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#27 of 30 · GPU cloud

CoreWeave

250,000 GPUs, 1.3 GW contracted, not one sustainability number.

Livingston, New Jersey·coreweave.com ·Verified Oct 16, 2026
DLittle data
Index score
Little data

In plain words

How scores work

CoreWeave scores 34 out of 100 — laggard. Little or no disclosure, fossil-backed capacity, or active disputes with regulators and communities. Confidence in this score is little data (D).

What helps

  • Nothing on record.

What hurts

  • Carbon · No renewable procurement or carbon disclosure; much US capacity sits on Texas and Pennsylvania grids, with Nordic sites on hydro.
  • Transparency · The IPO prospectus and subsequent reports carry no environmental metrics at all.
  • Commitments · No targets.

What nobody knows

  • Per-prompt energy disclosed
  • Per-prompt water disclosed
  • Training emissions in model cards
  • Annual environmental report
  • Location-based Scope 2 reported
  • +3 more

CoreWeave — a former Ethereum miner — ran more than 250,000 GPUs across 32 data centres with 360 MW of active power at the end of 2024, with 1.3 GW contracted and a target of 1.7 GW by end-2026. It hosts OpenAI, Microsoft, Cohere's Canadian site and NVIDIA's own capacity. Its IPO filing contains no emissions, energy-mix or water disclosure and the company has no climate targets.

Products
CoreWeave Cloud (H100 / H200 / GB200) · Mission Control · Weights & Biases
Hosting
Leased capacity in 30+ data centres (Core Scientific, Applied Digital, Galaxy) across the US, UK, Norway, Sweden and Spain.

Key figures

Per-prompt and fleet metrics. Hover a title for what it means; open “How we got this number” for the working.

How to read the labels:Company figureCompany figure. Published by the company itself. We take it as given and record the scope next to it.Measured independentlyMeasured independently. Measured or estimated by researchers or analysts with no stake in the result.ecogpt.co estimateecogpt.co estimate. Our own estimate from published factors. The working is shown next to the number; treat it as an order of magnitude, not a measurement.DerivedDerived. Arithmetic on a disclosed or independent input using a published conversion factor.Not disclosedNot disclosed. The company publishes nothing on this and no defensible estimate exists.— hover any label.
Energy per promptElectricity used to answer one typical request. Under 0.3 Wh is good. A 10 W LED bulb uses 0.3 Wh in about two minutes.
0.30
Wh / typical prompt
≈ 25.0 smartphone charges per 1,000 prompts
ecogpt.co estimateecogpt.co estimate. Our own estimate from published factors. The working is shown next to the number; treat it as an order of magnitude, not a measurement.Epoch AIThe Next Platform

ecogpt.co estimate; no company figure.

How we got this number

CoreWeave hosts frontier inference and training for OpenAI, Microsoft and others; the 0.3 Wh Epoch estimates for a typical frontier query is the representative workload. Uncertainty roughly ±3×.

Water per promptWater evaporated cooling the servers for one request. Scope matters: on-site cooling only, or also the water used to generate the electricity (which adds ≈1.8 mL per Wh).
0.09
mL / typical prompt
≈ 0.18 500 mL bottles per 1,000 prompts
ecogpt.co estimateecogpt.co estimate. Our own estimate from published factors. The working is shown next to the number; treat it as an order of magnitude, not a measurement.Epoch AIThe Next PlatformMicrosoft

On-site cooling only, so comparable with Google and OpenAI's figures.

How we got this number

0.3 Wh per prompt × 0.3 L/kWh (estimated WUE for liquid-cooled dense racks). Counting the water evaporated to generate the electricity adds ≈0.54 mL.

Carbon per promptGreenhouse gas from one request on the grid where it actually runs. Below 0.1 g is clean. A kilometre in a petrol car is about 170 g.
0.117
gCO₂e / typical prompt
≈ 0.69 km driven (petrol car) per 1,000 prompts
ecogpt.co estimateecogpt.co estimate. Our own estimate from published factors. The working is shown next to the number; treat it as an order of magnitude, not a measurement.Epoch AIThe Next Platform

Location-based: what the grid actually emitted. Renewable certificates would bring the market-based figure near zero.

How we got this number

0.3 Wh × 390 gCO₂/kWh (US grid, location-based).

Annual emissionsThe company's whole yearly footprint, in million tonnes of CO₂e. Clouds and device makers dwarf pure labs because they also count shops, logistics or products. Compare the trend, not the size.
0.98
MtCO₂e / year (AI compute only)
ecogpt.co estimateecogpt.co estimate. Our own estimate from published factors. The working is shown next to the number; treat it as an order of magnitude, not a measurement.Data Center Dynamics

Location-based estimate for the AI fleet only; not comparable with a full corporate inventory.

How we got this number

360 MW × 8,760 h × 80% utilisation × 390 gCO₂/kWh (US grid). Compute only — nothing else the company does is counted.

Emissions trendDirection of travel against last year or the company's own baseline. Negative is good. Positive means the AI build-out is outrunning clean energy.
+130
% (360 MW → ≈850 MW active)
ecogpt.co estimateecogpt.co estimate. Our own estimate from published factors. The working is shown next to the number; treat it as an order of magnitude, not a measurement.Data Center DynamicsThe Next Platform
How we got this number

Active power grew from 360 MW at end-2024 to about 850 MW during 2025, with 1.7 GW targeted for end-2026.

Water per kWh (WUE)Litres of water consumed per kilowatt-hour of server electricity, across the fleet. 0.15 is excellent, 0.3 is good, 1.8 is the US data-centre average.
0.30
L/kWh
ecogpt.co estimateecogpt.co estimate. Our own estimate from published factors. The working is shown next to the number; treat it as an order of magnitude, not a measurement.Microsoft
How we got this number

No disclosure. Liquid-cooled GB200 racks in leased facilities; comparable to Azure's 0.30 L/kWh.

Clean electricityShare of electricity matched with renewable or carbon-free sources. Annual matching counts certificates bought anywhere; hourly matching on the same grid is far stricter.
40.0
% (US grid average non-fossil, no procurement)
ecogpt.co estimateecogpt.co estimate. Our own estimate from published factors. The working is shown next to the number; treat it as an order of magnitude, not a measurement.Data Center Dynamics
How we got this number

The US grid is about 40% non-fossil; CoreWeave discloses no renewable purchases, and its Nordic sites are a small share of capacity.

Hardware & materials

The chips, power, copper and future e-waste behind the fleet — the part sustainability reports leave out

Factors we use
AI chips in service
250,000
GPUs (end-2024, IPO filing)
≈ 3,472 racks of 72 GPUs
Company figureCompany figure. Published by the company itself. We take it as given and record the scope next to it.Data Center DynamicsThe Next Platform

GPUs, TPUs or custom accelerators the company runs. Analyst figures are in H100-equivalents, company figures in physical chips.

How we got this number

Mostly H100, with H200 and GB200 arriving; 684,000 GPUs contracted as of mid-2026 per market trackers.

Power draw
360
MW active (end-2024)
≈ 270,000 US homes' worth of power
Company figureCompany figure. Published by the company itself. We take it as given and record the scope next to it.Data Center Dynamics

Megawatts the AI fleet pulls. One megawatt runs roughly 750 US homes.

How we got this number

1.3 GW contracted; 1.7 GW targeted by end-2026.

Electricity a year
2.52
TWh / year
≈ 240,000 US homes for a year
DerivedDerived. Arithmetic on a disclosed or independent input using a published conversion factor.Data Center DynamicsSemiAnalysis

Terawatt-hours per year. One TWh is a year of electricity for about 95,000 US homes.

How we got this number

360 MW × 8,760 h × 80% utilisation. Compute fleet only.

Carbon baked into the hardware
129
ktCO₂e embodied in chips and servers
≈ 27,935 petrol cars driven for a year
DerivedDerived. Arithmetic on a disclosed or independent input using a published conversion factor.Data Center DynamicsThe Next PlatformarXiv 2607.05408NVIDIA developer blog

CO₂e emitted making the chips and servers before they answer a single prompt.

How we got this number

250,000 accelerators × 514 kg CO₂e each (chip plus share of the host server). Emitted in manufacturing, before the first prompt is served.

Future e-waste
4,250
tonnes of servers to retire within ~5 years
≈ 24 empty Boeing 747s by weight
DerivedDerived. Arithmetic on a disclosed or independent input using a published conversion factor.Data Center DynamicsThe Next PlatformNVIDIAThe Register

Tonnes of server hardware that will be retired in three to five years.

How we got this number

250,000 accelerators × 17 kg of server hardware each. Tomorrow's e-waste unless reused; generative AI could produce 2.5 Mt of it a year by 2030.

Copper in the build
9,720
tonnes of copper in the build
≈ copper for 117,108 electric cars
DerivedDerived. Arithmetic on a disclosed or independent input using a published conversion factor.Data Center DynamicsBHPS&P Global Market Intelligence

Tonnes of copper in cabling, busbars and transformers.

How we got this number

360 MW × 27 t of copper per MW (cabling, busbars, transformers).

Fossil generators on site
138
backup diesel generators (implied)
≈ 359 MW of backup capacity
DerivedDerived. Arithmetic on a disclosed or independent input using a published conversion factor.Data Center DynamicsLatitude MediaLatitude Media / Floodlight

Diesel backup units or gas turbines at the data centres, permitted or observed.

How we got this number

360 MW ÷ 2.6 MW per generator, the average size permitted at US data centres. Permit counts are not published fleet-wide; this is the number a fleet this size normally carries.

Hardware reused or recycled
—
No hardware reuse or e-waste figure published.
Not disclosedNot disclosed. The company publishes nothing on this and no defensible estimate exists.

Share of retired servers and parts given a second life.

Mineral depletion
—
Only Mistral has published a mineral-depletion figure.
Not disclosedNot disclosed. The company publishes nothing on this and no defensible estimate exists.

Kilograms of antimony-equivalent, the life-cycle unit for scarce minerals consumed.

Score breakdown

Each pillar is 0–100; weights are fixed across the index

Energy efficiency — How much electricity one answer costs.weight 20% · confidence C
55
Carbon intensity — How clean that electricity is, and whether total emissions are rising.weight 25% · confidence C
35
  • No renewable procurement or carbon disclosure; much US capacity sits on Texas and Pennsylvania grids, with Nordic sites on hydro. Data Center Dynamics
Water — How much water the data centres consume, and whether it is replaced.weight 15% · confidence D
40
Transparency — How much the company actually publishes.weight 20% · confidence D
8
  • The IPO prospectus and subsequent reports carry no environmental metrics at all. Data Center Dynamics
Commitments — Whether it has dated, measurable climate and water targets.weight 10% · confidence C
10
Conduct — How it behaves: permits, lawsuits, gas turbines, community water.weight 10% · confidence C
55

Models

What this company ships, and what each prompt costs

No model-level entries — this company hosts or supplies others rather than serving its own models.

Where the compute lives

Named sites from company disclosures and press reporting

OperationalConstructionPlanned
  • Livingston HQNew Jersey, USA
  • PlanoTexas, USA
  • Denton (Core Scientific)Texas, USA · Converted crypto-mining site.
  • Ellendale (Applied Digital)North Dakota, USA · 400 MW campus.
  • CrawleyUnited Kingdom
  • Oslo regionNorway · Hydro grid.