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  "seed": "no --seed flag sent — the gemma-class seat's serving unit dropped --seed in the change that added the bearer (2026-09-09)"
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 "packnorm_definition_recorded_not_governing": "v3",
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   "slug": "three-new-voices-at-the-narrators-chair",
   "q": "what did the round cost in total, and how were the three new voices judged?",
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   "answer": "the metered total for the round came to $0.7652 § {#the-bill}. the three new voices were judged by a panel of seven seats from outside families, six of which read, with every reply being held to a standard that requires speaking in the town's own tongue and using only facts present in the context § {#the-chair-and-who-sat-it-before}.",
   "served": "the metered total for the round came to $0.7652 § {#the-bill}. the three new voices were judged by a panel of seven seats from outside families, six of which read, with every reply being held to a standard that requires speaking in the town's own tongue and using only facts present in the context § {#the-chair-and-who-sat-it-before}.",
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   "ok": true,
   "answer": "the head-to-head used 36 cases § {#head-to-head}. the panel did not separate the two arms on the rules desk at this sample size § {#head-to-head}.",
   "served": "the head-to-head used 36 cases § {#head-to-head}. the panel did not separate the two arms on the rules desk at this sample size § {#head-to-head}.",
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   "slug": "six-worlds-painted-large",
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   "ok": true,
   "answer": "the article states that the first set consists of six worlds § {#six-worlds-for-a-print-lab-that-is-coming-soon}. these were painted at 2048×1280 and 40 steps § {#for-the-technically-curious}.",
   "served": "the article states that the first set consists of six worlds § {#six-worlds-for-a-print-lab-that-is-coming-soon}. these were painted at 2048×1280 and 40 steps § {#for-the-technically-curious}.",
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   "slug": "the-beat-lab-asked-and-answered",
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   "answer": "the page carries twenty-seven answers § {#the-beat-lab}. no model is asked for any answer on this page, and none ran to derive it § {#where-these-answers-come-from}.",
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   "slug": "ten-minutes-with-living-artists",
   "q": "how many tracks and releases went into the adapter, and what did the one listener prefer?",
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   "answer": "the adapter was trained on 159 tracks from 41 releases § {#forty-one-releases-licence-by-licence}. the one listener, who was unblinded, stated that the model was not very good at making good edm and that most of the samples were not pieces of music they would ever listen to for pleasure § {#twelve-requests-four-ways}.",
   "served": "the adapter was trained on 159 tracks from 41 releases § {#forty-one-releases-licence-by-licence}. the one listener, who was unblinded, stated that the model was not very good at making good edm and that most of the samples were not pieces of music they would ever listen to for pleasure § {#twelve-requests-four-ways}.",
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   "answer": "there are sixty-three players on the page, which play a listening master of each one § {#how-to-listen}. the listening masters are created by applying one constant gain to the raw render and nothing else § {#how-to-listen}. thirty-two of these masters land at −16 LUFS exactly, while the other thirty-one are left at their raw level because their peaks already sit at the engine's own −1 dB ceiling § {#how-to-listen}.",
   "served": "there are sixty-three players on the page, which play a listening master of each one § {#how-to-listen}. the listening masters are created by applying one constant gain to the raw render and nothing else § {#how-to-listen}. thirty-two of these masters land at −16 LUFS exactly, while the other thirty-one are left at their raw level because their peaks already sit at the engine's own −1 dB ceiling § {#how-to-listen}.",
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   "slug": "half-an-hour-with-dead-composers",
   "q": "how long did the Sousa and Bach adapters take to train?",
   "ok": true,
   "answer": "the Sousa adapter took 14 minutes 36 seconds by the trainer's own clock § {#sousa-a-hundred-and-six-marches}. the Bach adapter took 8 minutes 23 seconds § {#bach-the-pianist-who-freed-her-own-recordings}.",
   "served": "the Sousa adapter took 14 minutes 36 seconds by the trainer's own clock § {#sousa-a-hundred-and-six-marches}. the Bach adapter took 8 minutes 23 seconds § {#bach-the-pianist-who-freed-her-own-recordings}.",
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   "slug": "chopin-in-five-minutes",
   "q": "how many recordings were used, and how long did the training take by the trainer's clock?",
   "ok": true,
   "answer": "nineteen recordings went into training § {#five-minutes-of-training-honestly-accounted}. the training took 4 minutes 49 seconds by the trainer's own clock § {#five-minutes-of-training-honestly-accounted}.",
   "served": "nineteen recordings went into training § {#five-minutes-of-training-honestly-accounted}. the training took 4 minutes 49 seconds by the trainer's own clock § {#five-minutes-of-training-honestly-accounted}.",
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   "slug": "the-same-sixteen",
   "q": "what did glm-5.3-flash score on the tool bench, and what did the local models score?",
   "ok": true,
   "answer": "the reference arm glm-5.3-flash:cloud scored 16/19 — 84.2%, Wilson 95% interval [62.4%, 94.5%] on the tool bench § {#sixteen-of-nineteen}. local models scored various amounts, including gemma4:26b (the seat) at 14/19 [51.2%, 88.2%] at think:false and 15/19 [56.7%, 91.5%] at think:true, qwen3.6:27b at 16/19 and 14/19, gemma4:12b at 16/19, and gemma4:31b at 12/19 § {#sixteen-of-nineteen} § {#two-local-models-sixteen-days-earlier}. muse-glimmer:30b scored 13/19 § {#two-local-models-sixteen-days-earlier}.",
   "served": "the reference arm glm-5.3-flash:cloud scored 16/19 — 84.2%, Wilson 95% interval [62.4%, 94.5%] on the tool bench § {#sixteen-of-nineteen}. local models scored various amounts, including gemma4:26b (the seat) at 14/19 [51.2%, 88.2%] at think:false and 15/19 [56.7%, 91.5%] at think:true, qwen3.6:27b at 16/19 and 14/19, gemma4:12b at 16/19, and gemma4:31b at 12/19 § {#sixteen-of-nineteen} § {#two-local-models-sixteen-days-earlier}. muse-glimmer:30b scored 13/19 § {#two-local-models-sixteen-days-earlier}.",
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   "slug": "two-hours-on-battery",
   "q": "what speed did the mini pc hold on battery, and for how long?",
   "ok": false,
   "answer": "the mini pc held a speed of ~12 tokens/second on battery for about two hours § {#two-hours-at-12-tok-s-the-test-that-named-the-page}. specifically, the four answers completed on battery averaged 11.87 tok/s § {#two-hours-at-12-tok-s-the-test-that-named-the-page}.",
   "served": "this page doesn't say. the nearest it gets is § {#two-hours-at-12-tok-s-the-test-that-named-the-page}",
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   "slug": "the-instrument-travels",
   "q": "when the frozen exam moved to the smaller card, where did the ranked model land?",
   "ok": true,
   "answer": "the qwen3.6:27b model, which was previously RANKED on a 96 GB card, was re-examined on a 24 GB consumer card and remained RANKED § {#the-chair-and-who-gets-to-sit-in-it}. in the judge trial (C1), it achieved a kill-recall of 11 and a preservation of 8 § {#the-standings}.",
   "served": "the qwen3.6:27b model, which was previously RANKED on a 96 GB card, was re-examined on a 24 GB consumer card and remained RANKED § {#the-chair-and-who-gets-to-sit-in-it}. in the judge trial (C1), it achieved a kill-recall of 11 and a preservation of 8 § {#the-standings}.",
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   "slug": "nine-worlds-one-dog",
   "q": "what stays the same across the nine paintings?",
   "ok": true,
   "answer": "the same dog, the same curl, and the same tucked paws remain constant across all nine paintings § {#for-the-technically-curious}. the dog is a large black Portuguese Water Dog with one bright white chest patch § {#for-the-technically-curious}. while the dog and its posture are identical, the tree and the world change in every instance § {#for-the-technically-curious}.",
   "served": "the same dog, the same curl, and the same tucked paws remain constant across all nine paintings § {#for-the-technically-curious}. the dog is a large black Portuguese Water Dog with one bright white chest patch § {#for-the-technically-curious}. while the dog and its posture are identical, the tree and the world change in every instance § {#for-the-technically-curious}.",
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   "slug": "what-150-watts-buys",
   "q": "what did the 450-watt cap cost the dense model, and what did it buy back?",
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   "answer": "on the dense arm, the 600 → 450 W cap costs 2.0% of throughput and buys back 138 W, 11 °C, and a 28% jump in efficiency § {#the-answer-in-one-paragraph}. at concurrency 16, the throughput moved from 94.6 to 92.7 tok/s per stream § {#the-answer-in-one-paragraph}.",
   "served": "on the dense arm, the 600 → 450 W cap costs 2.0% of throughput and buys back 138 W, 11 °C, and a 28% jump in efficiency § {#the-answer-in-one-paragraph}. at concurrency 16, the throughput moved from 94.6 to 92.7 tok/s per stream § {#the-answer-in-one-paragraph}.",
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   "slug": "how-the-beat-lab-works",
   "q": "where is the sound made, and how long does a typical wish take?",
   "ok": true,
   "answer": "every sound in the Beat Lab is synthesised by the user's own browser § {#the-sound-is-made-on-your-device}. a typical wish takes about 4 s § {#what-happens-when-you-ask-the-genie}.",
   "served": "every sound in the Beat Lab is synthesised by the user's own browser § {#the-sound-is-made-on-your-device}. a typical wish takes about 4 s § {#what-happens-when-you-ask-the-genie}.",
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   "slug": "the-typist-and-the-developer",
   "q": "how long did the developer take to develop one picture?",
   "ok": true,
   "answer": "the developer developed a picture in 1.54 seconds when working alone § {#the-developer}. when working alongside a full token stream, the developer took 1.82 seconds to develop a picture § {#one-card-both-jobs-at-once}.",
   "served": "the developer developed a picture in 1.54 seconds when working alone § {#the-developer}. when working alongside a full token stream, the developer took 1.82 seconds to develop a picture § {#one-card-both-jobs-at-once}.",
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   "answer": "the 96 GB card is 3.4× faster than the RTX 3090 when running the FLUX.2 klein-4B sketch artist § {#the-table-that-answers-the-question}. for the z-image-turbo model, the 96 GB card is 3.9× faster than the 3090 § {#the-table-that-answers-the-question}. the krea2-turbo model is 4.9× faster on the 96 GB card compared to the 3090 § {#the-table-that-answers-the-question}.",
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   "answer": "on the seat the cove ships, an 896 px picture becomes 199 tokens and its prefill takes 184 ms § {#finding-one-a-picture-is-199-tokens-at-896-px-and-the}.",
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   "q": "which painter is the fastest cell, and at what time?",
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   "answer": "the distilled painter is the sharpest and fastest cell in the whole second run, recording a time of 0.62 s at 4 steps § {#finding-four-the-argument-with-our-own-settings-and-what-it}.",
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   "slug": "the-dog-the-dice-and-the-painter",
   "q": "how big is the file the whole world is written in?",
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   "answer": "the world of RealKeep is written in one YAML file that contains 16,705 lines § {#the-world-is-a-file}. this file holds six regions, forty NPCs, fifty-nine quests, and three kinds of adoptable pet § {#the-world-is-a-file}.",
   "served": "the world of RealKeep is written in one YAML file that contains 16,705 lines § {#the-world-is-a-file}. this file holds six regions, forty NPCs, fifty-nine quests, and three kinds of adoptable pet § {#the-world-is-a-file}.",
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   "q": "what are the two engines the page names for where new knowledge comes from?",
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   "answer": "the article identifies two engines for discovery. the first engine is present in the data, unmined, which refers to an archive that was already there but lacked a reader wide enough to hold it all at once § {#the-first-engine-the-archive-nobody-had-read}. the second engine is implied by the rules, unvisited, which describes a situation where a rule captured well enough emits entries that no row of the data contains § {#the-second-engine-the-rooms-the-rules-imply}.",
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   "q": "what does the page say a language model is, and what prize does it point to?",
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   "answer": "the article states that a language model is a codebook for a compressed archive of its corpus, where the weights are the compression § {#the-punchline}. it notes that training a model involves minimizing surprise by the next token, which is roughly a word, or a piece of one § {#the-punchline}. the text points to the Hutter Prize, which charges for everything including every decompressor byte counted § {#the-punchline}.",
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   "q": "what was the production median before the change, and what caused the speed-up?",
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   "answer": "the production median was 138.6 tok/s over 1,982 live rulings on 2026-08-15 § {#the-day-the-box-got-faster}. the speed-up was caused by an ollama upgrade that changed the default repeat_penalty from 1.1 to 1.0, which caused the server to skip the penalties stage in the sampling pipeline § {#the-hunt-change-one-thing}. this change meant the system no longer performed a CPU-side hash-table lookup for every entry in the 262,144-token vocabulary for every token generated § {#what-the-tax-actually-was}.",
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   "answer": "the uncompressed original was slower than the q4 build, with the uncompressed original's speed being 58.1 tok/s compared to the q4 build's 129.4 tok/s § {#the-same-question-down-the-whole-ladder}. the uncompressed original hauls 3.4× its bytes at 0.43× its speed § {#the-same-question-down-the-whole-ladder}.",
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   "q": "what is the true active share for the live seat, and what does the page call the two numbers in a model name?",
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   "answer": "the true active share for the live seat is 14.4% of the model's bytes § {#the-payroll-and-the-meeting}. the two numbers in a model name are the payroll, which are the parameters hired, trained, and taking up space, and the meeting, which are the parameters that actually show up for any given token § {#the-tag-with-two-numbers}.",
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   "q": "what was the median reading speed, and why is reading faster than writing?",
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   "answer": "the median reading speed was 5,415 tokens/s § {#a-measurement,-from-our-own-card}. reading is faster because it is parallel, as the model can process every token in the prompt at the same time since the text already exists § {#reading-is-a-group-photo}. in contrast, writing is serial because the future of the sentence does not yet exist, requiring the model to choose tokens one at a time § {#writing-is-one-at-a-time}.",
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   "slug": "three-librarians",
   "q": "how many dimensions does the embedder's map have, and what does the third librarian do?",
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   "answer": "the embedder's map has 768 directions § {#the-second-librarian-searches-by-meaning}. the third librarian works only the aisle of the game the user asked from by picking up the edition's own rulebook and any matched correction documents § {#the-third-librarian-never-left-your-aisle}. she ranks each book's passages by the map of meaning and sends up to thirty-two candidates into the room § {#the-third-librarian-never-left-your-aisle}.",
   "served": "the embedder's map has 768 directions § {#the-second-librarian-searches-by-meaning}. the third librarian works only the aisle of the game the user asked from by picking up the edition's own rulebook and any matched correction documents § {#the-third-librarian-never-left-your-aisle}. she ranks each book's passages by the map of meaning and sends up to thirty-two candidates into the room § {#the-third-librarian-never-left-your-aisle}.",
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   "q": "which seat did the new model pass, and which floor did it miss?",
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   "answer": "the qwen3.8:27b model passed the classifier seat, clearing all five pre-registered gates § {#the-classifier-seat-five-gates-all-pass-faster}. however, it failed the judge seat by missing the preservation floor of 13, scoring 11 of 16 § {#the-judge-seat-and-the-floor-it-missed}.",
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   "answer": "the article states that in the original twenty-six days, there were zero requests from an AI crawler § {#measured-again-after-publication}. the largest llms-full file measured weighs 30.7 MiB § {#where-the-file-came-from}.",
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   "answer": "twenty arms were seated to answer the frozen bytes § {#five-things-before-any-figure}. the round's metered spend was $2.2826 § {#2-2826-over-56-metered-calls-against-38-49-of-caps}.",
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   "q": "how long does every notebook on the server keep its entries?",
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   "answer": "every notebook on the server now keeps thirty days instead of a century § {#the-first-promise-your-visit-stays-between-us}. a sweep runs every night to hold this thirty days § {#the-first-promise-your-visit-stays-between-us}.",
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