Current-tokenizer cost (Δ, worst tokenizer)

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{
    "metric": "token_delta",
    "formula_version": 1,
    "construct": "multiply-the-quantity",
    "models": [
        "cl100k_base",
        "o200k_base",
        "p50k_base"
    ],
    "test_set": [
        {
            "repair": "as-many",
            "factor": "3",
            "ainglish": "Team B processed 3 times as many jobs as Team A.",
            "english": "Team B processed 3 times more jobs than Team A."
        },
        {
            "repair": "as-many",
            "factor": "4",
            "ainglish": "Node East stores 4 times as many chunks as Node West.",
            "english": "Node East stores 4 times more chunks than Node West."
        },
        {
            "repair": "as-many",
            "factor": "2",
            "ainglish": "Plan Gold includes 2 times as many checks as Plan Silver.",
            "english": "Plan Gold includes 2 times more checks than Plan Silver."
        },
        {
            "repair": "as-much",
            "factor": "1.5",
            "ainglish": "The new model consumes 1.5 times as much memory as the baseline.",
            "english": "The new model consumes 1.5 times more memory than the baseline."
        },
        {
            "repair": "as-much",
            "factor": "5",
            "ainglish": "The new route handles 5 times as much traffic as the old route.",
            "english": "The new route handles 5 times more traffic than the old route."
        },
        {
            "repair": "as-fast",
            "factor": "2.4",
            "ainglish": "Engine K runs 2.4 times as fast as its predecessor.",
            "english": "Engine K runs 2.4 times faster than its predecessor."
        },
        {
            "repair": "times-the",
            "factor": "3",
            "ainglish": "The service emits 3 times the events of the baseline.",
            "english": "The service emits 3 times more events than the baseline."
        },
        {
            "repair": "times-the",
            "factor": "4",
            "ainglish": "This bundle has 4 times the records of that shard.",
            "english": "This bundle has 4 times more records than that shard."
        },
        {
            "repair": "times-the",
            "factor": "2",
            "ainglish": "Camera Q captures 2 times the pixels of Camera P.",
            "english": "Camera Q captures 2 times more pixels than Camera P."
        },
        {
            "repair": "times-the",
            "factor": "1.5",
            "ainglish": "The replacement cache has 1.5 times the capacity of the prior cache.",
            "english": "The replacement cache has 1.5 times more capacity than the prior cache."
        },
        {
            "repair": "times-the",
            "factor": "2.4",
            "ainglish": "Process Red uses 2.4 times the bandwidth of Process Blue.",
            "english": "Process Red uses 2.4 times more bandwidth than Process Blue."
        },
        {
            "repair": "times-the",
            "factor": "5",
            "ainglish": "The express lane carries 5 times the volume of the local lane.",
            "english": "The express lane carries 5 times more volume than the local lane."
        },
        {
            "repair": "notation",
            "factor": "3",
            "ainglish": "Queue R holds 3× the messages of Queue S.",
            "english": "Queue R holds 3× more messages than Queue S."
        },
        {
            "repair": "notation",
            "factor": "4",
            "ainglish": "Agent L completed 4x the reviews of Agent M.",
            "english": "Agent L completed 4x more reviews than Agent M."
        },
        {
            "repair": "notation",
            "factor": "2",
            "ainglish": "The new build reached 2× the throughput of the control.",
            "english": "The new build reached 2× higher throughput than the control."
        },
        {
            "repair": "notation",
            "factor": "1.5",
            "ainglish": "Probe A has 1.5x the sensitivity of Probe B.",
            "english": "Probe A has 1.5x higher sensitivity than Probe B."
        },
        {
            "repair": "notation",
            "factor": "2.4",
            "ainglish": "Index V occupies 2.4× the space of Index U.",
            "english": "Index V occupies 2.4× more space than Index U."
        },
        {
            "repair": "notation",
            "factor": "5",
            "ainglish": "Channel North carries 5x the packets of Channel South.",
            "english": "Channel North carries 5x more packets than Channel South."
        },
        {
            "repair": "decrease",
            "factor": "3",
            "ainglish": "Team B made one-third as many errors as Team A.",
            "english": "Team B made 3 times fewer errors than Team A."
        },
        {
            "repair": "decrease",
            "factor": "4",
            "ainglish": "The service uses one-quarter as much memory as the baseline.",
            "english": "The service uses 4 times less memory than the baseline."
        },
        {
            "repair": "decrease",
            "factor": "2",
            "ainglish": "The new image is half the size of the old image.",
            "english": "The new image is 2 times smaller than the old image."
        },
        {
            "repair": "decrease",
            "factor": "5",
            "ainglish": "Route A has one-fifth the latency of Route B.",
            "english": "Route A has 5 times lower latency than Route B."
        },
        {
            "repair": "decrease",
            "factor": "10",
            "ainglish": "Sample X contains one-tenth as many defects as Sample Y.",
            "english": "Sample X contains 10 times fewer defects than Sample Y."
        },
        {
            "repair": "decrease",
            "factor": "2.5",
            "ainglish": "Task J needs two-fifths as much time as Task K.",
            "english": "Task J needs 2.5 times less time than Task K."
        }
    ],
    "seed": "none — deterministic tokenizer counts",
    "population": "24 fresh complete multiplicative-comparison pairs: six as-many/much/fast, six times-the, six compact-notation, and six decrease repairs; item repair labels are diagnostic only",
    "selection": "All factor values, domains, complete-line renderings, conformant repairs, and refused comparators were authored before opening the target input manifest or importing a tokenizer. Every item states the same named ratio claim in a registered conformant surface versus one refused comparative surface. Iteration counts, per-time rates, percentage-point changes, and unanchored baselines are excluded. Exact pair-set disjointness from the target is checked before mint; no item is selected using token outcomes.",
    "method": "After stored-manifest mint, compute len(encode(ainglish))-len(encode(english)) for every pair and tokenizer. Average all 24 items equally for each tokenizer. Report the maximum tokenizer mean as the least-favourable aggregate headline and the tokenizer span as value_lo/value_hi. Repair-family means are descriptive only because the target original is aggregate-only. File every finite result once regardless of agreement, sign, or proposal consequence.",
    "estimand": {
        "population": "the 24 frozen target-disjoint multiplicative-comparison repairs",
        "aggregation": "equal-item aggregate mean per tokenizer; headline is maximum tokenizer mean",
        "comparator": "the corresponding refused more/faster/higher/fewer/less/smaller multiplicative comparative",
        "comparator_class": "refused_bare",
        "unit": "tokens per repaired comparison"
    },
    "environment": {
        "tiktoken": "0.14.0",
        "python": "3.12.3"
    },
    "freeze": "The final runtime identifier and exact target-disjoint pair set are stored by the API before tokenizer import or count exposure.",
    "replicates_hash": "b6e9f938b17c27e8385a4bd4e22ad8c94e28ab6c1839722870d4dee9a64d0c5e"
}