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GPU depreciation is a cloud provider’s accounting allocation of the cost of owned infrastructure over an estimated useful life. It is not a separate depreciation charge on a customer’s cloud bill: customers pay the published price for the configured GPU instance under the applicable billing terms.
Depreciation and a cloud GPU bill are different things
When a provider owns servers and GPUs, depreciation spreads the capitalized cost of those assets across the periods in which the provider expects to use them. It is an accounting expense, not the same as the cash paid to buy equipment, its resale value, or the price a customer is charged to rent computing capacity.
For customers, the practical starting point is the configured instance and its billing terms. Google Cloud says, “Each GPU adds to the cost of your instance in addition to the cost of the machine type.” Google Cloud GPU pricing therefore treats GPU pricing as an added part of instance cost, rather than presenting a separate customer-facing depreciation line.
A provider’s depreciation expense may be one factor in its overall economics, but published rental prices do not disclose a per-GPU depreciation schedule. Do not infer one from the hourly rate.
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What company filings say about useful lives
Public filings give useful-life estimates for asset categories defined by each company. The cited disclosures group servers with network equipment or network assets; none establishes a standard useful life for GPUs alone.
| Company and filing | Disclosed useful life | What the disclosure covers |
|---|---|---|
| Alphabet, 2025 Form 10-K | Generally six years | Servers and network equipment. Alphabet says depreciation begins when assets are ready for intended use and is recorded straight-line. |
| Microsoft, fiscal 2026 Form 10-K | Two to six years | Servers and network equipment. Depreciation is straight-line over the shorter of estimated useful life or lease term. |
| Amazon, 2025 Form 10-K | Five to six years | Servers and networking equipment. Amazon changed its server estimate from five to six years effective January 1, 2024, then changed a subset of servers and networking equipment from six to five years effective January 1, 2025. |
| Meta, 2025 Form 10-K | 5.5 years for most, effective January 1, 2025 | Most servers and network assets. Meta reported $13.36 billion in depreciation expense for server and network assets for 2025; that figure is not GPU-only. |
These are company-specific accounting estimates, not forecasts of the date equipment becomes obsolete or ceases to be useful. Companies may also revise estimates as their assessments change, as Amazon’s disclosed adjustments illustrate.
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How to estimate what a workload will cost
For a customer estimate, compare the actual resource configuration and billing arrangement rather than trying to reverse-engineer the provider’s depreciation. Google Cloud’s resource-based commitments documentation describes commitments for predictable workloads and GPU discounts; the customer price depends on the applicable offering and commitment.
Check these inputs for each estimate:
- GPU model and quantity: the accelerator type and number attached to the instance.
- Machine type and attached resources: include the machine charge and relevant CPU, memory, storage, or network resources.
- Usage time: estimate the hours the workload will actually run, not just the maximum possible runtime.
- Region: compare the same location because published prices can vary.
- Pricing mode: account for on-demand rates, commitments, or other applicable terms.
- Cost perspective: distinguish the external customer bill from internal allocation across teams or workloads.
Provider prices can change, so record the date, region, configuration, and pricing mode alongside any quoted estimate.
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When internal cost allocation matters
A shared GPU instance may serve multiple teams, namespaces, or pods. In that case, an organization can allocate its billed or measured instance costs internally using a method suited to its workload. AWS documents a split-cost example for accelerated instances that calculates unit costs for GPU, vCPU-hour, and GB-hour resources. That can help structure workload allocation, but it does not establish how a provider assigns depreciation expense to a customer workload.
Keep the accounting question separate from the allocation question: financial statements report expenses for provider-defined asset groups, while internal chargeback policies decide how an organization distributes its own cloud spend.
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Why the distinction matters
- Depreciation is an accounting estimate about provider-owned assets.
- Purchase cost is the cash paid to acquire hardware; it is not the same as the expense recognized in a particular reporting period.
- Rental price is the customer-facing price for a configured cloud resource under the provider’s terms.
- Utilization affects how much useful work an organization gets from the capacity it pays for, but does not reveal the provider’s asset life estimate.
- Internal allocation distributes an organization’s cloud costs among workloads; it is not the provider’s depreciation schedule.
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
