True-Cost Accounting · Confidence-Banded Model · v8.0

The Cost of Blackwell

A proxy model of the GB200 NVL72 rack-scale system built from what is publicly available. 72 Blackwell GPUs. 36 Grace CPUs. ~120 kW-class load. Not a server — a small building’s worth of power, distilled into 1.36 tonnes of extracted earth.
GB200 NVL72 rack 72× Blackwell B200 36× Grace CPUs 18 compute trays · 9 NVLink switch trays ~120 kW-class Liquid-cooled 1.36 t confirmed
⚠  No peer-reviewed elemental analysis of B200 or H100 exists as of May 2026. Material composition uses Falk et al. 2026 A100 ICP-OES data as a lower-generation proxy. Every figure carries a confidence label.
High — manufacturer-specified or peer-reviewed
Medium — modelled from published proxies
Low — estimated or extrapolated
Unknown — not publicly disclosed
CO₂ live — GB200 NVL72
0.0000kg CO₂e since page load 1,334 kg/day · 120kW × 24h × PUE 1.2 × 0.386 kg/kWh = 115–120 US homes · ~1.3 NYC–LA flights/day · 34 US residents’ annual footprint per year Day 24–38: operational carbon surpasses all embodied carbon Reserved contract: $3.30–3.50/GPU-hr · rack ASP ~$1.5–2M [A,D] 0.0000kg CO₂e since page load 1,334 kg/day · 120kW × 24h × PUE 1.2 × 0.386 kg/kWh = 115–120 US homes · ~1.3 NYC–LA flights/day · 34 US residents’ annual footprint per year Day 24–38: operational carbon surpasses all embodied carbon Reserved contract: $3.30–3.50/GPU-hr · rack ASP ~$1.5–2M [A,D]
GB200 NVL72 — architecture (Nvidia-specified) high confidence
GPUs
72× B200
GB200 modelled; GB300 now shipping [K]
CPUs
36× Grace
ARM, co-packaged with B200
Compute trays
18
2× Grace + 4× B200 each
NVLink switch trays
9
Rack-scale NVLink fabric
Power class
~120 kW
Spec 120 kW · HPE measured 132 kW deployed
Cooling
Liquid
Direct liquid, CDU, cold plates
Rack mass
~1.36 t
1.36 t — confirmed Spheron, Sunbird, HPE 2024–2025
PUE (est.)
~1.2
Liquid cooling advantage
📄
Only peer-reviewed elemental source: Falk et al. “From computation to environmental cost.” Commun. Earth Environ. 7, 397 (2026). ICP-OES on Nvidia A100 SXM 40GB — 32 elements identified, 93% of GPU mass classified hazardous. Used here as lower-generation proxy for Blackwell material categories. No public peer-reviewed teardown of B200, H100, or any post-Ampere GPU exists as of May 2026. All B200 composition claims in this ledger are proxy inferences, not measurements.
DOI: 10.1038/s43247-026-03537-5 · Open Access CC BY 4.0
How to use this document
✓  On firm ground — use this to say:
“Based on Nvidia’s own ISO 14067-reviewed PCF data and standard US grid metrics, a Blackwell rack’s operational carbon completely overtakes its manufacturing carbon footprint somewhere between Day 15 and Day 45 — making its operational lifetime efficiency the only variable that truly matters.”
Also: the reserved contract economics, the deployment lag risk, the Jevons’ Paradox argument, the pollution taxonomy, the audit gap table.
✗  Do not use this to say:
“A Blackwell rack contains exactly 1.2 grams of cobalt and uses 5,000 litres of water a day.”
The cobalt figure is scaled from A100 ICP-OES data (Falk et al. 2026) — Blackwell uses CoWoS-L co-packaging and a different architecture. The water figure is deployment-dependent and zero for some closed-loop configurations. These are proxy boundaries, not measurements. See C-01, C-06.
This is a confidence-banded forensic proxy model — not a peer-reviewed teardown. It builds a bounded argument around what is publicly verifiable versus what remains hidden. Methodological transparency is the point: every figure carries a confidence label, every caveat is documented, every proxy is named. “A brilliant piece of critical infrastructure accounting that uses rigorous logic to fill the intentional blanks left by corporate disclosures.”
Daily resource consumption — one GB200 NVL72 rack at 120 kW · continuous operation medium confidence
3,456kWh/day
Electricity — 120 kW × 24h × PUE 1.2
Per hour144 kWh
Per week24,192 kWh
Per year1,261,440 kWh
= 115 average US homes (EIA 2023: 30 kWh/day avg) · ~10× an 8×H100 DGX system
💨
1,334kg CO₂/day
Carbon — 0.386 kg/kWh US grid avg (EIA eGRID 2023)
Per hour55.6 kg
Per week9,338 kg
Per year486,910 kg
Driving a petrol car 5,379 km/day (EPA 0.248 kg CO₂/km) · or ~1.3 NYC–LA return flights per day (~492/yr)
✈️
~492flights/yr
NYC–LA return trip CO₂ equivalents
Per day~1.3 flights
Per week~9.4 flights
2-yr lifetime~984 flights
NYC–LA round trip ≈ 990 kg CO₂/passenger · 486,910 kg/yr ÷ 990 = 492
🏠
115–120homes
Average US households powered by one rack (est.)
Rack/year1,261,440 kWh
Home/year10,500 kWh
Range115 (30kWh/d) – 120 (10,500kWh/yr)
EIA 2023: US residential avg 10,500 kWh/yr
🌊
1,173L per chip
TSMC water to manufacture one B200 GPU
What this isUltrapure water used by TSMC fab to clean wafers, etch, rinse & planarize during chip production
Per B200 chip~310 gal / 1,173 L
Full rack (72 B200 + 36 Grace + NVLink est.)~118,000 L
= daily water use of~833 Americans
Appears on any invoice$0 — never billed
TechInsights Aug 2025 [J]: IC fabrication water only — does not include packaging, assembly, shipping, or data centre cooling water. Murphy yield model, 90% fab utilisation, location-based Scope 2. medium confidence
💧
~5,000L/day
Liquid cooling water — rack ops estimate
Per year~1,825,000 L
= Americans/day~35 people
Cost in ledger$0 — unpriced
Rough estimate. Nvidia internal email (Dec 2025): Microsoft’s GB200 facility-level cooling described as “wasteful” — uses air cooling on top of in-rack liquid cooling, higher energy, lower water. Real PUE may be 1.3–1.4 not 1.2. [I, low confidence]
Value chain — mine to model · who captures the margin
Miners
DRC, Mongolia
Indonesia, Chile
TSMC / Samsung
Taiwan, Korea
3nm–5nm fabs
Nvidia
Design + IP
Fabless
Cloud / DC Ops
CoreWeave, Meta
Google, Microsoft
AI Companies
OpenAI, Anthropic
Mistral, xAI
End Users
Enterprises
Developers
Gross margin
5–15%
Gross margin
~53%
Gross margin
~75%
Gross margin
~53%
Margin
varies
Price paid
$20–200/mo
What they sell
Raw ore & refined metals
What they sell
GPU & CPU dies
What they sell
~$1.5–2M/rack [D]
What they sell
$3.30–3.50/GPU-hr [A]
What they sell
API calls & products
What they pay
Subscription / usage
Revenue scale
~$1–3/day wage
(ASM workers)
Revenue scale
$90B/yr [17]
Revenue scale
$130B/yr [18]
Revenue scale
$2.1B/qtr [C]
Revenue scale
$billions/yr
Spend
$20–$200/mo
Sources: [A] CloudSyntrix reserved pricing · [C] CoreWeave Q1 2026 · [D] Analyst Vinh/Benzinga · [3] Amnesty International DRC · [17] TSMC Q1 2025 · [18] Nvidia FY2025 · ASM = artisanal & small-scale mining
blackwell_gb200_nvl72_true_cost_v8.xlsx
A1fx=SUM(materials) · GB200 NVL72: 72×B200 + 36×Grace + NVLink + liquid cooling · elemental proxy: A100 ICP-OES Falk et al. 2026 [P]
#
Material / origin
Est. mass
% rack
Est. cost
Confidence
▣  Structural — rack frame, trays, power shelves, CDU enclosure
2
FeSteel — chassis, 18 compute tray frames, rack rails, power shelves
~520 kg
38%
~$4,500
medium
3
AlAluminium — cold plates, liquid cooling manifolds, heatsink frames
~290 kg
21%
~$800
medium
4
~Coolant & thermal interface — liquid loop, CDU fluid, thermal paste
~180 kg
13%
~$1,200
low
5
PCB substrate — FR4 fibreglass, 18 compute trays + 9 NVLink switch trays
~160 kg
12%
~$4,000
low
STRUCTURAL SUBTOTAL
~1,150 kg
84%
~$10,500
◎  Conductors — A100 ICP-OES ×72 GPU proxy [P] · Blackwell unadjusted
7
CuCopper — 1,374 g/GPU measured (A100) ×72 + NVLink busbars + power railsICP-OES A100
~160 kg
11.8%
~$1,600
low
8
SnTin — 20.3 g/GPU measured (A100) ×72 + NVLink switch traysICP-OES A100
~2.5 kg
0.18%
~$56
low
CONDUCTORS SUBTOTAL · A100 proxy scaled ×72
~163 kg
12%
~$1,656
◈  Compute silicon — 72× B200 + 36× Grace + NVLink ASICs + HBM3e stacks
10
SiSilicon — 72× B200 GPU die, 36× Grace CPU die, HBM3e stacks, NVLink ASICsKEY
~50 kg est.
3.7%
~$1.5–2M
low
COMPUTE SUBTOTAL · B200 unit cost undisclosed by Nvidia
~50 kg
3.7%
~$1.5–2M
⚠  Contested extraction — A100 ICP-OES: 93% of GPU mass hazardous [P] · scaled ×72 GPUs · Blackwell values unmeasured
12
CoCobalt — 0.0165 g/GPU (A100) ×72 = ~1.2 g min. · DRC artisanal minesHAZARDOUSCONTESTED
~1.2 g
trace
~$0.07
low
13
AuGold — 0.0426 g/GPU (A100) ×72 = ~3.1 g min. · bond wire connectionsCONTESTED
~3.1 g
trace
~$240
low
14
RERare earths — Er, Nd, Dy · Bayan Obo (Inner Mongolia) + NVLink magnet assembliesCONTESTED
~20 g
trace
~$30
low
15
HfHafnium — high-k gate dielectric · 72 B200 + 36 Grace dies at 3–5nm nodeCONTESTED
trace
trace
est.
unknown
16
AgSilver — 0.553 g/GPU (A100) ×72 = ~40 g min. · contact surfacesCONTESTED
~40 g
trace
~$35
low
CONTESTED / HAZARDOUS SUBTOTAL · A100 proxy ×72 · Blackwell values unknown
>65 g
trace
~$305
TOTAL RACK · GB200 NVL72 · 72×B200 + 36×Grace + NVLink + liquid cooling
~1,360 kg
100%
~$1.5–2M est.
Steel is 38% of this rack by weight. Silicon is 3.7%. The cobalt — measured at 0.0165 g per A100 GPU — is a rounding error. And yet it comes from the most contested supply chain on the planet.

Where each element sits in the value chain maps almost exactly to how little the people who extract it are paid and how little legal protection they have. Artisanal cobalt miners in the DRC earn $1–3/day. Nvidia earns a 75% gross margin. No invoice anywhere in this chain prices the hazardous mass, the radioactive tailings, or the groundwater at the mine. The B200 profile remains unmeasured in the peer-reviewed literature.

C1fx=120kW × 24h × 1.2PUE × 0.386kgCO₂/kWh = 1,334 kg/day · range 1,334–1,556 (PUE 1.2–1.4) · 2yr = ~974k–1.14M kg CO₂e
Embodied CO₂e
20.5–60k kg
PCF lb + full-rack modelled
medium-low [L]
GPU layer — confirmed
20,466 kg
9× HGX B200 PCF × 2,274 kg
high confidence [L]
Operational CO₂e (2yr)
~974k kg
Grid power, PUE 1.2
medium confidence
Lifetime multiplier
16–30×
Operational ÷ embodied
medium confidence
GPU lifespan
2.8 yrs
Empirical, 18,688 GPUs [11]
high confidence
Crossover day
Day 15–45
PCF lower bound to full-rack est.
medium confidence
Unbooked carbon @$50/t
~$48,700
2yr life · no invoice exists
medium confidence
Every single day — 1,334 kg of CO₂
🍔
~300
beef burgers
(~4.5 kg CO₂ each incl. beef, bread, cooking)
✈️
1.3
London → New York
return flights (990 kg each)
🚘
5,379 km
in a petrol car
London to Dubai and back
📱
155,000
smartphone charges
(8.6 g CO₂ each)
Every year — 487,310 kg of CO₂
🌍
34
US residents’ entire
annual carbon footprint
(US fossil CO₂ avg 13,800 kg/person/yr — Statista/IEA 2023)
🌳
23,186
trees absorbing CO₂
for a full year
(each tree absorbs ~21 kg/yr)
✈️
101
London → New York
return flights
(4,800 kg CO₂ each)
Full 2-year lifetime — 974 tonnes of CO₂ — what does that look like?
👥
68
US residents’ entire
annual carbon footprint
(14,400 kg/person/yr avg — Our World in Data 2023)
🏈
198
Olympic swimming pools
of CO₂ gas
(that’s how much space it takes up)
🌳
46,381
trees absorbing CO₂
for a full year to offset it
that’s a forest of 46,000 trees
⏱  The crossover — Day 15
Making this rack — all the mining, shipping, and manufacturing — produces about 20,466 kg of CO₂ (Nvidia’s own HGX B200 PCF figure ×9 for the GPU layer).
Running it produces 1,334 kg every single day.
By Day 15, the electricity it has used has already released more carbon than it took to build the whole machine.
Every day after that: the machine’s existence adds more carbon than making another one would.
PUE uncertainty range
kWh / day
3,456 kWh (PUE 1.2)4,032 kWh (PUE 1.4)
kg CO₂ / day
1,334 kg (PUE 1.2)1,556 kg (PUE 1.4)
2yr lifetime CO₂
~974,000 kg~1,136,000 kg
Cumulative CO₂e — embodied vs. operational over 2-year rack life
OPERATIONAL — ~974,000 kg (97% of lifetime total)
Embodied ~20.5k–60k kg (2–6%) · PCF lb: 20,466 kg [L]Operational ~974k–1.14M kg (97%)
Crossover arrives within 15–45 days depending on embodied carbon assumption. Nvidia's own HGX B200 PCF (ISO 14067, reviewed by WSP) gives 2,274 kg CO₂e per 8-GPU baseboard — 9× for 72 GPUs = 20,466 kg confirmed lower bound. At 1,334 kg/day that's Day 15. Add Grace CPUs, NVLink trays, rack structure, and CDU (~32,000–60,000 kg full rack) and crossover is Day 24–45. At 1,334 kg/day, one GB200 NVL72 rack emits what ten 8×H100 DGX systems would. The crossover arithmetic is robust across the full PUE uncertainty range. [P,10,11]
◎  Carbon by phase
#
Phase
kg CO₂e
% total
Timing
Confidence
2
Mining & refining — 72 GPU proxy + Grace CPUs + NVLink
~20,000
2.0%
one-time
low
2b
HGX B200 PCF (Nvidia/WSP, ISO 14067) — 8-GPU baseboard: 2,274 kg CO₂e cradle-to-gate · 9× = 20,466 kg confirmed GPU-layer lower boundNVIDIA PCF
20,466
lb only
one-time
high
2c
HGX B200 PCF breakdown: HBM3e memory 49% (1,123 kg), ICs 28% (643 kg), thermal 12% (267 kg) — per baseboard [L]
see left
one-time
high
3
Semiconductor fab — Blackwell IC: Scope 2 = 59%, Scope 3 = 30%, Scope 1 = 12% of mfg CO₂e [J]TECHINSIGHTS
~16,000
1.6%
one-time
medium
3b
Manufacturing location note — Scope 2 (grid electricity) is the single biggest lever; TSMC Taiwan grid vs US/Korea fab = very different CO₂e [J]
varies
location-dependent
medium
4a
Ocean freight — Taiwan → US East Coast · 1.36t · ~12,000 km
~700
0.07%
one-time
low
4b
Air freight — GPU dies Taiwan → packaging (high-value, time-sensitive)
~400
0.04%
one-time
low
4c
Domestic trucking — port → data center · multi-state · oversized load
~350
0.04%
one-time
low
4d
Assembly ops — Supermicro/ODM facility, test burn-in energy
~500
0.05%
one-time
low
5
Grid power — 120 kW IT load (compute + NVLink + Grace)
~562,000
56.0%
~774 kg/day
medium
6
Grid power — liquid cooling overhead (PUE 1.2 = +20% above IT load)
~112,000
11.2%
~154 kg/day
medium
7
Grid power — CDU, power delivery, networking infrastructure
~259,000
25.8%
~356 kg/day
low
TOTAL LIFETIME CO₂e — 2 YEARS · PUE 1.2
~974,000 kg
100%
~1,334 kg/day
Nvidia counter-claim [K]: “25× greater performance per watt vs prior generation” & “50× more energy efficiency per token (Blackwell Ultra).” These per-token efficiency gains are real. But GB200 NVL72 draws ~120 kW vs H100’s 10.2 kW — ~10× more absolute power per rack. More efficient per inference ≠ less total power. Jevons’ Paradox: efficiency lowers cost-per-token, expanding demand, expanding total deployment. [K, C-09]
vendor claim
unverified
E1fx=gross_revenue − opex − debt_service · reserved 3yr contract $3.30–3.50/GPU-hr [A] · rack ASP ~$1.5–2M [D] · 2.8yr lifespan [11]
ⓘ  Market structure — reserved contracts dominate; spot is a small slice
Reserved 3-year take-or-pay contracts at $3.30–3.50/GPU-hr are the dominant commercial structure for GB200 capacity [A]. Customers commit to pay whether they use the capacity or not — providers are insulated; customers bear utilisation risk. CoreWeave’s $14.2B Meta deal and $22.4B OpenAI commitment are reserved contracts [B]. On-demand spot pricing ($10.50–$27/hr) exists for uncommitted capacity but carries full Rubin obsolescence risk when the next generation arrives [E, G].
◎  Daily P&L — reserved contract model · medium confidence
#
Line item
Per day
2L
Revenue — reserved low: $3.30/GPU-hr × 72 × 95% util × 24h [A]
+$5,417
2H
Revenue — reserved high: $3.50/GPU-hr × 72 × 95% util × 24h [A]
+$5,746
spot ref
Spot on-demand: $10.50/GPU-hr × 72 GPUs × 70% util × 24h = $12,701/day gross. Higher but uncommitted — bears full obsolescence risk when Rubin arrives [E, G].
+$12,701
3
− Electricity — 3,456 kWh/day @ $0.10/kWh [15]
−$346
4
− Liquid cooling / CDU operations
−$500
5
− Colocation — power density premium (120 kW racks require specialist facilities) [16]
−$800
6
− Network egress + NVLink fabric operations
−$200
7
− Staff & ops overhead (amortized per rack)
−$300
7D
− Debt service — ~9.3% on $1.5M rack (CoreWeave SOFR+4% facility) [B]
−$382
8L
= Net profit/day — reserved low ($3.30/hr)
~$2,889/day  (53% margin)
8H
= Net profit/day — reserved high ($3.50/hr)
~$3,217/day  (56% margin)
9
Hardware cost — analyst ASP $1.5M–$2M per rack [D]
$1.5–2M
10
Payback — $1.5M ÷ $2,889–3,217/day
459–519 days (15–17 months)
11
Payback — $2.0M ÷ $2,889–3,217/day
622–693 days (21–23 months)
⏱  Profit window — lifespan 2.8yr = 1,022 days [11] · adjusted for deployment lag [H,I]
⚠  Deployment lag — real cost not in the model
Deployment lag is real and unmodelled. The Information (May 2026) reports OpenAI, Oracle, and Meta had a hard time getting GB200 NVL72 up and running, and are still in early phases of rollout. Early 2025 customers including Microsoft and Amazon found chips not working properly in testing — some reduced orders [H]. An Nvidia internal email described validation requiring extensive on-site support and documentation rewriting [I]. During deployment lag the rack earns nothing but still incurs debt service (~$382/day) and colocation costs (~$800/day).
$1.5M rack · $3.30/hr · 1mo lag
Deploy lag: 30 days idle
Dead cost: ~$35k
Net: ~$1.33M
Best case — fast deployment
$1.5M rack · $3.30/hr · 3mo lag
Deploy lag: 90 days idle
Dead cost: ~$106k
Net: ~$1.09M
Realistic per The Information [H]
$2.0M rack · $3.30/hr · 3mo lag
Deploy lag: 90 days idle
Dead cost: ~$106k
Net: ~$586k
Thin — any further delay painful
CoreWeave actual Q1 2026
Revenue: +112% YoY
Op. margin: 1%
Backlog: $99.4B
CapEx burden compresses net [C]
⚠  Obsolescence — the H100 precedent
△  Obsolescence risk — the H100 precedent
H100 spot rates fell 70% when Blackwell shipped at scale — from $8–10/hr to $2.85–3.50/hr now [F]. Jensen Huang at GTC 2025: “When Blackwell starts shipping in volume, you couldn’t give Hoppers away.” Rubin ships 2H 2026 [G]. Reserved take-or-pay contracts insulate the cloud provider — the customer bears the risk of paying for compute that is no longer state-of-the-art. CoreWeave’s $99.4B contracted backlog is largely locked; spot capacity is not.
◎  Margin by layer — from mine to model
#
Entity
Role
Gross margin
Revenue scale
Source
1
Miners — DRC, Mongolia, Indonesia
Raw extraction
5–15%
$bn commodity
[5]
2
TSMC
Fab / wafers
~53%
$90B/yr
[17]
3
Nvidia
Design + IP
~75%
$130B/yr
[18]
4
CoreWeave — reserved contract gross
DC ops
~53–56%
$2.1B Q1 2026
[B,C]
4b
CoreWeave — operating margin after CapEx
Net after build
~1%
Q1 2026 actual
[C]
5
Artisanal miners — DRC cobalt (ASM)
ASM cobalt
<5%
~$1–3/day wage
[3,P]
⚠  Unbooked externalities — costs that appear on no invoice anywhere in this supply chain
Climate
Carbon @$50/t — 2yr operational ~974k kg CO₂e · no invoice, no regulation
~$66/day
~$48,700 life
unbooked
medium
Refrigerant HFC emissions — data centre air-side cooling uses HFCs (GWP 1,000–9,000× CO₂) · F-gas losses not in Scope 1 for many operators
unpriced
unpriced
unbooked
low
Fab perfluorocarbons (PFCs) — CVD/etch process gases · GWP 10,000–24,000× CO₂ over 100yr · excluded from standard carbon accounting at TSMC and peers
unpriced
unpriced
unbooked
low
Water & chemical pollution
Acid mine drainage — cobalt extraction at DRC sites · sulphuric acid + heavy metals leach into groundwater · Lualaba River contamination documented[3,P]
unpriced
unpriced
unbooked
low
Fab chemical discharge — TSMC treats ~150,000t wastewater/day · photoresists, HF, H₂SO₄, NH₃, CMP slurries · residual chemical load into Hsinchu aquifer[13]
unpriced
unpriced
unbooked
low
Fab water consumption — ~1,173 L TSMC water per B200 IC (TechInsights) · ~118,000 L total for rack chips · treated discharge not zero-impact[J]
unpriced
unpriced
unbooked
medium
Cooling fluid leaks — glycol-based CDU coolants · environmentally persistent · no standardised leak accounting per rack[I]
unpriced
unpriced
unbooked
low
Air pollution
Mining dust & exhaust — open-pit PM2.5/PM10 particulates + diesel exhaust at DRC, Mongolia, Indonesia mine sites · no air quality monitoring at ASM scale[3]
unpriced
unpriced
unbooked
low
Copper smelter SO₂ & arsenic — copper refining (DRC, Zambia) releases sulphur dioxide, arsenic, lead vapour · documented lung disease in proximate communities[7]
unpriced
unpriced
unbooked
low
Radioactive tailings dust — Bayan Obo rare earth processing · thorium + uranium co-extracted with Nd, Dy, Er · windblown tailings contaminate Inner Mongolia farmland[5]
unpriced
unpriced
unbooked
low
End of life
E-waste leachate — 93% of GPU mass hazardous (A100 proxy) · informal recycling via acid baths & open burning at Agbogbloshie (Ghana), Guiyu (China) · lead, mercury, cadmium into soil and groundwater[P,9]
unpriced
unpriced
unbooked
low
PFAS fire suppression — data centre decommission & rack fire suppression uses per-& polyfluoroalkyl substances (PFAS) · “forever chemicals” · no industry standard for end-of-life rack disposal
unpriced
unpriced
unbooked
low
Labour & community
DRC ASM cobalt — ~$1–3/day wage · no safety equipment · tunnel collapse deaths · child labour documented · zero legal liability upstream[3,P]
unpriced
unpriced
unbooked
low
Community health burden — heavy metal exposure near smelters, tailings ponds · no remediation cost allocated to any entity in this supply chain
unpriced
unpriced
unbooked
low
None of the above appears on any invoice, earnings call, regulatory filing, or cloud pricing page. Methods to price most of these exist — carbon trading, EPA health-cost models, water pricing mechanisms, polluter-pays liability. The absence is not a measurement problem. It is a disclosure problem.
F1fx=items_not_on_any_invoice() + unknown_quantities() → 10 caveats · v8.0
C-01
B200/GB200 elemental composition — unknown. No peer-reviewed ICP-OES or equivalent teardown of any Blackwell GPU exists as of May 2026. All elemental claims use Falk et al. 2026 A100 data as proxy. Blackwell dies are larger, packaging more complex (NVL co-packaging), and the rack includes Grace CPUs and NVLink ASICs not present in A100-era systems.
⚠ The 93% hazardous mass figure is empirically confirmed for A100 only. It is directionally applicable to Blackwell but not measured.
C-02
Power draw and PUE — more uncertain than modelled. Oracle confirms “over 120 kW at peak” but sustained draw during typical workloads may be lower. PUE 1.2 assumes efficient liquid cooling, but an Nvidia internal email (Dec 2025) described Microsoft’s GB200 facility-level cooling as “wasteful” — the setup uses a second air-cooling layer on top of in-rack liquid cooling, trading water efficiency for energy use. Real-world PUE may be 1.3–1.4 at some facilities, increasing carbon by 8–17%. [I]
⚠ Our 1.2 PUE assumption is optimistic for at least some real deployments.
C-03
Rack ASP — sell-side estimate only. Analyst Vinh (Benzinga) estimates $1.5M–$2M per rack [D]. Nvidia hardware cost to OEMs not publicly disclosed. Our previous $3–5M estimate was likely 2–3× too high.
C-04
Reserved contract pricing — not public. $3.30–3.50/GPU-hr sourced from CloudSyntrix analysis of private cloud Blackwell contracts [A]. Actual CoreWeave contract rates are confidential. On-demand spot ($10.50–$27/hr) is observable but represents a different risk structure.
C-05
Legal liability gap — cobalt. No company in the cobalt supply chain is legally liable for DRC extraction or labor conditions. ASM accounts for ~20% of DRC cobalt. Nvidia’s Responsible Minerals Policy covers disclosure, not remediation.
★ Peer-reviewed: Falk et al. 2026 [P] confirms Co as hazardous in A100
C-06
Cooling water — deployment-dependent, not a fixed figure. Our ~5,000 L/day estimate may be misleading. Supermicro’s GB200 NVL72 datasheet lists multiple CDU configurations including 250 kW, 240 kW, and 180 kW liquid-to-air solutions — some configurations require no facility water at all (closed-loop/liquid-to-air). An Nvidia internal email described Microsoft’s GB200 cooling as “wasteful due to the size and lack of facility water use” — suggesting Microsoft’s design uses more energy but less water than an evaporative design would. [I] The correct statement is: cooling water varies from near-zero (closed-loop dry cooler) to thousands of litres per day (evaporative), depending entirely on facility design. TSMC fab water (~1,173 L per B200 IC, ~118,000 L for the rack’s chips) is separately accounted. [J]
⚠ Do not cite the ~5,000 L/day figure without specifying facility cooling design. It is wrong for some deployments.
C-07
All figures are lower bounds. Falk et al. 2026 explicitly state their ICP-OES results exclude losses during refining, processing, and component manufacturing. Logistics carbon, NVLink tray footprint, and Grace CPU materials are not independently quantified.
★ Peer-reviewed: Falk et al. 2026 [P]
C-08
Carbon price absent. ~974,000 kg CO₂e over 2 years. At $50/tonne = ~$48,700/rack — unbilled on any invoice. No mandatory carbon price applies to US data center operations.
C-09
Jevons’ Paradox — Nvidia’s own marketing confirms it. Nvidia’s sustainability page claims GB200 NVL72 delivers “25× greater performance per watt vs prior generation” and Blackwell Ultra delivers “50× more energy efficiency per token.” [K] These per-token efficiency gains are real and measurable. But they say nothing about total power. GB200 NVL72 draws ~120 kW; the H100 DGX it replaces drew 10.2 kW. “25× performance per watt” + “10× more absolute power” = 2.5× more total power per rack, not less. More efficient per inference does not mean less total environmental burden — it means the ceiling for total deployment rises. Nvidia also claims AI tasks use “100,000× less power than a decade ago” with no methodology cited — this compares best-case 2024 inference per-token against 2014 training compute and is not a statement about total system power consumption. [K]
★ Peer-reviewed: Falk et al. 2026 [P]; Luccioni, Strubell & Crawford, ACM FAccT 2025
Vendor source (marketing): Nvidia Sustainable Computing page, nvidia.com, accessed May 2026 [K]
C-10
Obsolescence timeline uncertain. Hyperscalers depreciate GPUs over 4–6 years for accounting purposes. Technological useful life may be 1–2 years given Nvidia’s annual cadence [G]. H100 spot rates fell 70% within one product cycle [F]. Reserved contracts transfer this risk to the customer.
C-12
Manufacturing water — upgraded from estimate to modelled figure. TechInsights (Aug 2025) applied the Murphy yield model, 90% fab utilisation, 98% package yield, and location-based Scope 2 accounting to Blackwell. Result: ~310 gallons (1,173 L) of water per Blackwell IC. Our previous figure of ~2,000 L/wafer overstated by ~41%. Full rack: ~118,000 L for IC manufacturing alone (72 B200 + 36 Grace + NVLink ASICs estimated), equivalent to 833 Americans’ daily water use. This is still IC-only — excludes packaging, assembly, cooling, and operational water. Architecture matters: Blackwell has ~20 cm² silicon vs MI300X >40 cm²; produces ~20% less total CO₂e in manufacturing but is ~2× more carbon-intensive per cm². Scope 2 (grid electricity) = 59% of Blackwell manufacturing emissions — meaning fab location is the single largest decarbonisation lever. [J]
★ Source: TechInsights, “The Hidden Environmental Cost of Advanced AI Chips,” Aug 2025. Modelled, not peer-reviewed — proprietary methodology.
C-11
Deployment lag not modelled. The Information (May 2026) reports that OpenAI, Oracle, Meta, Microsoft, and Amazon all experienced significant delays getting GB200 NVL72 up and running. Early 2025 chips failed testing; customers reduced orders or reverted to Hopper. Nvidia’s internal email on a Microsoft deployment noted validation documentation required extensive rewriting and handover processes needed “a lot more solidification.” Our P&L assumes revenue begins immediately. A 3-month lag on a $2M rack costs ~$106k in dead debt+colo and compresses the already thin profit window significantly. [H, I]
⚠ Take-or-pay contracts may require customers to pay during deployment lag even if the rack is not earning. Confirms C-04: reserved rate structure needs verification.
What can be publicly audited — and what cannot
Material bill
Embodied carbon
Water burden
Hazardous mass
CoWoS footprint
End-of-life risk
Can audit publicly
✗ Cannot
✗ Cannot
△ IC only [J]
△ A100 only
✗ Cannot
✗ Cannot
Methods exist
✓ ICP-OES
✓ LCA modelling
✓ Facility audits
✓ ICP-OES
✓ DC testbeds
✓ Hardware refresh
Last peer-reviewed
A100 (2020)
Falk et al. 2026
TechInsights 2025
93% — A100
Not published
WEEE estimates
The gap between what we can price and what we can audit is not a data problem. It is a transparency problem.

The infrastructure of artificial intelligence is commercially visible and environmentally opaque by design. Every GPU sold is tracked to the dollar. Every kilowatt-hour is billed. The cobalt content, the water, the hazardous mass, the embodied carbon — none of these appear on any invoice, any earnings call, or any regulatory filing. The methods to measure them exist. The data does not.

This ledger is a proxy model built from what is publicly available. It is not an audit. It is an argument that an audit is overdue.

Sources & methodology — v8.0
  1. [P] PEER-REVIEWED: Falk, S. et al. “From computation to environmental cost.” Commun. Earth Environ. 7, 397 (2026). DOI: 10.1038/s43247-026-03537-5. Open Access CC BY 4.0.
  2. [1] Supermicro H100 NVL GPU SuperServer spec; full rack ~1,360 kg. Distinct from single DGX H100 unit.
  3. [2] Nvidia DGX H100/H200 User Guide — 8U, 130.45 kg max, 10.2 kW max. docs.nvidia.com/dgx/dgxh100-user-guide/
  4. [3] Amnesty International “This is What We Die For” (2016); Nvidia Responsible Minerals Policy 2024
  5. [4] USGS Mineral Commodity Summaries 2024 — Gold, Silver; LBMA
  6. [5] USGS Mineral Resources Program — Rare Earth Elements
  7. [6] USGS Mineral Commodity Summaries — Hafnium; TSMC HfO2 gate dielectric
  8. [7] USGS Mineral Commodity Summaries 2024 — Copper; LME spot pricing
  9. [8] USGS Mineral Commodity Summaries 2024 — Tin; ITRI supply chain
  10. [9] European Parliament WEEE Directive 2012/19/EU; RoHS classification
  11. [10] US EIA eGRID 2023 (0.386 kg CO2/kWh); Nvidia DGX H100 TDP 10.2 kW; PUE 1.4x Uptime Institute 2024
  12. [11] Ostrouchov et al. (2020) “GPU lifetimes on Titan supercomputer.” SC20. 18,688 GPUs, 7 years, mean failure 2.8 yrs.
  13. [12] Science Based Targets initiative; Dell Technologies PCF methodology (server hardware proxy)
  14. [13] TSMC 2023 Sustainability Report; USGS US water use (142 L/person/day)
  15. [14] CoreWeave pricing — GB200 on-demand: CoreWeave ~$10.50/GPU-hr (Spheron, Mar 2026). Market range $10.50–$27.04/GPU-hr, avg $20.14 (getdeploying.com, May 2026). $42/hr figure was wrong — likely misread from $68.80/hr 8×HGX B200 node price.
  16. [15] US EIA Average Commercial Electricity Price 2024 (~$0.10/kWh)
  17. [16] Uptime Institute 2024 Global Data Center Survey
  18. [17] TSMC Q1 2025 earnings — gross margin 53.1%
  19. [18] Nvidia FY2025 Annual Report — data center gross margin ~74.6%
  20. [19] US EPA Social Cost of Carbon 2024 ($51/metric tonne CO2)
  21. [A] Reserved contract pricing $3.30–3.50/GPU-hr: CloudSyntrix, “How NVIDIA Blackwell GPUs Are Transforming Cloud Costs and Revenue,” Feb 2025.
  22. [B] CoreWeave debt SOFR+4% (~9.3%); Meta $14.2B deal; OpenAI ~$22.4B commitment: mlq.ai CoreWeave Deep Dive (citing Wedbush/Finterra “The GPU Debt Wall,” Feb 2026).
  23. [C] CoreWeave Q1 2026: revenue $2.1B (+112% YoY), operating margin 1% (from 17%), backlog $99.4B, CapEx $6.8B: Investing.com / HyperFRAME Research, May 2026.
  24. [D] GB200 NVL72 rack ASP $1.5M–$2M: analyst Vinh, Benzinga 2024. Sell-side estimate — Nvidia hardware cost to OEMs not publicly disclosed.
  25. [E] Spot GB200 pricing $10.50–$27.04/GPU-hr, avg $20.14: getdeploying.com, May 2026. CoreWeave on-demand ~$10.50: Spheron Network, Mar 2026.
  26. [F] H100 spot collapse 70% (from $8–10/hr to $2.85–3.50/hr): stanleylaman.com, Nov 2025. $176B hyperscaler depreciation adjustment risk through 2028.
  27. [G] Nvidia annual product cadence; Jensen Huang “couldn’t give Hoppers away”; CoreWeave GB300 NVL72 deployment: Data Center Dynamics, May 2026.
  28. [A] Reserved contract pricing $3.30–3.50/GPU-hr: CloudSyntrix, “How NVIDIA Blackwell GPUs Are Transforming Cloud Costs and Revenue,” Feb 2025. 3-year take-or-pay structure.
  29. [B] CoreWeave SOFR+4% debt (~9.3%); Meta $14.2B deal through 2031; OpenAI ~$22.4B commitment: mlq.ai CoreWeave Deep Dive, citing Wedbush/Finterra “The GPU Debt Wall,” Feb 2026.
  30. [C] CoreWeave Q1 2026: revenue $2.1B (+112% YoY), operating margin 1% (from 17%), backlog $99.4B, CapEx $6.8B: Investing.com / HyperFRAME Research, May 2026.
  31. [D] GB200 NVL72 rack ASP $1.5M–$2M: analyst Vinh estimate, Benzinga 2024. Nvidia hardware cost to OEMs not publicly disclosed.
  32. [E] Spot GB200 $10.50–$27.04/GPU-hr, avg $20.14: getdeploying.com, May 2026. CoreWeave on-demand ~$10.50: Spheron Network, Mar 2026.
  33. [F] H100 spot fell 70% from $8–10/hr to $2.85–3.50/hr: stanleylaman.com, Nov 2025. $176B hyperscaler depreciation adjustment risk through 2028.
  34. [G] Nvidia annual product cadence; Jensen Huang “couldn’t give Hoppers away”; CoreWeave GB300 NVL72 deployment: Data Center Dynamics, May 2026.
  35. [H] GB200 NVL72 deployment struggles: Ana Gardezi, The Information podcast, May 2026. OpenAI, Oracle, Meta, Microsoft, Amazon all experienced delays; early chips failed testing; some customers switched back to Hopper GPUs; Nvidia has no clear competitive alternative.
  36. [I] Nvidia internal email (NVIS team), Dec 2025, via Business Insider / Tekedia. Two GB200 NVL72 racks at Microsoft for OpenAI: cooling described as “wasteful due to size and lack of facility water use”; validation documentation required extensive rewriting; handover between Nvidia and Microsoft “required a lot more solidification.” Both racks achieved 100% pass rate on compute tests after support. DOI/URL: businessinsider.com/nvidia-microsoft-ai-gpu-blackwell-cooling-wasteful-2025-12.
  37. [J] TechInsights, “The Hidden Environmental Cost of Advanced AI Chips,” Aug 2025. Manufacturing emissions and water use for Blackwell (192GB) vs AMD MI300X. Method: Murphy yield model, 90% fab utilisation, 98% package yield, location-based Scope 2. Blackwell: ~20 cm² silicon, ~310 gal (1,173 L) water/IC, Scope 2 = 59% of mfg CO₂e, ~20% less total CO₂e than MI300X but ~2× more carbon-intensive per cm². IC portion only. techinsights.com (Aug 2025).
  38. [L] Nvidia HGX B200 Product Carbon Footprint (PCF) Summary. ISO 14067-conformant, third-party reviewed by WSP. One HGX B200 baseboard (8× B200 GPUs, 32 kg): 2,274 kg CO₂e cradle-to-gate. Breakdown: HBM3e 49% (1,123 kg), ICs 28% (643 kg), thermal 12% (267 kg), assembly 5.6%, transport <1%. Excludes use-phase and end-of-life. URL: images.nvidia.com/aem-dam/Solutions/documents/HGX-B200-PCF-Summary.pdf (Jul 2025).
  39. [K] Nvidia Sustainable Computing page, nvidia.com (accessed May 2026). Claims: GB200 NVL72 “25× greater performance per watt vs prior generation”; Blackwell Ultra NVFP4 “50× more energy efficiency per token”; AI tasks “100,000× less power than a decade ago” (no methodology cited). NVLink 5.0: 1.3 pJ/bit. Vendor marketing — per-token efficiency claims are directionally plausible but do not imply reduced total power consumption. Absolute power draw (~120 kW/rack) and Jevons’ Paradox effects not addressed.
The Cost of Blackwell · v8.0 · GB200 NVL72 · 72× B200 + 36× Grace · ~120 kW · ~1.36 tonnes
A confidence-banded proxy model · Not a forensic audit · Elemental data: A100 proxy (Falk et al. 2026) · B200 ICP-OES not yet published