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 / day3,456 kWh (PUE 1.2)4,032 kWh (PUE 1.4)
kg CO₂ / day1,334 kg (PUE 1.2)1,556 kg (PUE 1.4)
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]
#
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
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.