GPU Residual Values & Depreciation for AI Datacenters

AI Summary • 12 Data Sources Verified

How fast do GPUs depreciate?

GPUs follow an entropic decay curve where value remains stable for 12-18 months, then drops 40-60% immediately upon next-generation announcements.

Key Data Points

  • H100 residual values typically stay at 65-75% after 24 months
  • A100 residual values drop to 45-55% after 24 months
  • 36-month residual value is typically <30%
  • Accelerated depreciation (30-40% in Year 1) is standard for financial models

Understanding GPU residual values is critical for lease vs buy decisions, refinancing strategies, and balance sheet optimization. Track real-time secondary market values and depreciation curves across all major GPU models.

H100 Residual

65-75%

After 24 months

A100 Residual

45-55%

After 24 months

Depreciation Method

30-40%

Year 1 typical

Secondary Market

Active

High liquidity

Why Residual Values Matter

GPU residual values directly impact your total cost of ownership (TCO) and return on investment (ROI) across multiple financing scenarios. Whether you're evaluating lease vs buy economics, planning equipment refreshes, or structuring asset-backed financing, residual projections are foundational.

For leased GPUs, higher residual values reduce monthly lease payments and improve IRR calculations. For owned assets, they determine refinancing capacity and provide downside protection in secondary markets. Infrastructure funds and lenders rely on conservative residual curves to underwrite AI datacenter projects.

The rapid pace of GPU innovation creates unique depreciation dynamics. Next-generation releases, competitive positioning, and market demand all influence how values decay over 24-60 month holding periods. Understanding these patterns is essential for board-ready financial models.

Key Topics Covered

H100 & A100 Residuals

  • • 24, 36, and 60-month residual projections
  • • SXM vs PCIe variant value differences
  • • Secondary market liquidity analysis
  • • Impact of next-gen releases (B100, H200)

Depreciation Curves

  • • Straight-line vs accelerated methods
  • • GAAP and tax treatment considerations
  • • Regional accounting standards (US, EU)
  • • Impact on EBITDA and balance sheets

Financing Implications

  • • Lease vs buy sensitivity analysis
  • • Refinancing capacity over time
  • • Asset-backed lending covenants
  • • Sale-leaseback residual guarantees

Market Intelligence

  • • Secondary market transaction data
  • • Broker pricing benchmarks
  • • Demand indicators by model/region
  • • Upgrade cycle timing predictions

Example: How Residuals Impact IRR

Consider a 36-month lease for 8x H100 GPUs with a total equipment value of $240,000:

Conservative Residual: 50%

Equipment Value$240,000
36mo Residual (50%)$120,000
Depreciation to Recover$120,000
Monthly Payment$4,100
Lessor IRR12-14%

Optimistic Residual: 70%

Equipment Value$240,000
36mo Residual (70%)$168,000
Depreciation to Recover$72,000
Monthly Payment$2,650
Lessor IRR12-14%

Impact: $1,450/month savings (35% reduction)

A 20-point increase in residual value reduces monthly payments by ~35%, demonstrating why accurate residual projections are critical for competitive lease pricing and lender underwriting.

GPU Asset Management Guides

GPU Finance & Residual Tools

FREE TOOL

GLRI (GPU Lease Rate Index)

Track H100/A100/B200 lease rate trends - core market data

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PRO TOOL

GPU Residual/LTV Calculator

Calculate GPU depreciation and residual values

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Lease vs Own Model

Strategic GPU ownership decision tool

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Performance Risk Model

Model GPU performance degradation over time

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