The model, and every change to it
Every figure on this site comes from one model of what it costs to produce a Pearl (PRL) coin. This page lists every change to that model since the first version: what it did before, what it does after, and why. A correction is listed as a correction rather than edited away, and a change that was later replaced stays here with a pointer to what replaced it.
This site runs
Model 40
2026-10-23 · Zcash beside Bitcoin on both power charts, each day on that day's best Equihash machine. Every chart is labelled with the model that drew it, and each chart's own page lists the changes that touched it. The inputs these changes rest on are on Assumptions, each with its sources.
All changes
40 Zcash beside Bitcoin on both power charts, each day on that day's best Equihash machine
- Before
- /networks compared Pearl's power with Bitcoin's only.
- After
- Zcash is a third line on Network power draw and on Power draw at the same point in issuance. Its hashrate is each day's blocks times mean difficulty times 2^13 over 86,400 s, from Blockchair's daily block aggregates since the 2016 launch; its supply is the protocol's subsidy schedule at the day's last height, out of 21M (Blockchair's generation figure nets out shielded-pool movements and goes negative). On the date chart every day is priced on today's frontier, the Antminer Z15 Pro (840 kSol/s at 2,780 W, 3.31 J/kSol), at Bitcoin's 1.05 PUE. On the issuance chart each day is priced on a new assumption, zec_frontier_history: 7 steps with 11 citations, from an i7-6700K CPU at launch through an R9 Nano (SILENTARMY v5, 2016-11-11), a GTX 1080 (2017-03-21), the Innosilicon A9 ZMaster (2018-06-10), Antminer Z11, Z15 and Z15 Pro. The page gives Zcash's draw on the day it had issued Pearl's share.
- Why
- Zcash copied Bitcoin's 21M cap and four-year halving, so it sits on the same issuance axis, and unlike Bitcoin it went from a GPU era to ASICs within two years, the path a GPU-mined chain like Pearl could take. The Z15 and Z15 Pro ship dates are the weakest in the table (an aggregator's first-batch date and Bitmain's specification page), and the rationale says so.
- Moved
- networks, assumptions
39 The Bitcoin mining frontier, researched and cited
- Before
- Change 38 shipped a provisional table of 16 machines: makers' headline figures and approximate ship months, with no sources.
- After
- A new assumption, btc_frontier_history, with 35 citations whose quotes were checked against the fetched pages: 25 machines, each dated from the first evidence it was in customers' hands (a receipt, a maker or seller saying it shipped, or for the newest the maker's shipping window). The CPU row is an Intel Core 2 Duo E8400 (6.9 MH/s at 65 W, about 9.4 million J/TH) from the genesis block; GPUs from 2010-10-01, dated from the first public OpenCL miner rather than the card's 2009 release (Radeon HD 5870); FPGAs from 2011-08-18; ASICs from Avalon's first delivery on 2013-01-31, through 20 ASIC steps to the S23 Hydro from 2026-01-01. Machines whose ship date could not be checked are left out and named in the rationale. The page now gives each network's age at the matched share, names the H200 basis of the chart above (about a third higher), and, where the matched Bitcoin day falls within a year before a new era's row, the figure on that row too.
- Why
- Ship dates set where each step falls on the chart, and a date that cannot be shown should not move a line. Several provisional dates were early by months (the S19 Pro, the S23 Hydro), and the provisional GPU and FPGA rows were not real devices.
- Moved
- networks, assumptions
38 Pearl and Bitcoin power by share of supply issued, each day on that day's best machine
- Before
- Bitcoin's power was charted only across Pearl's life, every day priced on the Antminer S23 Hydro (9.5 J/TH). No chart compared the two networks at the same stage of their emission schedules.
- After
- /networks has a chart of both networks' power against the share of each supply cap issued (Pearl out of 2.1B from the protocol curve; Bitcoin out of 21M from blockchain.info's circulating supply, now stored daily back to the genesis block). Power is observed hashrate, a trailing 7-day mean, over the most efficient machine available that day, times wall power and PUE. For Bitcoin that is a dated frontier (btc_frontier, 16 steps from a 2009 CPU at about 5,000,000 J/TH through GPUs, FPGAs and each ASIC generation to the S23 Hydro), at PUE 1.05. For Pearl it is the card with the most hashes per watt in the gpu table, today the B200 (1,382 TH/s at 983.5 W, measured), at PUE 1.25. The machine table is provisional: makers' figures and approximate ship months, to be replaced by a cited one. The existing Bitcoin date series now start at Pearl's genesis, since they price every day on the S23.
- Why
- On the calendar Bitcoin is seventeen years in and Pearl half of one, so a date axis compares a mature network with a newborn. Both caps are half issued after four years (Bitcoin at block 210,000, Pearl at height 650,226), so the share issued is the same point in both schedules; it is not the same age, since Pearl's front-loaded curve reaches each share younger, and the page says so. Pricing 2010 on a 2026 ASIC would put Bitcoin's early draw orders of magnitude too low, so each day uses the machine that existed then.
- Moved
- networks
37 Which cards mine after the FP8 fork, and the cheapest consumer coin on one that will
- Before
- Every card in the table was assumed to keep mining. The cheapest consumer coin was priced on an Ada card (RTX 4070 Ti) with no mention that Pearl's planned FP8 protocol would stop it mining.
- After
- A new assumption, fp8_whitelist, from PIP-3 (Draft, 2026-07-30): after the FP8 hard fork only Hopper and Blackwell cards can mine. The PIP names architectures, not cards; which cards that means, including that consumer Blackwell (the RTX 50 series) counts, is the r/pearl_mining summary's reading, cited beside it. Each core cost figure says whether its card is on the list, and a seventh figure, Consumer, FP8-ready, all-in, is the cheapest consumer card that would still mine (today an RTX 5070 Ti). Today's network is still priced on every card, because the PIP has no activation height; hashrates are today's, because no speeds under the FP8 protocol are published.
- Why
- The site's cheapest consumer figure would stop existing at the fork, and a reader buying hardware now needs to know that. The whitelist is the specification's own: the verifier must reproduce floating-point results bit for bit, so hardware is named.
- Moved
- mining, overview
36 Core cost figures: the cheapest coin on each kind of infrastructure
- Before
- The home page and /mining quoted four postures priced on different cards and rules: dedicated on the cheapest consumer card, dedicated on the cheapest datacenter card, idle cards on an H200 at 70% utilisation, and mining beside inference on an H200 at the measured overhead. The cost charts computed the same postures from another table and another parameter base, and drew each day's mean, so /chart/price ended its dedicated line on $0.362 while the home page read $0.369.
- After
- Six core figures, each the minimum over every card of its class at the site's tariff, PUE and hardware life: consumer all-in (power and straight-line depreciation), enterprise all-in, enterprise electricity only (an idle datacenter card, the power mining adds), and mining beside inference on a serving datacenter card at 0%, 1% and 5% overhead (the power the miner adds plus that share of the GPU-hour's market value; only cards with a sourced rental value qualify). One function (src/core_costs.rs) computes them for the home page, /mining, the profitability summary and the cost charts; each chart line ends on the latest network snapshot, the same reading the pages use, and a daily chart's current day ends on the latest reading rather than a partial-day mean. /mining adds a row at the reader's chosen overhead. At 0% overhead mining beside inference costs what electricity only does on the same card, by change 27's rule; the two minimums can land on different cards, because only cards with a rental value qualify beside inference.
- Why
- A chart and the page linking to it disagreed, which cannot happen on a site whose numbers are meant to be checked. The postures also answered an operator-specific question (a fleet at 70% utilisation on one card) where a reader asks a general one: what is the cheapest a coin can be made on consumer hardware, on enterprise hardware, and beside inference. /production still prices a specific operator.
- Moved
- overview, mining, PRL price, Consumer, all-in $/PRL, Enterprise, all-in $/PRL, Enterprise, electricity only $/PRL, Beside inference, 0% overhead $/PRL, Beside inference, 1% overhead $/PRL, Beside inference, 5% overhead $/PRL
35 Pass's three worlds, and the crossover renamed for what it measures
- Before
- A chart called the useful-work crossover divided an H200-hour's mining revenue by its rental rate and called 100% the point where useful work stops being subsidised by emission, below which a rational operator mines only idle capacity.
- After
- That chart is renamed "Mining vs serving, per GPU-hour": at 100% buying the card to mine pays as well as renting it out, and nothing more. /ai now places Pearl in one of Rafael Pass's three equilibria (The Economics of Proof-of-Useful-Work, arXiv 2606.06700, Theorem 1) for each workload: alpha = 1 / inference kept beside the miner, gamma = 1 / hashrate kept against a dedicated card, Delta = 1/gamma + 1/alpha - 1, theta = a year of net block rewards in dollars over the inference market ($23.3B, Gartner's 2026 cloud inference spend, a new assumption). Bitconia if Delta < 0; Fortessia if Delta > 0 and theta < alpha - 1; Duplexia above, where the inference price is alpha/(1 + theta) of the cost of compute (pure) or alpha(1 - 1/gamma) (mixed). At the measured overhead, chat is in Bitconia and coding and long-prompt traffic in Fortessia, with Duplexia at about $5.60 a PRL; the overhead picker moves all of it.
- Why
- The old description was wrong. In Pass's model the subsidy to inference begins when theta exceeds alpha - 1, which depends on the overhead and on rewards against the whole market, not on one card's hour; and Section 7 (Corollary 8) shows cheaper or idle hardware lowers the cost of compute without moving the regime boundaries. Whether idle cards mine at a profit is shown beside the regimes as a separate, practical test. The regimes are long-run equilibria and the page says so: Pearl draws a fraction of a percent of the power behind AI inference.
- Moved
- ai, Mining vs serving, per GPU-hour, mining, overview
34 Inference overhead capped at 12.5%
- Before
- The inference-loss control on /mining and /production offered 10%, 20% and 30%; the throughput sweep on /production ran from 0% to 100% of inference kept; a URL parameter could set any value.
- After
- Every control, sweep and parameter stops at 12.5% overhead (87.5% of inference kept). The controls offer 0%, 1%, 5% (Pearl's figure), the measured ~8%, 10% and 12.5%; the sweep runs from 12.5% to 0% in half-point steps; a larger value in a URL is clamped to 12.5%. The measured default is unchanged.
- Why
- The only figures we have are Pearl's 5% and one independent on/off benchmark, ~8% on chat traffic, whose prompt shapes ranged from 2% to 14%; the 14% is a single prompt shape on a benchmark, not a deployment. An operator losing more than an eighth of a card's inference would stop running the miner, so pricing a coin at 20-30% overhead modelled a deployment nobody would keep and made the dearest posture look worse than any real one.
- Moved
- mining, production, difficulty, Mining during inference $/PRL, Idle inference GPU $/PRL
33 Coding-agent traffic as a third workload, and one chart for all of it
- Before
- /inference priced two workloads, chat and long prompts, both on 8k-input/1k-output throughput and two token prices.
- After
- A coding-agent workload: per output token, about 7 input tokens the GPU has to process and 125 served from cache, billed at the input, cache and output prices; throughput is output tokens per GPU on a coding-agent trace where measured (four models) and scaled from the 8k/1k figure where not, with its range; Pearl's miner keeps at most 10.8% of a GPU's hashrate, from an estimated 60% of GPU time in decode -- an upper bound, since the 27% of prefill that mines was measured on 8k-token prompts, coding steps mostly append fewer than the 1,024 tokens the miner needs, and at 130k contexts much of prefill is attention, which does not mine. No overhead has been measured on coding traffic, so every overhead column is marked unsupported there. A small-multiples chart at the top of the page shows every model's price change at every overhead for all three workloads at once.
- Why
- Requested. Coding agents are the largest open-model workload by tokens on OpenRouter, and their bill is mostly cached input, which a two-price model cannot represent. The token mix is the median of 920 measured coding-agent benchmark runs; the decode share is an estimate bracketed three ways (0.30-0.85), because no source measures busy prefill time for agentic serving. Both are assumptions on /assumptions with their sources.
- Moved
- inference
32 Input and output priced separately, and the discount stated as a ceiling
- Before
- /inference priced every model at one blended price (8 input tokens to 1 output) and showed one discount, the largest a provider could give, without saying it was the largest.
- After
- Market input and output prices are the medians across providers, each on its own; revenue per GPU-hour is input tokens at the input price plus output tokens at the output price, 8:1 as the benchmarks run. The page shows each model's market input and output price, then the input and output prices mining could fund at each overhead. How much of its net mining income the provider passes on is a control: all of it is the maximum discount, at which mining gains the provider nothing, and is labelled as the ceiling; half and a quarter are shown beside it. A loss is charged in full, not shared. A 0% overhead column shows the most mining could fund at all: its income less its electricity, the same figure as the break-even overhead at full pass-through.
- Why
- A reader rightly asked whether the page assumed a provider would pass on every dollar it mined, and which tokens the prices were for. It did, without saying so, and it blended input and output into one price. Taking medians of input and output separately moves some models' market price slightly (DeepSeek-V4-Pro's blend from $1.37 to $1.49).
- Moved
- inference
31 What mining could take off the price of open-model inference
- Before
- The site priced mining against one model (a 70B-class model at one throughput and one token price) and did not ask what a provider could pass on to its customers.
- After
- /inference prices leading open-weight models, each on the card its throughput comes from: revenue per GPU-hour from tokens per second and the median provider's list price (both at an 8:1 prompt-to-reply mix, the site's convention and the shape of the 8k/1k benchmarks), against what Pearl's miner earns on that card at today's PRL price and hashrate. The discount at 0.5%, 1%, 5% and 12% overhead is the price cut that leaves a sold-out provider the same dollars of profit per GPU-hour: (mining - overhead x revenue - added electricity) / ((1 - overhead) x revenue). The break-even overhead is where it reaches zero: 0.4-2.8% on chat traffic, 1.6-11% on long prompts. Columns outside the overheads measured for each workload are shaded.
- Why
- Requested. It turns the site's per-coin cost into the number an inference provider decides on. Throughput is measured for six models; for the rest it is derived from a reply-only figure (x9 to an 8k/1k shape, which at a 95% cache hit is close to the compute actually done) or scaled from measured models, marked estimated, and shown with its range. One model (GLM-5.3) has no defensible H200 throughput and is listed but not priced. The hashrate is held at the workload's figure whatever the overhead, which pairs a long-prompt hashrate with overheads nobody has measured for it at the low end; the page shades those columns and says so.
- Moved
- inference
30 Every researched input checked again at the source
- Before
- Inputs as researched in late September, several resting on secondary sources: H200 at 813 TH/s, consumer cards at a 4090-class 250 TH/s, a five-card network mix, a fitted work-per-difficulty constant, 40 GW of AI datacenter capacity, $2.60/hr, 1,864 tok/s, $0.70 per million tokens, decode drawing 45% of rating.
- After
- Work per difficulty is exact, 2^64/65,535, from the node source. H200 735 TH/s (same compute as the measured H100). Consumer cards at their own measured speeds (RTX 4090 305, 5090 405 TH/s). The network mix is fourteen cards weighted from a census of 8,012 pool workers: 82% of hashrate on consumer cards. AI datacenter capacity 23 GW (chip power sold through mid-2026 × PUE). H200 rental $2.09 (cheapest quote), 1,920 tok/s (vLLM FP8, prompt and reply), $0.50 per million tokens (8:1 blend). Decode draws 75% of rating under current engines. Pool fees as each pool publishes them.
- Why
- A public model has to survive somebody checking its sources. Each figure was re-fetched and quoted from the page it came from; sources found not to say what they were cited for were removed. Some moved because a newer measurement exists; some because the old figure had been mislabelled (the 1,864 tok/s was TensorRT-LLM, not vLLM; the five-card mix averaged faster per card than the pools report per worker). Two GPU-hour routes that agreed within 2% turned out to agree by luck. Each assumption on /assumptions names the measurement that would settle it.
- Moved
- All-in cost per PRL, Network-mix electricity $/PRL, Network-mix power draw, Network-mix GPU-equivalents, Consumer, all-in $/PRL, Idle inference GPU $/PRL, Mining during inference $/PRL, Mining vs serving, per GPU-hour, Mining revenue per GPU-hour, difficulty, production, networks, overview
29 Correction: orphans counted from our own node
- Before
- The orphan deduction read the explorer's 'orphans in the last 24 hours' field: 3.5% of blocks.
- After
- Orphans are counted from our own full node's stale chain tips over the last 3,000 blocks (about six days): 1.1%. When the node has no figure, the researched 1.1% stands in; the explorer's count is no longer used.
- Why
- The explorer's field read 14 while its own list of orphans in that day held 3. Three independent counts agree on about 1%: our node's chain tips (34 in 3,331 blocks), the explorer's list (30 in 2,580; 28 of them hash-for-hash the same as ours), and one pool's own record (3 in 330). Every cost per coin falls about 2.4%.
- Moved
- All-in cost per PRL, Network-mix electricity $/PRL, Miner revenue, Consumer, all-in $/PRL, Idle inference GPU $/PRL, Mining during inference $/PRL
28 Mining during inference is Pearl's own miner, which mines only prefill
- Before
- The co-resident posture modelled a separate miner filling the compute that decode leaves idle: 41% of a dedicated card's hashrate derived from phase utilisations, or 90% on a figure cited to Hashrate Index. Inference lost: a derived 12%.
- After
- It models the miner Pearl ships. Pearl's vLLM plugin swaps the model's own matrix multiplications for mining ones, only in batches of 1,024 tokens or more, which in serving is prefill. So a card keeps (1 − decode share) × 27% of a dedicated card's hashrate: 5.4% on the default 80%-decode chat mix. Inference kept is the measured 92% (an independent on/off benchmark lost 2–14% by prompt shape; Pearl reports 5.08%). The overview's control now sets only the inference cost; the hashrate follows from the workload. On chat traffic, mining beside paying work becomes the dearest way to produce a coin.
- Why
- Research for this release found the 90% was one line on a mining pool's blog, not on the page it was cited to, and that Pearl's miner works the opposite way from the one modelled: Pearl's config.yaml (min_m: 1024) and a Pearl contributor ('Mining favors prefill heavy workloads'). Pearl's own prefill-heavy benchmark mined 155–245 TMAC/s per H200, 21–33% of a dedicated card. The measurement that would settle it is one H100 serving a real chat trace under Pearl's plugin, mining on and off.
- Moved
- Mining during inference $/PRL, production, difficulty, overview
27 A miner pays only the power it adds
- Before
- Every posture was charged its hashrate share of the card's full rated draw, whatever the card was doing.
- After
- Each posture pays the draw mining adds to what the card would draw without it. A card bought to mine pays its whole draw. An idle card pays 90%: an idle H100 already draws 72.5 W of 700 W. A miner sharing a card with inference pays an idle card's watts per hash. Two earlier drafts of this change were caught by the pre-publication reviews and never shipped: one capped the co-resident miner's watts at the power headroom while still crediting its hashrate (90% of a dedicated card's work for about half its power); the next capped its hashrate at the headroom, which for Pearl's in-engine miner counted the power limit twice, since its 27% was measured on cards already at their limit.
- Why
- A card's idle draw is paid whether or not it mines, so charging it to mining overstated the idle posture by 10%. Measured: idle 72.5 W and sustained full load 668 W on a 700 W H100 (National Laboratory of the Rockies); a power limit is enforced by lowering the whole chip's clock (NVIDIA). Sources on /assumptions.
- Moved
- Idle inference GPU $/PRL, Mining during inference $/PRL, production, difficulty, overview
26 Tuned co-residency: a 1% floor by 1% of the pool, as a scenario
- Before
- On /difficulty the overhead fell from today's figure to 2% only at Bitcoin parity (about 23% of AI datacenter power), so the 1% rung was priced at 8%.
- After
- It falls log-linearly to a 1% floor by the time mining is 1% of AI datacenter power (0.23 GW of the 23 GW pool, about 193 EH/s or four times today's network) and holds there, Bitcoin parity included. The floor and the share where it is reached are parameters, and the page labels the column a scenario, with the case where it never improves beside it.
- Why
- Requested: at that scale, with Pearl's miner keeping ~5% of a card's hashrate on chat traffic, some 4.9 million serving cards would be mining and the displaced inference would be worth about a billion dollars a year even at the floor, so the work would be tuned. It is a scenario, not a learning curve: getting from today's ~8% to 1% over about two doublings of scale means the overhead more than halving with every doubling, far steeper than any learning curve on record. The hashrate each card keeps does not improve with it. Nothing published shows a miner sharing a serving GPU for 1% or less; LithOS (SOSP 2025) is cited for the order of magnitude only, and it is about right-sizing one job's kernels, not about a miner.
- Moved
- difficulty
25 Correction: no price before trading began
- Before
- The first traded price was back-filled over the two months before trading, drawing revenue and cost history at a price that never existed — an 8,195% spike on the crossover chart.
- After
- No price, no point. The overview's prose uses the same contention pair as its cards.
- Why
- From a review of the live site.
- Moved
- Mining vs serving, per GPU-hour, Miner revenue, Idle inference GPU $/PRL, Network-mix electricity $/PRL, Pearl FDV vs Bitcoin, overview
24 The overview's inference-loss control defaults to 5%
- Before
- The overview used the derived 12% loss, adjustable only on /production.
- After
- A control at the top of the overview, defaulting to 5% (reported to us, unsourced), with 0% (Pearl's position), the derived 12% and 10–30% one click away. Picking a value also switched the hashrate kept from the derived 41% to a 90% "vendor" figure, without saying so; #28 removed that.
- Why
- It is the most important open number and nobody has measured it. At 5% mining beside inference costs $0.31 against $0.35 for a dedicated rig; at 30% it is $1.45.
- Moved
- overview, Mining during inference $/PRL
23 Correction: the verdict priced on the cards beside it
- Before
- The overview's verdict said 'AI operators only' while the card beside it showed a dedicated rig at a 70% margin.
- After
- The verdict is priced on the same hardware as the cards.
- Why
- The overview stated two conclusions side by side.
- Moved
- overview
22 Each posture priced on the hardware that suits its job
- Before
- Every posture was priced on an H200, which put cards bought to mine underwater at $2.18 a coin.
- After
- Cards bought to mine are the cheapest card per hash at the reader's tariff and depreciation ($0.35, a 72% margin). The postures beside inference use the card with the best measured inference throughput per watt.
- Why
- 'Buying hardware to mine does not pay' was an artefact of the card it was priced on. Nobody buying cards to mine buys an H200.
- Moved
- Consumer, all-in $/PRL, Idle inference GPU $/PRL, Mining during inference $/PRL, production, overview, difficulty
21 Pool fee and orphan rate measured, not typed in
- Before
- 1.8% pool fee and 3.3% orphans, copied by hand.
- After
- Recomputed on every request: the fee weighted by blocks each pool found in the last day, over pools that publish one (1.57%), and orphans over blocks found (2.66%).
- Why
- The stated method had never actually been run, and 1.8% could not be reproduced from the site's own data.
- Moved
- All-in cost per PRL, Network-mix electricity $/PRL, Miner revenue, Consumer, all-in $/PRL, Idle inference GPU $/PRL, Mining during inference $/PRL, pools
20 The co-residency overhead falls with scale (revised by #26)
- Before
- A flat 1% budget at every scale (#18).
- After
- The contention model returns the derived 12.1% again. On /difficulty the overhead falls log-linearly in the share of the pool, from 12.1% today to 2% at Bitcoin parity, and each row states the figure it was priced at beside the case where it never improves.
- Why
- The flat cap put a projection inside the physics and applied it at today's scale, where nothing justifies it. Log-linear is the standard learning-curve shape.
- Moved
- difficulty, Mining during inference $/PRL
19 Correction: one definition of the idle posture everywhere
- Before
- /production's middle posture blended idle cards with serving ones ($0.129); /difficulty's was idle cards alone ($0.074).
- After
- The idle posture is cards serving nothing, with nothing displaced, on every page. Its unit cost does not move with utilisation; only how many idle cards exist does.
- Why
- A shared label guaranteed one name, not one definition.
- Moved
- Idle inference GPU $/PRL, production, difficulty, overview
18 Co-resident miner capped at 1% inference loss (superseded by #20)
- Before
- The miner beside inference ran flat out: 12.1% of inference lost.
- After
- A 1% loss budget inside the contention model at every scale: mining beside inference went from $1.29 to $0.18 a coin.
- Why
- Operators throttle a miner to what their service levels can absorb. It was an assumption about tuning presented as physics, and was replaced within the hour.
- Moved
- Mining during inference $/PRL, production, difficulty
17 Each posture costed separately, at the issuance when it arrives
- Before
- Below the idle threshold the idle and co-resident columns were blended into one number. Every scale was priced as if built today.
- After
- Each posture is costed as itself at every scale, with availability a separate flag. Each scale is priced against the issuance at the time it could be built (5 GW a year by default).
- Why
- Mining beside inference always displaces some throughput. Emission roughly halves in two years, so when a build lands moves its cost more than anything else on the page.
- Moved
- difficulty
16 Correction: 'hardware charged' becomes 'bought to mine'
- Before
- The column charged full capital and the inference revenue displaced at once — a card cannot be both bought to mine and giving up inference.
- After
- Bought to mine: purpose-built cards running flat out, full capital, nothing displaced, matching the dedicated posture on /production.
- Why
- It is the only column comparable with Bitcoin, whose hardware has no other use.
- Moved
- difficulty
15 Pearl's implied value against Bitcoin's, floor to floor
- Before
- /difficulty divided Pearl's cost-floor valuation by Bitcoin's market valuation.
- After
- A column divides by Bitcoin's own floor: the price at which its issuance just covers its electricity at the same tariff.
- Why
- Dividing a floor by a market price mixed two kinds of number. What remains floor to floor is the issuance schedule: Pearl mints about 0.046% of its cap a day, Bitcoin about 0.002%.
- Moved
- difficulty, Pearl FDV vs Bitcoin
14 Each cost states which issuance it is divided by
- Before
- Every $/PRL divided today's cost by issuance at the 194-second target, without saying so.
- After
- The default is unchanged. The site also reports the observed block time, issuance at that pace, and the cost per coin on it.
- Why
- Blocks were running at about 162 seconds, minting about 19% more than the target pace. On the posture beside inference that is $1.285 against $1.071 at a $1.27 price — enough to flip the headline, so both are shown.
- Moved
- production, difficulty, Mining during inference $/PRL, Daily emission
13 Correction: a card nobody rents out is not free to rent
- Before
- A rented fleet priced cards with no rental quote at $0, making 60% of the default fleet's hashrate free: $1.50 a coin.
- After
- A rented fleet is priced over cards that have a quote, renormalised: $3.75 a coin.
- Why
- No quote means no quote, not free.
- Moved
- All-in cost per PRL, production
12 Correction: revenue net of deductions, and no invented price
- Before
- The miner-revenue tile used gross emission while the chart it linked to was net, about 4% apart. A missing price fell back to a typed-in $1.19.
- After
- The tile reads the net series. A missing price gives no point. A card links only to a page showing the same number.
- Why
- Absent means absent, and a card must agree with the chart it opens.
- Moved
- Miner revenue, Mining vs serving, per GPU-hour, Inflation rate, Network-mix electricity $/PRL, overview
11 Correction: every verdict charges mining its electricity
- Before
- The strategy table gave the blended fleet its mining power free (+$409/day, 'it helps') while the posture beside it charged for that power and lost money. The overview's verdict compared price with a revenue-allocated cost that moves with price, so it could never say 'unprofitable'.
- After
- The flag, the threshold and the strategy table all carry the power mining adds: the blended fleet is −$91/day against inference alone. Both verdict boundaries are costs that do not move with price.
- Why
- One page stated two answers, and revenue allocation cannot decide whether to mine.
- Moved
- production, overview
10 The difficulty curve is priced on the marginal supplier
- Before
- Every scale on /difficulty was priced on electricity alone.
- After
- Capacity enters cheapest first: idle AI cards for electricity, then cards mining beside live inference once the idle ones run out. Utilisation became a control.
- Why
- The price that attracts a given amount of capacity is the cost of the last card attracted. 50% of the pool moved from $21.68 to $92.48 a coin.
- Moved
- difficulty
9 The difficulty estimator
- Before
- No forward model of cost against scale.
- After
- /difficulty carries a card, a power price and a share of world AI datacenter power (a researched 10–96 GW range) through to hashrate, difficulty and cost per coin, with a real row for today at the network's observed share.
- Why
- Emission depends only on height, so cost per coin scales exactly with compute. Pearl covered its electricity up to about 2.2% of the pool; matching Bitcoin's draw needs about 22%.
- Moved
- difficulty, Pearl energy vs Bitcoin
8 Mining beside inference pays for the electricity it adds
- Before
- The miner beside inference was charged no power, on the reasoning that the card was already on.
- After
- It is charged the power it adds, taken as its hashrate share of the card's full draw (revised by #27). With no inference lost the cost is that electricity alone, reported as the theoretical floor. The inference loss became a control. 69e4dce made the posture table match: ff4ae6d computed the power term there and then dropped it, though the headline figure already used it.
- Why
- A serving GPU is below full draw, and lighting up idle compute pulls it toward its rating. At $1.27 the figure ran from $0.08 at the floor to $1.29 at the derived loss — the assumption is the answer.
- Moved
- Mining during inference $/PRL, Idle inference GPU $/PRL, production
7 Correction: prefill was charged twice, and sunk capital charged to mining
- Before
- Contention charged prefill for hashrate the miner earned during decode: 18% inference lost, $1.78 a coin beside inference. The idle cards' capital was charged to mining.
- After
- Contention is costed per phase: 12% lost, $1.21 a coin. Capital on an inference fleet follows an attribution setting that defaults to zero, because the fleet was bought for inference whether or not it mines.
- Why
- The output did not survive a sense check, and the review found the two errors. An earlier claim that the idle-card posture always sits between the other two was withdrawn.
- Moved
- Mining during inference $/PRL, Idle inference GPU $/PRL, production
6 Three ways to produce a coin
- Before
- Four costings of the same coin: standalone, revenue-allocated, capital-free and incremental.
- After
- Three postures, each fully costed through one function: cards bought to mine; a serving fleet that mines on its idle cards; and the miner switched on beside live inference. All three appear on the overview and as chart series.
- Why
- These are the three businesses that exist. At 70% utilisation they came out $2.21, $2.03 and $1.83 on the derived contention and $2.15, $1.15 and $0.67 on the vendor's — so the contention assumption, not the posture, decides.
- Moved
- Consumer, all-in $/PRL, Idle inference GPU $/PRL, Mining during inference $/PRL, production, overview
5 Mining and inference share a card, and the contention is derived
- Before
- Some cards served and the rest mined. The hashrate and inference kept while sharing were free dials.
- After
- The miner runs on the same card as inference and each workload costs the other some throughput. Both figures are derived from published physics — tensor cores about 92% busy in prefill and 28% in decode; the miner 95–100% compute and under 30% memory bandwidth — from one input, the share of serving time spent in decode.
- Why
- Pearl's reference miner runs on vLLM beside inference. Two free dials invite choosing the answer. The derivation keeps 41% of standalone hashrate against the vendor's 90%, a gap the site reports rather than hides.
- Moved
- Mining during inference $/PRL, production
4 The squeeze, and Bitcoin costed the same way as Pearl
- Before
- The headline asked whether mining beats inference, with no cross-network yardstick.
- After
- The headline compares a miner who buys the whole card with an operator whose card is already paid for by inference and is charged electricity only. Bitcoin is costed by the same rule — observed hashrate over the most efficient machine sold for it — so the two are compared in watts, dollars and machines, never in hashes, which are different functions.
- Why
- The question is when a standalone miner stops being able to compete, not whether mining beats inference. The comparison put Pearl at 0.62% of Bitcoin's energy.
- Moved
- Consumer, all-in $/PRL, Pearl network power, Bitcoin network power, Pearl energy vs Bitcoin, networks, production
3 Datacenter hashrate from measurements, not calculators
- Before
- H200 680 TH/s and H100 SXM 615 TH/s, both calculator estimates.
- After
- H100 SXM 735 TH/s and B200 1,382 TH/s as measured by PeakMiner on its own hardware; H200 813 TH/s, derived by scaling the H200 estimate by the measured-to-estimated ratio for the H100, and labelled as derived.
- Why
- A measured figure beats an estimate. A faster card means fewer cards and less power for the same network hashrate.
- Moved
- All-in cost per PRL, Network-mix electricity $/PRL, Network-mix power draw, Network-mix GPU-equivalents
2 An AI inference fleet, with mining priced as an opportunity cost
- Before
- Mining was costed as electricity and hardware only. A GPU-hour had no other value.
- After
- A GPU-hour sold for inference has a market value, and mining it costs that revenue; mining an idle hour costs only power, so utilisation decides the answer. Defaults: 1,000 H200s, 1,864 tok/s, $0.70 per million tokens, 70% utilisation, PUE 1.25, 36-month depreciation, no capital charged to mining. Adds the useful-work crossover: mining revenue per GPU-hour over inference revenue per GPU-hour.
- Why
- The site's question became whether the work Pearl pays for is worth what the AI market pays for work. The crossover read about 31% at the time, up from 22.8% ninety days earlier.
- Moved
- Mining vs serving, per GPU-hour, Mining revenue per GPU-hour, production
1 Initial cost-to-produce model
- Before
- No model.
- After
- Cost per PRL = network spend per day ÷ PRL emitted per day. Emission is exact, not fitted: subsidy(t) = S·H/((t+H)(t+H−1)) with S = 2.1e9 and H = 650,226. Network spend comes from the observed hashrate on a five-card mix (H200 15%, H100 SXM 25%, RTX 5090 25%, RTX 4090 20%, RTX 5080 15% of hashrate) at $0.05/kWh, PUE 1.15, 24-month straight-line hardware, 15% opex, 1.8% pool fee and 3.3% orphans. Two figures: marginal (electricity only) and all-in (electricity, hardware and opex).
- Why
- Emission depends on block height alone, so a coin's cost is network spend divided by a known issuance. A single-card model cannot show the first finding, that datacenter cards have the lowest marginal cost and the worst all-in cost. At height 119,163 and $1.14 the mix read $0.1127 marginal and $2.45 all-in.
- Moved
- All-in cost per PRL, Network-mix electricity $/PRL, Network-mix power draw, Network-mix GPU-equivalents, Daily emission, Circulating supply
Commit hashes refer to the site's source repository, which is private: they are our audit trail, and we will show the change behind any of them to anyone who asks. Invariant numbers refer to the list of properties the site must always hold, each with the test that holds it.
Where to next
Related pages that answer the questions this one raises.