neural networks learn. Let me start by recalling what I know. Neural networks are like big computers that can learn from data. They have layers of processing, ri..."
      },
      "optimized": {
        "name": "long_generation",
        "prompt_tokens": 19,
        "generated_tokens": 1000,
        "prefill_tokens_per_sec": 515.049,
        "decode_tokens_per_sec": 131.841,
        "total_tokens_per_sec": 101.30268327558746,
        "peak_memory_gb": 1.364,
        "total_time_sec": 9.871406834106892,
        "prompt": "Write a detailed technical explanation of how neural networks learn:",
        "generated_text": "<think>\nOkay, so I need to explain how neural networks learn. Let me start by recalling what I know. Neural networks are like big computers that can learn from data. They have layers of processing, ri..."
      },
      "improvements": {
        "decode_speed_pct": -21.441850488005425,
        "prefill_speed_pct": 34.46315146420357,
        "total_speed_pct": -16.47625379455269,
        "memory_reduction_pct": -2.0958083832335346,
        "time_reduction_pct": -19.726430557874245
      }
    },
    {
      "benchmark_name": "conversational_assistant",
      "standard": {
        "name": "conversational_assistant",
        "prompt_tokens": 85,
        "generated_tokens": 1060,
        "prefill_tokens_per_sec": 1558.637,
        "decode_tokens_per_sec": 110.265,
        "total_tokens_per_sec": 88.00089711055672,
        "peak_memory_gb": 1.404,
        "total_time_sec": 12.045331750065088,
        "prompt": "You are a helpful AI assistant. A user asks:\n\n\"I'm planning a trip to Japan for 2 weeks. I've never been there before. I like \nhistory, food, and nature. I have a moderate budget. Can you help me plan...",
        "generated_text": "<think>\nOkay, the user is planning a 2-week trip to Japan. They've never been before, so they need a detailed itinerary with recommendations for cities, activities, and travel tips. Let me start by br..."
      },
      "optimized": {
        "name": "conversational_assistant",
        "prompt_tokens": 85,
        "generated_tokens": 1060,
        "prefill_tokens_per_sec": 1624.919,
        "decode_tokens_per_sec": 147.833,
        "total_tokens_per_sec": 110.80791478921105,
        "peak_memory_gb": 1.367,
        "total_time_sec": 9.566103667020798,
        "prompt": "You are a helpful AI assistant. A user asks:\n\n\"I'm planning a trip to Japan for 2 weeks. I've never been there before. I like \nhistory, food, and nature. I have a moderate budget. Can you help me plan...",
        "generated_text": "<think>\nOkay, the user is planning a 2-week trip to Japan. They've never been before, so they need a detailed itinerary with recommendations for cities, activities, and travel tips. Let me start by br..."
      },
      "improvements": {
        "decode_speed_pct": 34.07064798440121,
        "prefill_speed_pct": 4.252561693325653,
        "total_speed_pct": 25.916801336697247,
        "memory_reduction_pct": 2.63532763532763,
        "time_reduction_pct": 20.582480702790885
      }
    },
    {
      "benchmark_name": "creative_writing",
      "standard": {
        "name": "creative_writing",
        "prompt_tokens": 53,
        "generated_tokens": 800,
        "prefill_tokens_per_sec": 1112.589,
        "decode_tokens_per_sec": 154.895,
        "total_tokens_per_sec": 106.99556747700527,
        "peak_memory_gb": 1.381,
        "total_time_sec": 7.476945249829441,
        "prompt": "Write a short story about a robot who discovers emotions for the first time. \nInclude dialogue and describe the robot's internal experience as it learns about feelings like \njoy, sadness, and wonder. ...",
        "generated_text": "<think>\nOkay, the user wants a short story about a robot discovering emotions for the first time. They specified including dialogue, internal experience, and making it engaging and thoughtful. Let me ..."
      },
      "optimized": {
        "name": "creative_writing",
        "prompt_tokens": 53,
        "generated_tokens": 800,
        "prefill_tokens_per_sec": 1540.651,
        "decode_tokens_per_sec": 141.137,
        "total_tokens_per_sec": 100.8810695154153,
        "peak_memory_gb": 1.335,
        "total_time_sec": 7.930130041670054,
        "prompt": "Write a short story about a robot who discovers emotions for the first time. \nInclude dialogue and describe the robot's internal experience as it learns about feelings like \njoy, sadness, and wonder. ...",
        "generated_text": "<think>\nOkay, the user wants a short story about a robot discovering emotions for the first time. They specified including dialogue, internal experience, and making it engaging and thoughtful. Let me ..."
      },
      "improvements": {
        "decode_speed_pct": -8.88214596985055,
        "prefill_speed_pct": 38.47440519365194,
        "total_speed_pct": -5.7147208111252334,
        "memory_reduction_pct": 3.330919623461263,
        "time_reduction_pct": -6.06109549686686
      }
    },
    {
      "benchmark_name": "medium_context_analysis",
      "standard": {
        "name": "medium_context_analysis",
        "prompt_tokens": 127,
        "generated_tokens": 200,
        "prefill_tokens_per_sec": 2300.242,
        "decode_tokens_per_sec": 169.049,
        "total_tokens_per_sec": 59.57798010812093,
        "peak_memory_gb": 1.396,
        "total_time_sec": 3.3569449591450393,
        "prompt": "Context: Machine learning has revolutionized many industries in recent years. \nFrom healthcare diagnosis to autonomous vehicles, AI systems are becoming increasingly \nsophisticated. However, challenge...",
        "generated_text": "<think>\nOkay, let's tackle this question. The user wants me to analyze the current state of AI development based on the given context and predict the most important research directions for the next fi..."
      },
      "optimized": {
        "name": "medium_context_analysis",
        "prompt_tokens": 127,
        "generated_tokens": 200,
        "prefill_tokens_per_sec": 2099.829,
        "decode_tokens_per_sec": 169.053,
        "total_tokens_per_sec": 54.26174147081993,
        "peak_memory_gb": 1.396,
        "total_time_sec": 3.6858382089994848,
        "prompt": "Context: Machine learning has revolutionized many industries in recent years. \nFrom healthcare diagnosis to autonomous vehicles, AI systems are becoming increasingly \nsophisticated. However, challenge...",
        "generated_text": "<think>\nOkay, let's tackle this question. The user wants me to analyze the current state of AI development based on the given context and predict the most important research directions for the next fi..."
      },
      "improvements": {
        "decode_speed_pct": 0.0023661778537528632,
        "prefill_speed_pct": -8.712691968931964,
        "total_speed_pct": -8.92316024754985,
        "memory_reduction_pct": 0.0,
        "time_reduction_pct": -9.7973977487617
      }
    },
    {
      "benchmark_name": "comprehensive_analysis_generation",
      "standard": {
        "name": "comprehensive_analysis_generation",
        "prompt_tokens": 39,
        "generated_tokens": 1232,
        "prefill_tokens_per_sec": 899.455,
        "decode_tokens_per_sec": 108.956,
        "total_tokens_per_sec": 89.29787741356088,
        "peak_memory_gb": 1.428,
        "total_time_sec": 13.796520540956408,
        "prompt": "Analyze the evolution of computer programming languages from assembly to modern high-level languages. Discuss paradigms, performance considerations, developer productivity, and future trends:",
        "generated_text": "<think>\nOkay, so I need to analyze the evolution of computer programming languages from assembly to modern high-level languages. Let me start by recalling what I know about this topic. \n\nFirst, assemb..."
      },
      "optimized": {
        "name": "comprehensive_analysis_generation",
        "prompt_tokens": 39,
        "generated_tokens": 1232,
        "prefill_tokens_per_sec": 1003.789,
        "decode_tokens_per_sec": 156.875,
        "total_tokens_per_sec": 123.20302567134158,
        "peak_memory_gb": 1.368,
        "total_time_sec": 9.99975441582501,
        "prompt": "Analyze the evolution of computer programming languages from assembly to modern high-level languages. Discuss paradigms, performance considerations, developer productivity, and future trends:",
        "generated_text": "<think>\nOkay, so I need to analyze the evolution of computer programming languages from assembly to modern high-level languages. Let me start by recalling what I know about this topic. \n\nFirst, assemb..."
      },
      "improvements": {
        "decode_speed_pct": 43.98013877161422,
        "prefill_speed_pct": 11.599690923948385,
        "total_speed_pct": 37.968593699889915,
        "memory_reduction_pct": 4.201680672268896,
        "time_reduction_pct": 27.519736689118844
      }
    }
  ],
  "aggregate_improvements": {
    "decode_speed_improvements_avg": 12.524778103377688,
    "decode_speed_improvements_median": -0.7221175434583268,
    "decode_speed_improvements_min": -34.25860640021771,
    "decode_speed_improvements_max": 106.2942344812152,
    "decode_speed_improvements_std": 38.29698329321707,
    "prefill_speed_improvements_avg": 14.435163691749414,
    "prefill_speed_improvements_median": 13.282678535031767,
    "prefill_speed_improvements_min": -13.183079593232083,
    "prefill_speed_improvements_max": 49.431001564329655,
    "prefill_speed_improvements_std": 17.649765739092885,
    "total_speed_improvements_avg": 10.407679373300745,
    "total_speed_improvements_median": -4.678076912319016,
    "total_speed_improvements_min": -29.496258314338036,
    "total_speed_improvements_max": 92.79850859663821,
    "total_speed_improvements_std": 30.698256840048263,
    "memory_improvements_avg": 0.9905551842183241,
    "memory_improvements_median": 0.0,
    "memory_improvements_min": -2.0958083832335346,
    "memory_improvements_max": 5.422853453841179,
    "memory_improvements_std": 1.7245771941812529,
    "time_improvements_avg": 3.213888268537205,
    "time_improvements_median": -4.920069940073875,
    "time_improvements_min": -41.83644386683175,
    "time_improvements_max": 48.132378861283534,
    "time_improvements_std": 23.136633995726953
  },
  "summary": {
    "avg_decode_improvement_pct": 12.524778103377688,
    "avg_total_improvement_pct": 10.407679373300745,
    "avg_memory_reduction_pct": 0.9905551842183241,
    "avg_time_reduction_pct": 3.213888268537205,
    "avg_standard_decode_speed": 143.99245,
    "avg_optimized_decode_speed": 148.9022,
    "benchmarks_improved": 10,
    "total_benchmarks": 20
  }
}