{
 "lane": "full_recipe",
 "model": "qwen3.8-flash-next",
 "thinking": "off",
 "concurrency": 1,
 "n": 40,
 "summary": {
  "coding": {
   "n": 5,
   "auto_score": 1.0,
   "ttft_med_s": 0.24,
   "decode_med_tok_s": 44.5,
   "tokens_med": 138
  },
  "reasoning": {
   "n": 5,
   "auto_score": 1.0,
   "ttft_med_s": 0.27,
   "decode_med_tok_s": 46.6,
   "tokens_med": 423
  },
  "json": {
   "n": 5,
   "auto_score": 1.0,
   "ttft_med_s": 0.29,
   "decode_med_tok_s": 47.1,
   "tokens_med": 38
  },
  "html": {
   "n": 5,
   "auto_score": 1.0,
   "ttft_med_s": 0.27,
   "decode_med_tok_s": 48.2,
   "tokens_med": 163
  },
  "prose": {
   "n": 5,
   "auto_score": 0.6,
   "ttft_med_s": 0.26,
   "decode_med_tok_s": 29.4,
   "tokens_med": 194
  },
  "narrative": {
   "n": 5,
   "auto_score": 0.693,
   "ttft_med_s": 0.26,
   "decode_med_tok_s": 28.9,
   "tokens_med": 337
  },
  "summary": {
   "n": 5,
   "auto_score": 0.75,
   "ttft_med_s": 0.23,
   "decode_med_tok_s": 36.0,
   "tokens_med": 31
  },
  "format": {
   "n": 5,
   "auto_score": 1.0,
   "ttft_med_s": 0.25,
   "decode_med_tok_s": 31.2,
   "tokens_med": 21
  }
 },
 "batches": [],
 "overall": {
  "auto_score": 0.88,
  "ttft_med_s": 0.26,
  "decode_med_tok_s": 43.5,
  "agg_tok_s_med": null
 },
 "items": [
  {
   "ttft_s": 0.22,
   "wall_s": 3.3,
   "completion_tokens": 138,
   "prompt_tokens": 47,
   "decode_tok_s": 44.5,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "```python\ndef merge_intervals(intervals):\n    if not intervals:\n        return []\n    \n    # Sort intervals by start time\n    intervals.sort(key=lambda x: x[0])\n    \n    merged = [intervals[0]]\n    \n    for current in intervals[1:]:\n        last = merged[-1]\n        # If current interval overlaps with the last merged interval\n        if current[0] <= last[1]:\n            # Merge them by updating the end time\n            last[1] = max(last[1], current[1])\n        else:\n            merged.append(current)\n    \n    return merged\n```",
   "id": "code1",
   "category": "coding",
   "prompt": "Write a Python function merge_intervals(intervals) that merges overlapping [start, end] intervals and returns the merged list sorted by start. Return only one ```python code block.",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.27,
   "wall_s": 5.97,
   "completion_tokens": 253,
   "prompt_tokens": 82,
   "decode_tok_s": 44.2,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "```python\ndef parse_duration(s: str) -> int:\n    \"\"\"\n    Convert a duration string like '1h30m15s', '45s', '2h', '3m', '1h1s'\n    into total seconds (int). Units appear in h, m, s order and may be omitted.\n    \"\"\"\n    total_seconds = 0\n    current_number = \"\"\n    \n    for char in s:\n        if char.isdigit():\n            current_number += char\n        elif char == 'h':\n            if current_number:\n                total_seconds += int(current_number) * 3600\n                current_number = \"\"\n        elif char == 'm':\n            if current_number:\n                total_seconds += int(current_number) * 60\n                current_number = \"\"\n        elif char == 's':\n            if current_number:\n                total_seconds += int(current_number)\n                current_number = \"\"\n    \n    # Handle any remaining number (shouldn't happen with valid input, but just in case)\n    if current_number:\n        total_seconds += int(current_number)\n    \n    return total_seconds\n```",
   "id": "code2",
   "category": "coding",
   "prompt": "Write a Python function parse_duration(s) that converts strings like '1h30m15s', '45s', '2h', '3m', '1h1s' into total seconds (int). Units may be omitted but always appear in h, m, s order. Return only one ```python code block.",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.24,
   "wall_s": 2.11,
   "completion_tokens": 85,
   "prompt_tokens": 48,
   "decode_tok_s": 45.1,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "```python\ndef top_k_frequent(words, k):\n    from collections import Counter\n    \n    # Count frequencies\n    freq = Counter(words)\n    \n    # Sort by frequency descending, then by word ascending (alphabetically)\n    sorted_words = sorted(freq.keys(), key=lambda w: (-freq[w], w))\n    \n    # Return the top k\n    return sorted_words[:k]\n```",
   "id": "code3",
   "category": "coding",
   "prompt": "Write a Python function top_k_frequent(words, k) returning the k most frequent words, most frequent first; ties broken alphabetically. Return only one ```python code block.",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.31,
   "wall_s": 2.3,
   "completion_tokens": 88,
   "prompt_tokens": 123,
   "decode_tok_s": 43.7,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "```python\ndef binary_search(a, target):\n    lo, hi = 0, len(a)\n    while lo < hi:\n        mid = (lo + hi) // 2\n        if a[mid] == target:\n            return mid\n        if a[mid] < target:\n            lo = mid + 1\n        else:\n            hi = mid\n    return -1\n```",
   "id": "code4",
   "category": "coding",
   "prompt": "This binary search has a bug that can make it loop forever. Return the corrected function only, as one ```python code block, same name and signature.\n\ndef binary_search(a, target):\n    lo, hi = 0, len(a)\n    while lo < hi:\n        mid = (lo + hi) // 2\n        if a[mid] == target:\n            return mid\n        if a[mid] < target:\n            lo = mid\n        else:\n            hi = mid\n    return -1",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.23,
   "wall_s": 3.42,
   "completion_tokens": 152,
   "prompt_tokens": 38,
   "decode_tok_s": 47.3,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "```python\ndef roman_to_int(s: str) -> int:\n    roman_values = {\n        'I': 1,\n        'V': 5,\n        'X': 10,\n        'L': 50,\n        'C': 100,\n        'D': 500,\n        'M': 1000\n    }\n    \n    total = 0\n    prev_value = 0\n    \n    for char in reversed(s):\n        value = roman_values[char]\n        if value < prev_value:\n            total -= value\n        else:\n            total += value\n        prev_value = value\n    \n    return total\n```",
   "id": "code5",
   "category": "coding",
   "prompt": "Write a Python function roman_to_int(s) converting a Roman numeral string to an integer. Return only one ```python code block.",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.25,
   "wall_s": 8.38,
   "completion_tokens": 380,
   "prompt_tokens": 60,
   "decode_tok_s": 46.6,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "Let $A$ be Ana's current age and $B$ be Ben's current age.\n\nFrom the first statement, \"Ana is twice as old as Ben,\" we can write the equation:\n$$ A = 2B $$\n\nFrom the second statement, \"In 6 years Ana will be 1.5 times Ben's age,\" we can write the equation:\n$$ A + 6 = 1.5(B + 6) $$\n\nNow, substitute the value of $A$ from the first equation into the second equation:\n$$ 2B + 6 = 1.5(B + 6) $$\n\nExpand the right side of the equation:\n$$ 2B + 6 = 1.5B + 9 $$\n\nSubtract $1.5B$ from both sides to group the terms with $B$:\n$$ 2B - 1.5B + 6 = 9 $$\n$$ 0.5B + 6 = 9 $$\n\nSubtract 6 from both sides:\n$$ 0.5B = 3 $$\n\nMultiply both sides by 2 to solve for $B$:\n$$ B = 6 $$\n\nSo, Ben is currently 6 years old.\n\nLet's verify the answer:\n- If Ben is 6, Ana is $2 \\times 6 = 12$.\n- In 6 years, Ben will be $6 + 6 = 12$.\n- In 6 years, Ana will be $12 + 6 = 18$.\n- Is 18 equal to 1.5 times 12?\n  $$ 1.5 \\times 12 = 18 $$\n  Yes, the condition holds.\n\nANSWER: 6",
   "id": "reason1",
   "category": "reasoning",
   "prompt": "Ana is twice as old as Ben. In 6 years Ana will be 1.5 times Ben's age. How old is Ben now?\n\nGive your final answer on the last line exactly as: ANSWER: <answer>",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.27,
   "wall_s": 9.07,
   "completion_tokens": 423,
   "prompt_tokens": 56,
   "decode_tok_s": 48.0,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "To find the probability of getting exactly 2 heads when flipping a fair coin 4 times, we can follow these steps:\n\n1.  **Determine the total number of possible outcomes:**\n    Since each coin flip has 2 possible outcomes (Heads or Tails) and there are 4 independent flips, the total number of outcomes is:\n    $$2^4 = 16$$\n\n2.  **Determine the number of favorable outcomes:**\n    We need to find the number of ways to get exactly 2 heads in 4 flips. This is a combination problem where we choose 2 positions for the heads out of the 4 available positions. The formula for combinations is $\\binom{n}{k} = \\frac{n!}{k!(n-k)!}$.\n    Here, $n=4$ and $k=2$:\n    $$\\binom{4}{2} = \\frac{4!}{2!(4-2)!} = \\frac{4 \\times 3 \\times 2 \\times 1}{(2 \\times 1)(2 \\times 1)} = \\frac{24}{4} = 6$$\n    So, there are 6 favorable outcomes: HHTT, HTHT, HTTH, THHT, THTH, TTHH.\n\n3.  **Calculate the probability:**\n    The probability $P$ is the ratio of favorable outcomes to total outcomes:\n    $$P = \\frac{\\text{Number of favorable outcomes}}{\\text{Total number of outcomes}} = \\frac{6}{16}$$\n\n4.  **Simplify the fraction:**\n    Both 6 and 16 are divisible by 2:\n    $$\\frac{6}{16} = \\frac{3}{8}$$\n    The fraction $\\frac{3}{8}$ is in lowest terms because 3 and 8 share no common factors other than 1.\n\nANSWER: 3/8",
   "id": "reason2",
   "category": "reasoning",
   "prompt": "A fair coin is flipped 4 times. What is the probability of exactly 2 heads? Give a fraction in lowest terms.\n\nGive your final answer on the last line exactly as: ANSWER: <answer>",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.27,
   "wall_s": 8.37,
   "completion_tokens": 326,
   "prompt_tokens": 57,
   "decode_tok_s": 40.1,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "To determine who finishes third, let's analyze the relative positions of the five runners: Al, Bo, Cal, Dee, and Eve.\n\n1.  **Analyze the constraints:**\n    *   \"Bo finishes last.\" -> Bo is in position 5.\n    *   \"Al finishes before Cal.\" -> Al < Cal (Al has a lower position number than Cal).\n    *   \"Dee finishes before Eve but after Cal.\" -> Cal < Dee < Eve.\n\n2.  **Combine the constraints:**\n    *   From \"Al < Cal\" and \"Cal < Dee < Eve\", we can chain these together:\n        Al < Cal < Dee < Eve\n    *   We also know Bo is last (position 5).\n\n3.  **Determine the full order:**\n    *   The chain Al < Cal < Dee < Eve involves four runners.\n    *   Since Bo is in position 5, the other four runners (Al, Cal, Dee, Eve) must occupy positions 1, 2, 3, and 4.\n    *   Because their relative order is fixed as Al < Cal < Dee < Eve, their specific positions are determined:\n        *   Position 1: Al\n        *   Position 2: Cal\n        *   Position 3: Dee\n        *   Position 4: Eve\n        *   Position 5: Bo\n\n4.  **Identify the third runner:**\n    *   The runner in position 3 is Dee.\n\nANSWER: Dee",
   "id": "reason3",
   "category": "reasoning",
   "prompt": "Five runners finish a race. Dee finishes before Eve but after Cal. Bo finishes last. Al finishes before Cal. Who finishes third?\n\nGive your final answer on the last line exactly as: ANSWER: <answer>",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.29,
   "wall_s": 10.14,
   "completion_tokens": 439,
   "prompt_tokens": 83,
   "decode_tok_s": 44.5,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "To solve this problem, we can avoid the complex calculation of summing an infinite series of the bird's back-and-forth trips by focusing on the total time the bird is in the air.\n\n**Step 1: Calculate the time until the trains meet.**\n\nThe two trains are traveling toward each other. Their relative speed is the sum of their individual speeds.\n*   Speed of Train 1 ($v_1$) = $70$ km/h\n*   Speed of Train 2 ($v_2$) = $80$ km/h\n*   Relative speed ($v_{rel}$) = $v_1 + v_2 = 70 + 80 = 150$ km/h\n\nThe initial distance between the trains ($d$) is $300$ km.\n\nThe time ($t$) it takes for the trains to meet is given by:\n$$ t = \\frac{d}{v_{rel}} $$\n$$ t = \\frac{300 \\text{ km}}{150 \\text{ km/h}} $$\n$$ t = 2 \\text{ hours} $$\n\n**Step 2: Calculate the distance the bird flies.**\n\nThe bird is flying continuously from the moment the trains start until the moment they meet. Therefore, the bird is in the air for exactly the same amount of time as it takes for the trains to meet, which is $2$ hours.\n\n*   Speed of the bird ($v_{bird}$) = $120$ km/h\n*   Time flying ($t$) = $2$ hours\n\nThe total distance ($d_{bird}$) the bird flies is:\n$$ d_{bird} = v_{bird} \\times t $$\n$$ d_{bird} = 120 \\text{ km/h} \\times 2 \\text{ h} $$\n$$ d_{bird} = 240 \\text{ km} $$\n\n**Conclusion:**\n\nThe bird flies a total distance of 240 km.\n\nANSWER: 240",
   "id": "reason4",
   "category": "reasoning",
   "prompt": "Two trains 300 km apart travel toward each other at 70 km/h and 80 km/h. A bird flying at 120 km/h goes back and forth between them until they meet. How many km does the bird fly?\n\nGive your final answer on the last line exactly as: ANSWER: <answer>",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.25,
   "wall_s": 14.55,
   "completion_tokens": 681,
   "prompt_tokens": 47,
   "decode_tok_s": 47.5,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "To find the remainder when $7^{100}$ is divided by 5, we can use modular arithmetic.\n\n**Step 1: Simplify the base modulo 5**\nFirst, we look at the base, 7, modulo 5.\n$$ 7 \\equiv 2 \\pmod{5} $$\nTherefore:\n$$ 7^{100} \\equiv 2^{100} \\pmod{5} $$\n\n**Step 2: Use Fermat's Little Theorem**\nFermat's Little Theorem states that if $p$ is a prime number and $a$ is an integer not divisible by $p$, then:\n$$ a^{p-1} \\equiv 1 \\pmod{p} $$\nHere, $p = 5$ and $a = 2$. Since 5 is prime and 2 is not divisible by 5, we have:\n$$ 2^{5-1} \\equiv 1 \\pmod{5} $$\n$$ 2^4 \\equiv 1 \\pmod{5} $$\n\n**Step 3: Simplify the exponent**\nWe need to calculate $2^{100} \\pmod{5}$. We can express the exponent 100 as a multiple of 4:\n$$ 100 = 4 \\times 25 $$\nSo,\n$$ 2^{100} = (2^4)^{25} $$\nSubstituting the congruence from Step 2:\n$$ (2^4)^{25} \\equiv 1^{25} \\pmod{5} $$\n$$ 1^{25} = 1 $$\nThus,\n$$ 2^{100} \\equiv 1 \\pmod{5} $$\n\n**Alternative Method: Pattern Recognition**\nLet's look at the powers of 7 modulo 5:\n- $7^1 = 7 \\equiv 2 \\pmod{5}$\n- $7^2 = 49 \\equiv 4 \\equiv -1 \\pmod{5}$\n- $7^3 = 7^2 \\cdot 7 \\equiv -1 \\cdot 2 = -2 \\equiv 3 \\pmod{5}$\n- $7^4 = 7^3 \\cdot 7 \\equiv 3 \\cdot 2 = 6 \\equiv 1 \\pmod{5}$\n\nThe powers of 7 modulo 5 repeat in a cycle of 4: $\\{2, 4, 3, 1\\}$.\nSince the exponent is 100, and $100$ is divisible by 4 ($100 = 4 \\times 25$), the remainder corresponds to the last term in the cycle, which is 1.\n$$ 7^{100} = (7^4)^{25} \\equiv 1^{25} \\equiv 1 \\pmod{5} $$\n\n**Conclusion**\nThe remainder when $7^{100}$ is divided by 5 is 1.\n\nANSWER: 1",
   "id": "reason5",
   "category": "reasoning",
   "prompt": "What is the remainder when 7^100 is divided by 5?\n\nGive your final answer on the last line exactly as: ANSWER: <answer>",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.3,
   "wall_s": 1.59,
   "completion_tokens": 66,
   "prompt_tokens": 99,
   "decode_tok_s": 50.4,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "{\n  \"invoice_id\": 4471,\n  \"customer\": \"Marta Ruiz\",\n  \"issued\": \"2026-03-14\",\n  \"amount\": 1250.50,\n  \"due_days\": 30\n}",
   "id": "json1",
   "category": "json",
   "prompt": "Extract into a JSON object with keys invoice_id (integer), customer (string), issued (ISO date string), amount (number), due_days (integer):\n\n\"Invoice 4471 was issued to Marta Ruiz on 2026-03-14 for $1,250.50, due in 30 days.\"\n\nOutput only the JSON, no prose, no code fences.",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.26,
   "wall_s": 1.56,
   "completion_tokens": 67,
   "prompt_tokens": 63,
   "decode_tok_s": 51.0,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "[\n  {\n    \"name\": \"apple\",\n    \"qty\": 3,\n    \"price\": 0.5\n  },\n  {\n    \"name\": \"pear\",\n    \"qty\": 2,\n    \"price\": 0.75\n  }\n]",
   "id": "json2",
   "category": "json",
   "prompt": "Convert this CSV to a JSON array of objects with numeric qty and price:\n\nname,qty,price\napple,3,0.5\npear,2,0.75\n\nOutput only the JSON, no prose, no code fences.",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.27,
   "wall_s": 0.73,
   "completion_tokens": 21,
   "prompt_tokens": 58,
   "decode_tok_s": 43.5,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "{\"user\": \"sam\", \"tags\": [\"a\", \"b\"], \"active\": true}",
   "id": "json3",
   "category": "json",
   "prompt": "Fix this invalid JSON and output only the corrected JSON:\n\n{'user': 'sam', 'tags': ['a', 'b',], 'active': True}\n\nOutput only the JSON, no prose, no code fences.",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.3,
   "wall_s": 0.92,
   "completion_tokens": 30,
   "prompt_tokens": 86,
   "decode_tok_s": 47.1,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "{\"Oslo\": 4.0, \"Cairo\": 31.0, \"Lima\": 19.5}",
   "id": "json4",
   "category": "json",
   "prompt": "Return a JSON object mapping each city to the arithmetic mean of its temperatures:\n\n{\"Oslo\": [2, 4, 6], \"Cairo\": [30, 32], \"Lima\": [18, 19, 20, 21]}\n\nOutput only the JSON, no prose, no code fences.",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.29,
   "wall_s": 1.14,
   "completion_tokens": 38,
   "prompt_tokens": 76,
   "decode_tok_s": 43.6,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "{\"id\": 7, \"name\": \"Widget\", \"price\": 19.99, \"in_stock\": true, \"tags\": [\"tools\", \"home\"]}",
   "id": "json5",
   "category": "json",
   "prompt": "Produce a JSON object with exactly these keys and values: id = integer 7, name = string \"Widget\", price = number 19.99, in_stock = boolean true, tags = array of strings [\"tools\", \"home\"].\n\nOutput only the JSON, no prose, no code fences.",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.28,
   "wall_s": 15.82,
   "completion_tokens": 750,
   "prompt_tokens": 71,
   "decode_tok_s": 48.2,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "```html\n<!DOCTYPE html>\n<html lang=\"en\">\n<head>\n    <meta charset=\"UTF-8\">\n    <meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\">\n    <title>Spark Bench</title>\n    <style>\n        * {\n            margin: 0;\n            padding: 0;\n            box-sizing: border-box;\n        }\n\n        body {\n            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;\n            background: #0a0a0f;\n            color: #e0e0e0;\n            min-height: 100vh;\n        }\n\n        header {\n            background: linear-gradient(135deg, #1a1a2e 0%, #16213e 100%);\n            padding: 1.5rem 2rem;\n            border-bottom: 2px solid #e94560;\n            display: flex;\n            align-items: center;\n            justify-content: space-between;\n            flex-wrap: wrap;\n            gap: 1rem;\n        }\n\n        h1 {\n            font-size: 1.8rem;\n            font-weight: 700;\n            color: #e94560;\n            letter-spacing: 1px;\n        }\n\n        nav {\n            display: flex;\n            gap: 1.5rem;\n        }\n\n        nav a {\n            color: #a0a0b8;\n            text-decoration: none;\n            font-size: 1rem;\n            font-weight: 500;\n            padding: 0.4rem 0.8rem;\n            border-radius: 4px;\n            transition: color 0.2s, background 0.2s;\n        }\n\n        nav a:hover {\n            color: #ffffff;\n            background: rgba(233, 69, 96, 0.15);\n        }\n\n        main {\n            max-width: 800px;\n            margin: 3rem auto;\n            padding: 0 2rem;\n        }\n\n        #summary {\n            background: #12121a;\n            border: 1px solid #2a2a3a;\n            border-radius: 8px;\n            padding: 2rem;\n            line-height: 1.7;\n        }\n\n        #summary p {\n            font-size: 1.05rem;\n            color: #c0c0d0;\n        }\n    </style>\n</head>\n<body>\n    <header>\n        <h1>Spark Bench</h1>\n        <nav>\n            <a href=\"#home\">Home</a>\n            <a href=\"#results\">Results</a>\n            <a href=\"#method\">Method</a>\n        </nav>\n    </header>\n    <main>\n        <section id=\"summary\">\n            <p>Spark Bench is a lightweight benchmarking suite designed to measure and compare the performance of data processing pipelines across various workloads, helping developers identify bottlenecks and optimize throughput.</p>\n        </section>\n    </main>\n</body>\n</html>\n```",
   "id": "html1",
   "category": "html",
   "prompt": "Write a complete HTML5 page: a <header> containing an <h1> that reads Spark Bench and a <nav> with three links (Home, Results, Method), then a <main> containing a <section id=\"summary\"> with one paragraph.\n\nOutput only the HTML.",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.29,
   "wall_s": 3.58,
   "completion_tokens": 163,
   "prompt_tokens": 81,
   "decode_tok_s": 49.3,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "```html\n<table>\n  <thead>\n    <tr>\n      <th>Lane</th>\n      <th>Decode tok/s</th>\n      <th>TTFT s</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <td>NVFP4</td>\n      <td>64.0</td>\n      <td>1.54</td>\n    </tr>\n    <tr>\n      <td>EXL3</td>\n      <td>61.5</td>\n      <td>0.52</td>\n    </tr>\n  </tbody>\n</table>\n```",
   "id": "html2",
   "category": "html",
   "prompt": "Write an HTML <table> with a <thead> row of Lane, Decode tok/s, TTFT s and a <tbody> with two rows: NVFP4, 64.0, 1.54 and EXL3, 61.5, 0.52.\n\nOutput only the HTML.",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.27,
   "wall_s": 3.4,
   "completion_tokens": 141,
   "prompt_tokens": 67,
   "decode_tok_s": 44.8,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "```html\n<form>\n  <label for=\"email\">Email:</label>\n  <input type=\"email\" id=\"email\" name=\"email\" required>\n\n  <label for=\"lane\">Lane:</label>\n  <select id=\"lane\" name=\"lane\">\n    <option value=\"NVFP4\">NVFP4</option>\n    <option value=\"EXL3\">EXL3</option>\n  </select>\n\n  <label for=\"notes\">Notes:</label>\n  <textarea id=\"notes\" name=\"notes\"></textarea>\n\n  <button type=\"submit\">Submit</button>\n</form>\n```",
   "id": "html3",
   "category": "html",
   "prompt": "Write an HTML <form> with: a required email input with id=\"email\", a <select id=\"lane\"> with the options NVFP4 and EXL3, a <textarea id=\"notes\">, and a submit <button>.\n\nOutput only the HTML.",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.27,
   "wall_s": 2.55,
   "completion_tokens": 106,
   "prompt_tokens": 68,
   "decode_tok_s": 46.2,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "```html\n<a href=\"#main\" class=\"skip\">Skip to content</a>\n<nav aria-label=\"Main\">\n  <ul>\n    <li><a href=\"#home\">Home</a></li>\n    <li><a href=\"#about\">About</a></li>\n    <li><a href=\"#services\">Services</a></li>\n    <li><a href=\"#contact\">Contact</a></li>\n  </ul>\n</nav>\n```",
   "id": "html4",
   "category": "html",
   "prompt": "Write an accessible site navigation: a skip link <a href=\"#main\" class=\"skip\">Skip to content</a>, then <nav aria-label=\"Main\"> containing a <ul> of four <li> items each with an <a>.\n\nOutput only the HTML.",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.27,
   "wall_s": 17.59,
   "completion_tokens": 846,
   "prompt_tokens": 66,
   "decode_tok_s": 48.8,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "```html\n<!DOCTYPE html>\n<html lang=\"en\">\n<head>\n  <meta charset=\"UTF-8\">\n  <meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\">\n  <title>Card Component</title>\n  <style>\n    * {\n      margin: 0;\n      padding: 0;\n      box-sizing: border-box;\n    }\n\n    body {\n      font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, sans-serif;\n      background-color: #f0f2f5;\n      display: flex;\n      justify-content: center;\n      align-items: center;\n      min-height: 100vh;\n      padding: 20px;\n    }\n\n    .card {\n      background: #ffffff;\n      border-radius: 12px;\n      overflow: hidden;\n      box-shadow: 0 4px 6px rgba(0, 0, 0, 0.07), 0 10px 24px rgba(0, 0, 0, 0.05);\n      max-width: 360px;\n      width: 100%;\n      transition: transform 0.2s ease, box-shadow 0.2s ease;\n    }\n\n    .card:hover {\n      transform: translateY(-4px);\n      box-shadow: 0 8px 12px rgba(0, 0, 0, 0.1), 0 16px 32px rgba(0, 0, 0, 0.08);\n    }\n\n    .card img {\n      width: 100%;\n      height: 200px;\n      object-fit: cover;\n      display: block;\n    }\n\n    .card h2 {\n      font-size: 1.25rem;\n      font-weight: 600;\n      color: #1a1a2e;\n      padding: 16px 20px 8px;\n      line-height: 1.4;\n    }\n\n    .card p {\n      font-size: 0.95rem;\n      color: #555;\n      padding: 0 20px 16px;\n      line-height: 1.6;\n    }\n\n    .card .btn {\n      display: inline-block;\n      margin: 0 20px 20px;\n      padding: 10px 24px;\n      background-color: #4361ee;\n      color: #ffffff;\n      text-decoration: none;\n      font-size: 0.9rem;\n      font-weight: 500;\n      border-radius: 6px;\n      transition: background-color 0.2s ease;\n    }\n\n    .card .btn:hover {\n      background-color: #3a56d4;\n    }\n  </style>\n</head>\n<body>\n  <div class=\"card\">\n    <img src=\"https://images.unsplash.com/photo-1506744038136-46273834b3fb?w=400&h=200&fit=crop\" alt=\"A scenic mountain landscape with a lake reflecting the peaks\">\n    <h2>Explore the Wilderness</h2>\n    <p>Discover breathtaking trails and serene landscapes perfect for your next adventure. Immerse yourself in nature's beauty.</p>\n    <a href=\"#\" class=\"btn\">Learn More</a>\n  </div>\n</body>\n</html>\n```",
   "id": "html5",
   "category": "html",
   "prompt": "Write an HTML card component with an inline <style> block: a <div class=\"card\"> containing an <img> with an alt attribute, an <h2>, a <p>, and an <a class=\"btn\">.\n\nOutput only the HTML.",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.25,
   "wall_s": 7.46,
   "completion_tokens": 203,
   "prompt_tokens": 38,
   "decode_tok_s": 28.0,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "Imagine you are trying to solve a massive math problem, but your brain is too small to hold all the numbers at once. Tensor parallelism is a strategy used in artificial intelligence to solve this exact problem by splitting the work across multiple powerful computer chips, called GPUs.\n\nIn a neural network, data flows through layers represented as giant grids of numbers, known as tensors. Instead of forcing one GPU to process an entire layer, tensor parallelism slices these grids into smaller chunks. Each GPU handles a specific slice simultaneously. For example, if a layer is a 100x100 grid, one GPU might calculate the left half while another calculates the right half.\n\nAfter computing their respective parts, the GPUs quickly communicate to combine their results, ensuring the final output is accurate. This method allows us to train huge AI models that would otherwise be impossible on a single device. It is essentially teamwork for computers, enabling faster processing and the creation of more intelligent systems by distributing the heavy computational load efficiently.",
   "id": "prose1",
   "category": "prose",
   "prompt": "Explain what tensor parallelism is to a smart high-school student, in 120 to 180 words.",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.27,
   "wall_s": 5.81,
   "completion_tokens": 146,
   "prompt_tokens": 54,
   "decode_tok_s": 26.2,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "Experience seamless AI development with our compact workstation, engineered for professionals who demand power without bulk. Featuring 128 GB of unified memory, this system allows you to run large language models and complex neural networks locally, eliminating latency and cloud dependency. The unified architecture ensures efficient data sharing between CPU and GPU, significantly accelerating training and inference tasks. Despite its high-performance capabilities, the sleek, space-saving design fits effortlessly on any desk, making it ideal for studios, labs, or home offices. Enjoy quiet operation and robust thermal management, ensuring sustained performance during intensive workloads. Whether you are fine-tuning models or generating content, this workstation delivers the reliability and speed needed to keep your creative and technical workflows moving forward without interruption.",
   "id": "prose2",
   "category": "prose",
   "prompt": "Write a product description of 80 to 120 words for a compact AI workstation with 128 GB of unified memory. Do not use the words revolutionary, game-changing, or unleash.",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.24,
   "wall_s": 4.42,
   "completion_tokens": 174,
   "prompt_tokens": 36,
   "decode_tok_s": 41.4,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "Subject: Re: Meeting Request\n\nDear [Name],\n\nThank you for reaching out and inviting me to discuss [Topic]. I appreciate the opportunity to connect.\n\nUnfortunately, I am unable to meet during the originally proposed time due to prior commitments. However, I am very interested in finding a time that works for both of us. Would either of the following slots next week suit your schedule?\n\n*   Tuesday, [Date], between 10:00 AM and 11:00 AM\n*   Thursday, [Date], between 2:00 PM and 3:00 PM\n\nPlease let me know if either of these options works for you, or if you would prefer to suggest another time. I look forward to speaking with you soon.\n\nBest regards,\n\n[Your Name]\n[Your Job Title]",
   "id": "prose3",
   "category": "prose",
   "prompt": "Write a professional email under 150 words politely declining a meeting request and proposing two specific alternative times next week.",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.26,
   "wall_s": 8.67,
   "completion_tokens": 250,
   "prompt_tokens": 41,
   "decode_tok_s": 29.6,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "Benchmarking language models with synthetic prompts is a flawed and misleading practice that undermines the integrity of AI evaluation. While synthetic data offers scalability and cost-efficiency, it fundamentally fails to capture the nuanced, chaotic, and context-dependent nature of real human interaction. Real-world users employ sarcasm, ambiguity, cultural references, and evolving slang in ways that algorithmically generated prompts rarely replicate authentically. Consequently, models optimized for synthetic benchmarks often exhibit \"benchmark overfitting,\" where they perform exceptionally well on controlled tests but collapse when faced with the unpredictable variability of actual user queries.\n\nFurthermore, synthetic prompts often reflect the biases and logical structures of their creators, creating an echo chamber that reinforces existing model limitations rather than exposing them. This leads to inflated performance metrics that do not translate to practical utility. True robustness requires evaluation against diverse, organic datasets that include edge cases, adversarial inputs, and genuine user intent. Relying on synthetic benchmarks creates a false sense of security, encouraging developers to prioritize metric manipulation over genuine capability improvement. To ensure AI systems are truly reliable and safe, the industry must prioritize high-quality, human-centric evaluation frameworks that reflect the messy reality of human communication, rather than retreating into the sterile, controlled environment of synthetic data.",
   "id": "prose4",
   "category": "prose",
   "prompt": "In 150 to 200 words, argue for or against benchmarking language models with synthetic prompts. Take one side clearly.",
   "score": 0.0,
   "fails": [
    "words 203 in 150-200"
   ]
  },
  {
   "ttft_s": 0.28,
   "wall_s": 6.84,
   "completion_tokens": 194,
   "prompt_tokens": 50,
   "decode_tok_s": 29.4,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "When using a chat assistant, the delay before the first word appears, known as time to first token, is far more critical than the speed at which subsequent words stream out. This initial pause determines whether the interaction feels responsive or sluggish. If the system takes too long to start, users perceive the AI as unresponsive, leading to frustration and a sense of disconnection, regardless of how fast the rest of the answer arrives.\n\nThink of it like waiting for a friend to start talking in a conversation. If they stare at you silently for ten seconds before speaking, you feel ignored and awkward, even if they speak rapidly once they finally begin. That initial silence breaks the natural flow of dialogue. In contrast, a quick start creates an immediate sense of engagement and presence. Therefore, minimizing that initial latency is essential for maintaining a smooth, human-like conversational rhythm, ensuring users feel heard and attended to instantly rather than left wondering if the system is working at all.",
   "id": "prose5",
   "category": "prose",
   "prompt": "In 100 to 150 words, explain in plain language why time to first token matters more than tokens per second for a chat assistant. Use exactly one concrete analogy.",
   "score": 0.0,
   "fails": [
    "words 168 in 100-150"
   ]
  },
  {
   "ttft_s": 0.27,
   "wall_s": 10.88,
   "completion_tokens": 337,
   "prompt_tokens": 53,
   "decode_tok_s": 31.7,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "The rain hammered against the roof of the abandoned lighthouse, a relentless rhythm that matched the pounding in my chest. I held the flickering **lantern** high, its weak beam cutting through the thick, damp fog that had swallowed the island whole. My fingers trembled as I reached for the heavy, leather-bound **ledger** resting on the dusty desk. It was the only thing left behind by the previous keeper, a man whose name had been erased from every official record.\n\n\"Is it really here?\" I whispered, my voice barely audible over the storm.\n\n\"It\u2019s always been here,\" a voice replied from the shadows behind me.\n\nI spun around, heart racing, but the room remained empty. The **thunder** cracked overhead, shaking the very foundations of the tower. I looked back at the ledger, my curiosity overriding my fear. I opened it to the final entry, dated just three days ago. The handwriting was jagged, frantic, and unmistakably mine.\n\n*Day 42,* it read. *The fog is getting thicker. I can no longer distinguish between the living and the dead. I am not the keeper. I am the ghost.*\n\nA cold chill swept through me, far colder than the sea breeze. I looked down at my hands, expecting to see skin, but instead, I saw only translucent mist swirling around the lantern\u2019s handle. The voice hadn\u2019t come from behind me; it had come from within. I wasn\u2019t searching for the truth. I was the truth, trapped in a loop of my own making, waiting for the next lost soul to pick up the book and take my place.",
   "id": "story1",
   "category": "narrative",
   "prompt": "Write a 150 to 250 word short story in first person that includes the words lantern, ledger and thunder, contains at least two lines of dialogue, and ends with a twist.",
   "score": 0.8,
   "fails": [
    "words 264 in 150-250"
   ]
  },
  {
   "ttft_s": 0.25,
   "wall_s": 9.93,
   "completion_tokens": 281,
   "prompt_tokens": 45,
   "decode_tok_s": 28.9,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "A clever fox, known for his silver tongue, stumbled upon a magnificent golden apple resting on a high branch. He tried to jump, but his paws slipped. He tried to climb, but the bark was too smooth. Frustrated, he noticed a weary old bear sitting nearby, struggling to lift a heavy log. The fox approached with a charming smile. \"Dear Bear,\" he said, \"I see you are strong but burdened. If you lift that log, I will show you a secret path to a river full of fresh salmon, far easier to catch than any fish in this forest.\" The bear, hungry and tired, agreed. He lifted the log with great effort, revealing a hidden trail. The fox, however, had no intention of sharing the secret. He simply pointed vaguely into the distance and scampered away, leaving the bear confused and empty-handed. Days later, the fox returned to the same spot, hoping to find another victim. But the bear was gone, and the forest was silent. The fox realized that while he had gained a momentary advantage, he had lost all trust. No animal would help him again, and his cleverness had isolated him completely. He sat alone, hungry and regretful, understanding that true strength lies in community, not deception. Moral: Deception may bring short-term gain, but it ultimately leads to isolation and loss.",
   "id": "story2",
   "category": "narrative",
   "prompt": "Write a 120 to 200 word fable with a talking fox. State the moral in the final sentence, starting with the word Moral:",
   "score": 0.6666666666666666,
   "fails": [
    "words 224 in 120-200"
   ]
  },
  {
   "ttft_s": 0.26,
   "wall_s": 15.72,
   "completion_tokens": 448,
   "prompt_tokens": 53,
   "decode_tok_s": 28.9,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "The fluorescent hum of the server room was the only sound besides their ragged breathing.\n\n\"It\u2019s a fluke, Marcus. Just a fluke.\"\n\n\"Flukes don\u2019t replicate three times in a row, Sarah.\"\n\n\"Check the thermal throttling logs again. I bet the CPU hit ninety degrees and downclocked.\"\n\n\"I checked. It stayed at seventy-two. Look at the graph.\"\n\nSarah squinted at the monitor, her eyes burning from the blue light. \"That\u2019s impossible. The latency dropped by forty percent. That\u2019s not optimization; that\u2019s magic.\"\n\n\"It\u2019s the new memory allocator. I told you the pointer arithmetic was cleaner.\"\n\n\"You rewrote the core loop in assembly? At two in the morning?\"\n\n\"Efficiency doesn\u2019t care about the clock, Sarah.\"\n\n\"Efficiency cares about maintainability. If I can\u2019t read it, I can\u2019t fix it when it breaks.\"\n\n\"It won\u2019t break. It\u2019s deterministic.\"\n\n\"Everything breaks eventually. You\u2019re trading clarity for speed, and you\u2019re doing it on a production branch.\"\n\n\"Look at the throughput. We\u2019re hitting the target. The client wants speed, not pretty code.\"\n\n\"The client wants code that doesn\u2019t crash during their demo next week.\"\n\nMarcus leaned back, rubbing his temples. \"I can add comments. I can document the register usage.\"\n\n\"You can\u2019t document intuition. You just guessed the cache line alignment.\"\n\n\"I measured it. I profiled it. I didn\u2019t guess.\"\n\nSarah pulled up the profiler output, her fingers flying across the mechanical keyboard. \"Okay. Show me the branch prediction misses.\"\n\n\"Here. Look at the drop-off after the loop unrolling.\"\n\nShe stared at the numbers, her anger slowly replaced by reluctant curiosity. \"That\u2019s... actually impressive.\"\n\n\"Thank you.\"\n\n\"Don\u2019t thank me yet. If this causes a race condition in the multi-threaded environment, I\u2019m reverting it.\"\n\n\"Run the stress test. I\u2019ll wait.\"\n\n\"You\u2019re insufferable.\"\n\n\"I\u2019m right.\"\n\n\"Run the test, Marcus. Before I throw this keyboard at you.\"",
   "id": "story3",
   "category": "narrative",
   "prompt": "Write a 200 to 300 word scene: two engineers arguing at 2 a.m. about a benchmark result. Mostly dialogue; no narration longer than one sentence at a time.",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.26,
   "wall_s": 7.4,
   "completion_tokens": 192,
   "prompt_tokens": 45,
   "decode_tok_s": 26.8,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "The hum dies. Silence crashes into the room like a physical weight, heavier than the racks of servers surrounding you. You stand frozen in the aisle, the emergency lights flickering to life, casting long, jagged shadows across the cold concrete floor. The air conditioning has stopped; the heat begins to rise, a slow, suffocating tide. You can hear your own heartbeat, loud and frantic, echoing in the sudden void.\n\nYou reach for your phone, but the screen remains black, a dead mirror reflecting your pale face. Panic tightens your chest. You are alone in the belly of the machine, surrounded by millions of sleeping thoughts, now silent. The backup generators fail to kick in. You press your hand against the nearest server rack, feeling the residual warmth of data that no longer flows. In this darkness, you realize you are not the operator anymore. You are just another component, waiting for a signal that may never return.",
   "id": "story4",
   "category": "narrative",
   "prompt": "Write a 100 to 150 word micro-story told entirely in second person, present tense, set in a data center during a power outage.",
   "score": 0.5,
   "fails": [
    "words 157 in 100-150"
   ]
  },
  {
   "ttft_s": 0.25,
   "wall_s": 16.07,
   "completion_tokens": 458,
   "prompt_tokens": 44,
   "decode_tok_s": 28.9,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "Bolt was a shiny, silver robot with bright blue eyes and a very fast processor. He loved to zoom around the garden, chasing butterflies and helping his friend, Mia, water her flowers. Bolt\u2019s internal clock ticked loudly, reminding him that every second was precious. He believed that waiting was a waste of time because he could calculate the perfect moment to act in a blink of an eye. One sunny afternoon, Mia asked Bolt to help her plant a tiny sunflower seed. \"Just put it in the dirt and watch it grow!\" Bolt said, tapping his metal foot impatiently. He wanted to see the big yellow flower right away, but Mia gently shook her head. \"Nature has its own speed, Bolt,\" she explained. \"We must be patient and let the earth do its work.\"\n\nBolt felt confused. His circuits buzzed with frustration as he watched the small mound of dirt. He tried to speed up the process by singing loud songs to the seed, but nothing happened. He tried to dig it up to check on it, but Mia stopped him just in time. \"If you disturb the roots, it might not grow,\" she warned. Bolt sat down heavily, his gears whirring softly. He watched the clouds drift slowly across the blue sky. For the first time, he noticed how the wind rustled the leaves and how the bees hummed a gentle tune. He realized that the world was beautiful even when nothing was happening quickly. He learned that silence could be peaceful, not empty.\n\nDays passed, and Bolt practiced waiting. He didn\u2019t zoom or tap his foot. Instead, he watched the sun rise and set, counting the stars at night. One morning, a tiny green sprout poked through the soil. Bolt\u2019s eyes widened with wonder. It was small, but it was real. He smiled, understanding that good things take time. He had learned that waiting wasn\u2019t about doing nothing; it was about trusting the process. Now, when Mia asked him to wait, Bolt didn\u2019t complain. He simply watched, listened, and appreciated the quiet magic of growing things. He was no longer just a fast robot; he was a patient friend, ready for whatever came next, no matter how long it took.",
   "id": "story5",
   "category": "narrative",
   "prompt": "Write a 150 to 250 word story for children aged 6 to 8 about a robot learning to wait. Exactly three paragraphs.",
   "score": 0.5,
   "fails": [
    "words 372 in 150-250"
   ]
  },
  {
   "ttft_s": 0.24,
   "wall_s": 0.85,
   "completion_tokens": 24,
   "prompt_tokens": 35,
   "decode_tok_s": 37.6,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "I cannot summarize the notes because the document content is missing. Please provide the text you would like me to summarize.",
   "id": "sum1",
   "category": "summary",
   "prompt": "Summarize the following notes in exactly 3 bullet points, each one sentence.\n\n---\n(document missing)",
   "score": 0.0,
   "fails": [
    "bullets=3"
   ]
  },
  {
   "ttft_s": 0.22,
   "wall_s": 1.44,
   "completion_tokens": 45,
   "prompt_tokens": 35,
   "decode_tok_s": 36.0,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "The provided text indicates that the document is missing. Consequently, there is no content available to summarize. Please provide the actual report text so that a concise summary of at most 80 words can be generated as requested.",
   "id": "sum2",
   "category": "summary",
   "prompt": "Summarize the following report in one paragraph of at most 80 words.\n\n---\n(document missing)",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.24,
   "wall_s": 1.23,
   "completion_tokens": 31,
   "prompt_tokens": 32,
   "decode_tok_s": 30.2,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "The provided text is missing, so it contains no information regarding quality. Consequently, it is impossible to summarize any statements about quality from the absent document.",
   "id": "sum3",
   "category": "summary",
   "prompt": "In exactly two sentences, summarize what the following text says about quality.\n\n---\n(document missing)",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.23,
   "wall_s": 1.37,
   "completion_tokens": 38,
   "prompt_tokens": 35,
   "decode_tok_s": 32.4,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "What: The document content is missing, so a summary cannot be generated.\nHow: Please provide the actual README text or file content to enable summarization.\nCredits: N/A",
   "id": "sum4",
   "category": "summary",
   "prompt": "Summarize the following README in 3 bullets labeled What, How, Credits.\n\n---\n(document missing)",
   "score": 0.75,
   "fails": [
    "bullets=3"
   ]
  },
  {
   "ttft_s": 0.23,
   "wall_s": 0.31,
   "completion_tokens": 4,
   "prompt_tokens": 39,
   "decode_tok_s": 39.1,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "(document missing)",
   "id": "sum5",
   "category": "summary",
   "prompt": "Turn the following into a single tweet of at most 280 characters. Output only the tweet.\n\n---\n(document missing)",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.24,
   "wall_s": 0.62,
   "completion_tokens": 21,
   "prompt_tokens": 34,
   "decode_tok_s": 53.3,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "53\n59\n61\n67\n71\n73\n79",
   "id": "fmt1",
   "category": "format",
   "prompt": "List exactly 7 prime numbers greater than 50, one per line, ascending. Output nothing else.",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.28,
   "wall_s": 1.71,
   "completion_tokens": 72,
   "prompt_tokens": 81,
   "decode_tok_s": 49.7,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "| Lane | Context | KV pool |\n| :--- | :--- | :--- |\n| NVFP4 | 262,144 | 295,230 |\n| EXL3 | 1,048,576 | 1,396,551 |",
   "id": "fmt2",
   "category": "format",
   "prompt": "Output a markdown table with the columns Lane | Context | KV pool and two rows: NVFP4 with 262,144 and 295,230; EXL3 with 1,048,576 and 1,396,551. Output nothing else.",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.24,
   "wall_s": 0.53,
   "completion_tokens": 10,
   "prompt_tokens": 45,
   "decode_tok_s": 31.2,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "dog lazy the over jumps fox brown quick the",
   "id": "fmt3",
   "category": "format",
   "prompt": "Reply with the sentence 'The quick brown fox jumps over the lazy dog' with the words in reverse order, all lowercase, no punctuation. Output only the result.",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.25,
   "wall_s": 1.17,
   "completion_tokens": 21,
   "prompt_tokens": 36,
   "decode_tok_s": 21.8,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "To free RAM for model weights, preventing OOM errors and avoiding costly swap thrashing during inference.",
   "id": "fmt4",
   "category": "format",
   "prompt": "In at most 20 words: why should a unified-memory machine drop its page cache before loading a large model?",
   "score": 1.0,
   "fails": []
  },
  {
   "ttft_s": 0.25,
   "wall_s": 1.15,
   "completion_tokens": 20,
   "prompt_tokens": 39,
   "decode_tok_s": 21.2,
   "reasoning_chars": 0,
   "finish": "stop",
   "output": "Whirring blades spin fast\nCooling down the hot silicon\nSilence falls at last",
   "id": "fmt5",
   "category": "format",
   "prompt": "Write a haiku about a GPU fan: three lines, 5-7-5 syllables. Output only the three lines.",
   "score": 1.0,
   "fails": []
  }
 ],
 "ts": "2026-09-06 15:50"
}