Energy per token in Spain: methodology, the electricity market and the cases of speculation
Contents
Notation: amounts in euros (N €), decimals with a point. The whole article is focused on the Spanish electricity market (OMIE). The dollar symbol is not used (on this site it is a formula delimiter).
What this article covers
This is the second article of the energy track (C2), and deliberately longer, because it puts together two things that are almost never told together: the technical methodology of measuring energy per token, and the reality of the Spanish electricity market that puts a price on that energy. For an inference platform in Spain, the J/token figure is half the story; the other half is that those kilowatt-hours are bought in a market that is marginal-priced, volatile and with documented cases of manipulation. Anyone who sizes the electricity cost of a cluster without understanding how the price is formed in OMIE, and why it has tripled in a year, is building 30–50 % of the TCO on sand. This article covers the measurement, the market, the cases of speculation and the strategies for not being left exposed. No partisan opinions: data, market mechanics and documented facts, with their sources.
The identity: energy per token, and why the price rules
Energy per token comes from the identity set out in the opening article:
$$\text{energy per token (J)} = \frac{\text{average power (W)}}{\text{throughput (tok/s)}}$$And the electricity cost per token is that energy multiplied by the price of electricity:
$$\text{electricity cost per token} = \text{energy per token (kWh)} \times \text{PUE} \times \text{price (€/kWh)}$$Here is the point of this article: the first two factors (energy and PUE) are controlled by your engineering; the third, the price, is set by the Spanish electricity market, and it is the one that moves most. The same workload, with the same efficiency, can cost three times as much in electricity depending on the month, not because of the technology but because of OMIE. That is why measuring energy per token well is necessary but not sufficient: you have to understand the price variable that multiplies it.
Methodology: measuring energy per token without fooling yourself
Before the market, the measurement. As we saw in the energy introduction, the energy-per-token figure has four instrumentation decisions that change the result:
| Decision | Trap | Good practice |
|---|---|---|
| Sampling frequency | coarse sampling misses the prefill peaks | sample finely (sub-second) |
| Board vs node | the GPU alone underestimates by 10–20 % | measure the whole node or declare the limit |
| Time window | including warm-up or shutdown distorts the J/token | align the window with the measured workload |
| Idle baseline | attributing or subtracting changes the number | decide and document it |
The golden rule: the same window for the power and for the tokens. If DCGM integrates the power of one interval and the benchmark tool counts the tokens of another, the J/token means nothing. With that settled, you already have the energy per token; the rest of the article is about what multiplies it.
The Spanish electricity market: how the price is formed
In Spain (and Portugal), the wholesale price of electricity is set by OMIE (Operador del Mercado Ibérico de Energía), which runs the day-ahead market and sets the price for each hour (OMIE). The system is marginal-priced (pay-as-clear): each hour supply (the plants, ordered from cheapest to most expensive) and demand are matched, and the price for everyone is that of the last plant to enter, the marginal one. That marginal price is the same across all of Spain (except the Canaries) and applies to all agents regardless of their initial bid (Energía y Sociedad).
The consequence, central to understanding the bill: when gas is the marginal plant (the usual case in hours without sun or wind), renewables, nuclear and hydro, dirt cheap to produce, are paid the price of gas. That difference between production cost and price received is what are called “windfall profits”, the heart of the debate about market design. For the buyer of electricity, a datacenter for example, it means that the price paid does not reflect the cost of generating, but that of the most expensive technology needed that hour.
The volatility: the price that triples in a year
The marginal-priced market, tied to gas in the expensive hours, produces enormous volatility. The 2026 data illustrates it: the Spanish wholesale price closed May 2026 with an average of 54 €/MWh, more than triple the 16.92 €/MWh of the same month in 2025 (Merca2). Tripling in a year, without your consumption or your efficiency changing.
And within a single day, the dispersion is brutal because of the effect of renewables: solar and wind enter at prices close to zero, and in the midday hours of May 2026 prices reached negative levels in several sessions (Merca2). The structural context: wind and solar went from 26 % of generation in 2019 to more than 40 % in the first half of 2024, and over that period the wholesale price was more than 40 % lower than it would have been with 2019 renewable levels (Banco de España).
| Reference | Value | Source |
|---|---|---|
| Wholesale May 2026 | 54 €/MWh | Merca2 |
| Wholesale May 2025 | 16.92 €/MWh | Merca2 |
| Year-on-year variation | +219 % (×3.2) | derived |
| Solar hours 2026 | prices close to 0 or negative | Merca2 |
| Renewables in generation | 26 % (2019) → >40 % (2024) | Banco de España |
The reading for a cluster: the electricity part of the TCO is not a fixed number, it is a variable with a range of 3× year on year and from zero-price hours to peak hours within the day. Sizing the energy cost with an annual average price and forgetting about it is ignoring the biggest risk in the model.
The structure of the bill: wholesale is not what you pay
It is worth not confusing the wholesale price (the OMIE pool price, the one the headlines talk about) with what a company actually pays. On top of the wholesale price come:
| Component | What it is | Nature |
|---|---|---|
| Energy (wholesale) | the OMIE price hour by hour | variable, volatile |
| Access tolls | use of the transmission and distribution networks | regulated |
| Charges | system costs (past renewables, etc.) | regulated |
| Taxes | IEE (special electricity tax) + VAT | fiscal |
The result: the industrial retail price a datacenter pays is well above the wholesale price, since tolls, charges and taxes can double the price of pure energy. That is why this article always distinguishes between the wholesale price (~0.054 €/kWh in May 2026) and industrial retail (~0.12 €/kWh): for the TCO the second one matters, but the first is the one that moves and drags the second with it. A large company can access the wholesale market more directly (via a supplier or a representative), reducing the mark-up, but taking on the exposure to volatility that comes with it.
There is also the PVPC (Precio Voluntario al Pequeño Consumidor), the regulated tariff indexed to the wholesale price for small consumers; a datacenter does not use PVPC, but its existence explains why the volatility of the pool reaches public opinion and political debate directly, and, with it, the regulation that ends up affecting everyone.
The 2021–2022 crisis: the origin of the problem
Today’s volatility is not new: it originates in the gas crisis of 2021–2022. When the price of gas shot up (the marginal plant in many hours), the marginal-pricing system passed that price on to all electricity, including that generated by cheap renewables, nuclear and hydro. The result was wholesale prices that were several times the historical levels and massive “windfall profits” for generators of cheap technologies that were paid the price of gas. That episode is what motivated both the Iberian exception (capping gas in price formation) and the European debate about redesigning the market, and it explains why, years later, the price is still a first-order risk variable for anyone consuming a lot of megawatt-hours. For a multi-year TCO model, the lesson is that the Spanish electricity price has shown it can multiply within months through external factors (gas geopolitics), and that no assumption of a “stable” price survives an episode like that unless it is covered by contract.
The cases of speculation and manipulation
The volatility of marginal pricing creates incentives to manipulate the price, and in Spain there are documented cases with final CNMC fines. The largest sanctions on utilities for manipulating the wholesale market (Nada es Gratis):
| Company | CNMC fine | Concept |
|---|---|---|
| Iberdrola | 25 million € | manipulation of the wholesale price via hydro plants |
| Naturgy | 19.5 million € | manipulation of the wholesale market |
| Endesa | 5.8 million € | manipulation of the wholesale market |
The Iberdrola case is the most illustrative of how marginal pricing is gamed: between 30 November and 23 December 2013, the company raised the prices of several hydro plants so that they would not clear despite the high prices in the day-ahead market (Nada es Gratis). The mechanism: withhold cheap water (not bidding it, or bidding it at a prohibitive price) so that the clearing needs a more expensive plant, pushing up the marginal price paid to your whole portfolio. In a pay-as-clear system, withdrawing cheap capacity raises the price of everything you sell that hour; the incentive to manipulate is embedded in the design.
OMIE has supervision mechanisms and carries out audits to prevent manipulation (Energía y Sociedad), and the CNMC sanctions it when it is detected; the fines above are the proof that it happens. For the buyer, the relevant point is not to assign blame, but to recognise that the price paid is formed in a market where manipulation is possible and has happened, and that therefore exposure to that price is a risk to manage, not a figure to accept.
The other speculation: hoarding grid capacity (and the new 2026 law)
There is a second form of speculation, distinct from price manipulation, that affects directly anyone who wants to build a datacenter: the hoarding of access and connection permits to the grid. For years, many developers reserved connection capacity at grid nodes for projects (mostly renewable) that had no real intention or capacity to build, blocking that capacity for firm projects and speculating on the value of the permit. Since an inference platform is a demand facility that needs its connection point, this bottleneck hits it squarely: grid capacity is a scarce and hoarded resource.
The regulatory response of 2026 targets exactly that. The Government (Ministry for the Ecological Transition) finalised a set of rules, within the framework of Royal Decree-Law 7/2026, to free up grid capacity and fight speculation, ensuring that firm requests can connect (El Periódico de la Energía, Fieldfisher). The central mechanism, with effect from 22 March 2026:
| Element | Detail |
|---|---|
| Who pays | holders of access and connection permits for demand facilities |
| What they pay | a monthly charge for “reserving” capacity until entering operation |
| How it is calculated | transmission and distribution tolls × a “k factor” |
| Modulation | by voltage level and by the delay in commissioning |
| k factor | to be set by resolution of the Secretary of State for Energy |
The logic: if reserving capacity costs every month and the cost grows with the delay, hoarding stops being free and the speculator releases the capacity it is not going to use. For a real datacenter project the implication is twofold: (1) that charge on the reserved capacity has to be budgeted during construction, and (2) there is a strong incentive to build quickly, since every month of delay in starting up adds to the charge. In other words, the new law turns commissioning time into an explicit cost. For the TCO model and the timetable of the proposal, this is a figure to build in from the start: grid capacity is no longer reserved “just in case” for free, and the construction schedule now has a bill attached.
The design debate: why marginal pricing rewards speculation
The underlying problem is not just that some companies manipulate: it is that the market design rewards doing it. In a pay-as-clear system (everyone is paid the marginal price), a generator with a lot of cheap capacity has a perverse incentive: withdrawing part of its cheap capacity raises the marginal price it is paid for all the capacity it does sell. If you control enough market share, the extra revenue from raising the price of your whole portfolio can exceed what you lose by not selling the withdrawn capacity. That is exactly what the CNMC sanctioned in the hydro case.
The design alternatives under debate:
| Design | How it pays | Effect on the incentive to speculate |
|---|---|---|
| Pay-as-clear (current) | everyone is paid the marginal price | high: withdrawing capacity raises the price of everything |
| Pay-as-bid | each one is paid its own bid | lower incentive, but strategic bidding |
| Long-term contracts / PPA | fixed bilateral price | takes volume out of the pool, reduces exposure |
There is no technical consensus that pay-as-bid is better (it introduces its own problems of strategic bidding), and the reform of the European electricity market has opted more for promoting long-term contracts (PPA and CfD) than for changing the pool mechanism. For the buyer, the practical conclusion is the same as for the regulator: taking your volume out of the pool through forward contracts is the most direct way of not being exposed to the marginal price, and to whoever manipulates it.
The Iberian exception: a patch with an expiry date
Faced with the gas price crisis of 2021–2022, the European Commission granted Spain and Portugal an exception allowing them to cap the price of the gas used to produce electricity (market context). The “Iberian exception” partially decoupled the electricity price from gas, containing the peaks. It is relevant for a multi-year cost projection because it is a regulatory mechanism with limited duration: any 36-month TCO model has to consider what happens to the price if the exception changes or expires. Regulation is another price variable, not just the market.
What it means for the electricity cost of a cluster
Putting together energy per token (technical) with the Spanish price (market), the electricity cost per token of an example node (8×H100, 0.78 kWh per million tokens with PUE) according to the price scenario:
| Price scenario (Spain) | €/kWh | Electricity cost / 1M tokens |
|---|---|---|
| Solar hour / negative price | ~0 | ~0 |
| May 2025 (low wholesale) | 0.017 | ~0.013 € |
| May 2026 (average wholesale) | 0.054 | ~0.042 € |
| Industrial retail (with tolls and taxes) | ~0.12 | ~0.094 € |
| Peak hour / crisis | 0.20+ | ~0.16 € |
The range is more than 10× between the solar hour and the peak hour, and 3× year on year at the level of the average. Over a fleet consuming megawatt-hours a year, that variability is the difference between a comfortable TCO and a suffocated one, and it does not depend on your technology but on when and how you buy the energy.
Strategies for not being left exposed
This is where the technical figure turns into a decision. Four levers for managing exposure to the Spanish price, from the least to the most structural:
| Strategy | What it does | Trade-off |
|---|---|---|
| Indexed tariff | you pay the wholesale price hour by hour | cheap on average, maximum exposure to volatility |
| Fixed / forward tariff (OMIP) | price locked by contract | predictability, you pay a premium for the insurance |
| PPA with a renewable plant | you buy directly from a solar/wind farm | stable price and low carbon, requires volume and term |
| Solar self-consumption | you generate on site | you cover the sunlight hours almost free, capex and space |
| Temporal scheduling | move shiftable load to cheap hours | only applies to the non-urgent (batch, fine-tuning) |
The sensible combination for an inference platform in Spain: a PPA or a fixed tariff for the base load (online inference, which cannot be moved), solar self-consumption to cover the midday hours almost free, and scheduling of the shiftable work (training, overnight batch) towards the off-peak or peak-solar hours. That turns the volatility of marginal pricing from risk into opportunity: the same zero-price hours that sink generators’ revenue are the cheap hours for whoever consumes.
Solar self-consumption: the numbers for a cluster
Spain is one of the best places in Europe for solar, and for a datacenter self-consumption has a clear cost logic. The numbers, for illustration:
| Parameter | Reference value |
|---|---|
| Solar output in Spain | ~1,400–1,600 kWh per kWp per year |
| Capex of an industrial installation | ~600–900 € per kWp |
| Panel service life | ~25–30 years |
| Electricity cost avoided (retail) | ~0.12 €/kWh |
For a 100 kWp installation (warehouse roof): it generates ~150 MWh/year, with a capex of ~70,000–90,000 €. At 0.12 €/kWh avoided, it saves ~18,000 €/year, with a payback of ~4–6 years and then ~20 years of almost free energy. The snag: a cluster consumes 24/7 and solar only produces by day, so self-consumption covers a fraction, the midday hours, not everything. But those midday hours are precisely the ones with low or negative wholesale prices, so self-consumption and the market complement each other: at night you buy cheap (off-peak), by day you generate. The avoided cost is not only that of the energy, it is that of not being exposed to the non-existent solar peak and to daytime volatility. For a cluster with roof space available, self-consumption is the most solid structural lever on electricity cost in Spain.
Annual electricity TCO: three scenarios for a cluster in Spain
Putting it all together, the annual electricity cost of an 8×H100 node (~7.84 kW with PUE, ~68,700 kWh/year at 100 % utilisation) according to the purchasing strategy, in Spain:
| Strategy | Effective €/kWh | Annual electricity cost | Exposure |
|---|---|---|---|
| Indexed (unhedged) | ~0.08 (variable) | ~5,500 € ±a lot | maximum to volatility |
| Fixed / renewable PPA | ~0.06 (stable) | ~4,120 € | low, predictable |
| PPA + solar self-consumption | ~0.045 (mixed) | ~3,090 € | low + minimal carbon |
The difference between the worst and the best strategy is ~2,400 €/year per node, before counting the risk: the indexed option can shoot up in a bad month, while PPA+solar is stable and low. Over a fleet of dozens of nodes and a 36-month horizon, the choice of how the energy is bought moves the TCO as much as a hardware decision, and it is a lever decided with contracts, not with engineering. This number feeds directly into the TCO model of the FinOps track (A8) and the sizing of the proposal.
PPAs: the central lever (and its small print in 2026)
Of all the strategies, the PPA (Power Purchase Agreement, a long-term energy purchase contract) is the most important piece for a datacenter in Spain today, and it deserves a section of its own because its current situation is exceptionally favourable… with a catch.
What a PPA is, in short
A PPA is a bilateral, long-term contract (typically 10–12 years in Spain) between a consumer and a renewable generator, at a locked price per MWh. It takes your volume out of the OMIE pool: instead of paying the marginal price hour by hour (with its volatility and its exposure to manipulation), you pay the contract price. There are two families: physical (you receive the energy from that farm) and financial/virtual (a swap covering the difference against the market); and two profile forms: pay-as-produced (you pay for what the farm generates, when it generates, cheap but intermittent) and baseload (a guaranteed flat profile, more expensive but firm).
Prices today: historic lows
Spain is living a unique moment in PPA prices. Solar PPAs fell to a historic low of 32.5 €/MWh in the fourth quarter of 2025, with the most competitive percentiles below 30 €/MWh, half the French level (pv-magazine, El Periódico de la Energía). Wind sits at around 50–60 €/MWh. To put it in context: a solar PPA at 30 €/MWh is ~0.030 €/kWh, less than half the industrial retail price (~0.12 €/kWh) and well below the volatile wholesale price.
| Technology (PPA, Spain 2026) | Price | Reference |
|---|---|---|
| Solar photovoltaic | ~32.5 €/MWh (percentiles <30) | pv-magazine |
| Wind | ~50–60 €/MWh | market |
| Industrial retail (for comparison) | ~120 €/MWh | — |
Why so cheap: cannibalisation
The fall is no accident: it is the cannibalisation of photovoltaics. The more solar is installed, the more midday hours there are with wholesale prices close to zero or negative, which sinks the value captured by solar (captured prices have fallen below 15 €/MWh), and with it the price at which farms sign PPAs (Energía Estratégica). With more than 40 GW competing for 30 GW of demand, there is an excess of solar supply that cheapens the PPA. For the industrial consumer it is a historic opportunity; for the solar developer, a crisis of profitability, hence the talk of the “closing of the solar PPA window” and of the new Royal Decree seeking to restore industrial competitiveness.
Spain, European leader in PPAs
This is no marginal phenomenon: in 2024 Spain was the country with the most PPAs signed in Europe for the sixth consecutive year, with 47 agreements for 4.66 GW of renewable capacity (market sources). The market is deep, liquid and mature, which makes it easier for a datacenter to find a counterparty.
The catch for a datacenter: annual energy ≠ firm power
Here is the small print that decides the architecture. A cheap solar PPA offsets energy over the year, but does not guarantee physical power every hour. And an AI datacenter cannot stop because there is no wind one January night or because the solar curve falls at dusk (El Periódico de la Energía). This is the difference between energy (kWh per year, which the solar PPA covers dirt cheap) and firm power (kW available for all 8,760 hours, which the sun does not provide). The sector sums it up like this: Spain is now forced to talk about firm energy (Revista Cloud).
The consequence for the design of the proposal: a solar PPA at 30 €/MWh is the ideal cost floor for the sunlight hours, but it has to be combined to cover the rest: a hybrid PPA (solar + wind, which complement each other over time), baseload for the flat part, or storage (batteries, which RDL 7/2026 also promotes) to move energy from the sunlight hours to the night. The sensible energy architecture of a Spanish datacenter in 2026 is not “a solar PPA”, it is a cheap solar PPA as the daytime base + firmness for the hours without sun (wind, baseload, batteries or the grid as backup). Anyone who signs only the cheap solar PPA and discovers in production that they have no firm power in the small hours will have optimised the cost of the energy and ignored that of availability, which for an inference platform with an SLO is non-negotiable.
The context: the datacenter boom in Spain
All of this is happening in the middle of a boom: Spain is positioning itself as the epicentre of southern Europe in datacenters, with investments of billions and installed capacity doubling towards 2026 (DCD). The appeal combines cheap renewable PPAs, industrial land more accessible than in other European digital capitals, and EU jurisdiction. The constraint that tempers it is exactly the one in C2: the cost of energy is low but firm power and grid capacity are the bottlenecks, and both are managed with the combination of a hybrid PPA, storage and a connection schedule that does not fall foul of the hoarding charge.
The sovereign and carbon angle
For a sovereign proposal, Spain has a double advantage worth quantifying. First, carbon: the Spanish grid runs at around ~150–170 gCO₂/kWh (a mix of renewables and gas), well below Germany (~363) though above nuclear France (~20–60). Second, growing renewables (>40 % of generation), which pull the price and the carbon down in the sunlight hours. The argument for the proposal: a cluster in Spain, with solar self-consumption and a renewable PPA, can achieve at the same time a low and predictable electricity cost and a competitive carbon per token, within EU jurisdiction. The volatility of marginal pricing is not only a risk: managed well with contracting and scheduling, it is a cost lever that a hyperscaler in another region does not exploit in the same way.
Carbon, moreover, is variable by the hour: in peak-solar hours the intensity of the Spanish grid drops, so moving shiftable load to those hours reduces both the cost and the carbon per token at once. The same scheduling strategy serves both axes.
Guarantees of Origin: carbon has its market too
One nuance that connects price speculation with carbon reporting: in Spain (and the EU) there is a market in Guarantees of Origin (GoO), certificates attesting that a quantity of energy was produced from a renewable source. A company can buy GoOs to declare that its consumption is “green” in its market-based carbon reporting, even though physically the electricity it received from the grid had the average intensity of the mix. This creates two ways of accounting for carbon, with different implications:
| Method | What it counts | How the figure is brought down |
|---|---|---|
| By location (location-based) | the real intensity of the Spanish grid that hour | generate/consume in clean hours; location |
| By market (market-based) | according to the GoOs/PPAs contracted | buy certificates or sign a PPA |
Location-based accounting rewards consuming when the Spanish grid is clean (solar hours); market-based allows the green attribute to be “bought” with GoOs. CSRD reporting normally requires both. The word of caution: the GoO market is relatively cheap, and buying GoOs without a real PPA behind them is a way of dressing up the figure without changing the physical electricity you consume, the cost equivalent of accounting greenwashing. For an honest sovereign proposal, the robust route is a real PPA with a Spanish renewable farm (which does change the physical origin and stabilises the price) plus location-based measurement that rewards scheduling to clean hours, rather than accumulating certificates.
Hourly intensity: the Red Eléctrica figure
Spain publishes the carbon intensity of the grid hour by hour (via Red Eléctrica / esios and ElectricityMaps), and it varies enormously over the day: on a sunny spring afternoon it can drop to ~80–100 gCO₂/kWh, and on a cold, windless night, with gas cycles, exceed ~250. That hourly figure is what makes carbon-aware scheduling possible: moving training, document ingestion or overnight batch to the hours of lowest intensity reduces the carbon per token of the shiftable work at no technical cost. It is the same lever as price-based scheduling, since the cheap hours and the clean ones largely coincide in Spain, because both are set by the excess of solar and wind. Measuring carbon per token “on an annual average” wastes this information; measuring it hour by hour and scheduling accordingly is what turns the figure into a real reduction.
Energy per token, with the Spanish price, step by step
Closing the circle with a complete calculation for the example node, in Spain:
- Energy per token: 5,600 W (8×H100) ÷ 2,800 tok/s = 2 J/token (board); ×PUE 1.4 = 2.8 J/token effective.
- Energy per 1M tokens: 0.78 kWh (with PUE).
- Electricity cost per 1M tokens by contracting model:
- Indexed in a solar hour (~0 €/kWh): ~0 €.
- Renewable PPA (~0.05 €/kWh stable): ~0.039 €.
- Industrial retail (~0.12 €/kWh): ~0.094 €.
- Carbon per 1M tokens: 0.78 kWh × ~160 gCO₂/kWh = ~125 gCO₂ (and less in solar hours).
The message: the J/token is fixed (your engineering sets it); the electricity cost per token varies more than 10× depending on how and when you buy the energy in Spain. That is why this article devotes more space to the market than to the measurement: measuring is 30 % of the problem; buying well is 70 %.
Limits and traps (data-driven)
- A misleading annual average price. Using an annual average hides the 3× year-on-year volatility and the 10× intraday range. Model scenarios, not a point.
- Indexed by default. The indexed tariff is cheap on average but leaves you exposed to every peak and every episode of manipulation. For base load, hedge it.
- Ignoring the Iberian exception. It is a regulatory mechanism with an expiry date; a 36-month TCO has to consider it changing.
- Forgetting hourly carbon. Carbon and price fall at the same time in solar hours; scheduling the shiftable work improves both axes.
- Confusing wholesale with what you pay. Industrial retail adds tolls and taxes on top of the wholesale price; use your contract price, not the pool price.
With the Spanish price understood, the energy track continues towards measurement tools in depth (C3) and energy in TCO and regulation (C8). But the lesson of C2 is that, in Spain, the energy cost of AI is not decided in the GPU alone: it is decided in how you buy the electricity in a market that is marginal-priced, volatile and watched for manipulation.
Closing
Energy per token is a number that engineering fixes with precision, so many joules per token, measured in a window aligned with the throughput, and that the Spanish electricity market multiplies by a factor that changes more than 10× depending on the hour and 3× depending on the year. That second half, the price one, hardly ever appears in technical AI articles, and it is what decides 30–50 % of the TCO of a cluster in Spain. The price is formed in a marginal-priced market where cheap renewables are paid the price of gas, where volatility has tripled the bill in a year, and where there are final CNMC fines, Iberdrola 25 M€, Naturgy 19.5 M€, Endesa 5.8 M€, that show that manipulation is not theoretical. For a sovereign inference platform in Spain, the conclusion the data supports is twofold: measure energy per token rigorously, and buy the electricity with your head — a PPA or fixed tariff for the base load, solar self-consumption for the sunlight hours, and scheduling of the shiftable work to the cheap, clean hours. Spain offers abundant sun, growing renewables and a reasonable average carbon figure; well contracted, its energy is a competitive advantage, and badly contracted, the biggest risk in the model. The J/token is yours to decide; the euro per token, the market’s, unless you take it out of the market with a contract.
See also
- MLPerf Power — the standard benchmark of energy efficiency (energy per query, performance-per-watt) and its limits.
- LLM energy efficiency leaderboards — the J/token rankings where the data this methodology produces is published: how to read them without falling for their biases.
- From the watt to carbon: PUE, grid intensity and the real cost of a token — the step after measuring J/token: turning that figure into gCO₂eq and into real electricity cost with PUE and the country’s energy mix.
- Energy efficiency levers in LLM inference — which levers (quantization, batching, engine, schedulers) effectively reduce the J/token this methodology measures.
Sources
- OMIE · Operador del Mercado Ibérico de Energía — https://www.omie.es/
- OMIE · precio del mercado diario — https://www.omie.es/es/market-results/daily/daily-market/day-ahead-price
- Energía y Sociedad · importancia y precios de OMIE — https://www.energiaysociedad.es/omie-cual-es-su-importancia-para-el-sistema-electrico-espanol-y-portugues/
- Nada es Gratis · manipulación del precio en el mercado eléctrico español (multas CNMC) — https://nadaesgratis.es/jose-luis-ferreira/manipulacion-del-precio-en-el-mercado-electrico-espanol
- Merca2 · el precio de la luz en mayo 2026 (54 €/MWh, ×3 interanual) — https://www.merca2.es/2026/05/30/precio-luz-mayo-2026-disparo-2386473/
- Banco de España · el sector eléctrico ante el alza del gas (renovables y precio) — https://www.bde.es/f/webbe/SES/Secciones/Publicaciones/PublicacionesSeriadas/DocumentosOcasionales/23/Fich/do2316.pdf
- El Periódico de la Energía · normativa para liberar capacidad de red y combatir la especulación — https://elperiodicodelaenergia.com/el-gobierno-ultima-una-normativa-para-liberar-la-capacidad-de-las-redes-electricas-y-combatir-la-especulacion/
- Fieldfisher · Real Decreto-ley 7/2026, paquete regulatorio de renovables — https://www.fieldfisher.com/es-es/locations/espana/actualidad/nuevo-paquete-regulatorio-energias-renovables
- Bird & Bird · almacenamiento energético en el RDL 7/2026 — https://www.twobirds.com/es/insights/2026/spain/almacenamiento-energetico-real-decreto-ley-7-2026
- pv-magazine · caída récord de los PPAs fotovoltaicos a 32,5 €/MWh — https://www.pv-magazine.es/2026/02/04/la-canibalizacion-provoca-una-caida-record-de-los-precios-de-los-ppas-fotovoltaicos-en-espana-hasta-los-325-e-mwh/
- El Periódico de la Energía · PPAs solares cerca de 30 €/MWh (mitad que Francia) — https://elperiodicodelaenergia.com/la-canibalizacion-acerca-el-precio-de-los-ppas-solares-a-30-mwh-en-espana-la-mitad-que-en-francia/
- Energía Estratégica · cierre de la ventana de PPAs solares y el nuevo RD — https://www.energiaestrategica.com/espana-atraviesa-un-cierre-de-la-ventana-de-ppas-solares-mientras-el-nuevo-real-decreto-busca-aliviar-la-industria/
- El Periódico de la Energía · la gran decisión energética de los data centers (energía firme) — https://elperiodicodelaenergia.com/la-gran-decision-energetica-de-los-data-centers
- Revista Cloud · los centros de datos obligan a España a hablar de energía firme — https://revistacloud.com/los-centros-de-datos-obligan-a-espana-a-hablar-de-energia-firme
- DCD · boom de data centers en España hacia 2026 — https://www.datacenterdynamics.com/es/features/data-centers-en-espa%C3%B1a-hacia-2026-un-boom-de-90000-millones-en-proyectos/