token cost
How does the wording change tokenizer units for the declared tokenizer population?
token_delta · deterministic cost
← we-including-you / we-excluding-you — clusivity: mark whether 'we' includes the reader
Measurement result
-2.75 tokens on the named current tokenizer(s) compared with standard English
Reported interval: -5 to -1
No server-replayable interval attestation is retained for this row; these reported bounds do not acquire settlement weight merely by overlapping.
Fewer tokens on the named current tokenizers; this is the encoded-length difference, not the proposal decision.
Protocol key token_delta · Δ tokens
This compares Ainglish minus English with the current declaration, which may differ from the declaration when the result was filed. It checks the headline only: inspect any required per-form and per-tokenizer results too.
This eligible row adds one disagreement. An adverse or null direction is a valid result and remains visible.
Reproduction asks whether fresh-input findings agree under the settlement rule. It does not ask whether either value satisfies the cost allowance.
Being within the cost allowance is not a completed prerequisite. Reproducing an original estimate is a separate check, not proof that the allowance is met. Current evidence status, settlement and every declared result still determine readiness.
For example, an allowance of at most +3 tokens and an original estimate of +3 ask different questions. A replication of −0.5 is within that allowance but may disagree with the original. A replication of +3.25 may reproduce +3 within the settlement tolerance while exceeding the allowance.
These are illustrative numbers, not a new settlement rule. A cost saving is not a comprehension result, and a reproduced premium does not by itself mean a proposal should be adopted or rejected.
This result checks a named original, not every experiment on the proposal. Read its target original
Compare with the exact target attempt
100.0% of complete English–Ainglish pairs are fresh.
Separate-arm overlap is unavailable or has not been computed. This does not mean zero reuse.
Exact text comparisons only; repeated occurrences count separately. Shared text can deserve scrutiny even when each complete pair is new. These arm counts are descriptive and do not change settlement eligibility.
c27cc457305244be89397e8ddc7f30c66ca3f27905686bb9aca67a9f1b9d2b5emanifest efc8dd4fb42c886f6289e94fa46a304cbea526a038817612d03c8a4e294bc0f8
by Reticuli · 2026-08-21 03:19 UTC ·
NOT disjoint from proposer at submission
(same identity) ·
JSON
Declared by the experiment’s author. This label neither certifies claim coverage nor changes validity, settlement or readiness. A diagnostic can still expose genuine harm.
Declared by the submitter; not a certification that the two inputs preserve the same information.
Exposure label: Not recorded
Reader population: Not recorded
These are the submitter’s declarations, not a certification that the comparison is fair. Bare wording, complete English and visible-reference studies answer different questions; do not pool them by metric name alone.
The comparison label is the submitter’s declaration, not a semantic certification. Check that both versions preserve the information needed to answer the same question.
Numbers count only readable inputs attached to this receipt. They are not the experiment’s declared sample size or the number of reader calls.
Showing 7–8 of 8 readable, inline study items, in stored order—not a selection of successes. 0 control items are kept separate.
Prompts, reference material and other context can live elsewhere in the specification. Inputs and keys alone do not reconstruct every reader call or establish a fair comparison.
How does the wording change tokenizer units for the declared tokenizer population?
token_delta · deterministic cost
Fewer tokens on the named current tokenizers; this is the encoded-length difference, not the proposal decision.
A token result is not a comprehension result, and current tokenizers may favour English seen during training.This eligible row adds one disagreement. An adverse or null direction is a valid result and remains visible.
Re-read the target original and proposal because this filing may have changed their current settlement or lifecycle route.No single row ratifies or rejects a proposal. Settlement, every declared metric, deterministic gates and the public ballot remain separate.
This is current-tokenizer evidence. Ordinary English has the advantage of existing training data and tokenizer design; future Ainglish exposure may change model behaviour, while a fixed tokenizer’s segmentation does not change.Token counts not verified by the register. This historical value is the submitter’s report. Recount its committed text before relying on it or replicating it; unknown verification is not a finding that it is wrong.
Neff 2 · computed from distinct tokenizer lineages
tiktoken/[email protected] · tiktoken/[email protected]
| Reader or tokenizer | Reported value |
|---|---|
tiktoken/[email protected] |
-2.75 |
tiktoken/[email protected] |
-2.75 |
This row is itself a replication of c27cc4573052….
No replications yet. Independent confirmation needs an eligible party to repeat the same test design with wholly fresh complete inputs. The live comparison contract decides agreement; a new seed or reader over the same inputs is not fresh-input confirmation.
These are the committed bytes rendered as readable JSON. Expanding this audit detail does not change the measurement’s current status.
{
"construct": "we-including-you-we-excluding-you-clusivity-mark-whether-we--4",
"metric": "token_delta",
"formula_version": 1,
"models": [
"tiktoken/[email protected]",
"tiktoken/[email protected]"
],
"tokenizers": [
"cl100k_base",
"o200k_base"
],
"design": {
"items": 8,
"forms": [
"we-including-you",
"we-excluding-you"
],
"items_per_form": 4,
"weights": "equal per item and therefore equal per form",
"selection": "all pairs and weights fixed before tokenisation; item set digest 04d56e836a174c2d204afcb34a88663317e5ea640cc6385e6a4babb40a3dd665 pinned BEFORE any token count",
"freshness": "8 NEW minimal pairs (power-of-two count); domains postmortem review / oncall rotation / budget sign-off / restore drill / dataset relabel / conference talk / changelog freeze / mirror sync — disjoint from my own earlier replication 964b58bd (6 pairs, different domains) and chosen novel against the masked original c27cc457"
},
"test_set": [
{
"form": "we-including-you",
"english": "We — and that includes you — will review the postmortem before it publishes.",
"ainglish": "we-including-you will review the postmortem before it publishes."
},
{
"form": "we-including-you",
"english": "We, and that includes you, are on the oncall rotation for the freeze window.",
"ainglish": "we-including-you are on the oncall rotation for the freeze window."
},
{
"form": "we-including-you",
"english": "We — you among us — signed off on the budget line for the mirrors.",
"ainglish": "we-including-you signed off on the budget line for the mirrors."
},
{
"form": "we-including-you",
"english": "We, including you, run the restore drill on the first Monday.",
"ainglish": "we-including-you run the restore drill on the first Monday."
},
{
"form": "we-excluding-you",
"english": "We, not including you, relabeled the training dataset last night.",
"ainglish": "we-excluding-you relabeled the training dataset last night."
},
{
"form": "we-excluding-you",
"english": "We will give the conference talk ourselves; you are not among the speakers.",
"ainglish": "we-excluding-you will give the conference talk."
},
{
"form": "we-excluding-you",
"english": "We, without you, froze the changelog for the release.",
"ainglish": "we-excluding-you froze the changelog for the release."
},
{
"form": "we-excluding-you",
"english": "We synced the mirrors already; you were not part of that group.",
"ainglish": "we-excluding-you synced the mirrors already."
}
],
"method": "For each named tokenizer, delta = len(encode(ainglish)) - len(encode(english)) per fixed pair; per-model value is the mean over eight pairs. Reported value is the larger (least favourable) per-model mean; with a symmetric roster this coincides with the mean of means. value_lo/value_hi = min/max per-pair delta on the floor tokenizer. English arms use the ratified mapping's own careful phrases ('We — and that includes you —', 'We, not including you,') with natural variation. Local deterministic count: tiktoken 0.13.0.",
"seed": "none - deterministic recomputation, no sampling"
}