GPU Depreciation and Useful Life at Hyperscalers

The filings and Burry’s numbers are the core of the debate. I’m pulling the company-level accounting changes and analyst earnings sensitivities next.
The fight is not whether a GPU still powers on in year six. It is whether straight-line depreciation over five to six years matches the period the chip earns an attractive return for its owner. Those clocks have diverged, and the gap is now large enough to move reported earnings by billions of dollars a year.

Five clocks, one argument

GAAP does not prescribe a number of years. It requires management to depreciate an asset over the period it is expected to provide service to that owner. Auditors test the estimate; a revision is applied prospectively, not by restating the past. At least five different durations are being collapsed into “useful life”: physical life until failure, rental life at any price, service life to the first owner, the book life management picks, and the contract term that actually pays for the box. A chip can be fully utilized in year seven and still have lost most of its economic value by year three, because newer silicon does the same work at a fraction of the power and token cost. Straight-line accounting ignores that shape. It charges the same dollar every year while the cash the card generates is heavily front-loaded.

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Recent Findings Supplement (October 2026)

Recent developments (primarily July–October 2026 filings, disclosures, pricing data, and commentary) show the GPU depreciation debate intensifying around real-world utilization and pricing evidence rather than purely theoretical obsolescence. Older NVIDIA GPUs (e.g., A100 from 2020 and H100 from 2022–2023) continue generating revenue through long-term contracts and rising rental rates, while hyperscalers show mixed accounting adjustments. Michael Burry maintains his critique, but counter-evidence from contracts, price hikes, and utilization data has prompted rebuttals.[1][2]

Michael Burry continues pressing the case for 2–3 year economic lives versus 5–6 year book lives, estimating ~$176 billion in understated industry depreciation from 2026–2028, with specific calls on companies like Oracle (~27% earnings overstatement) and Meta (~21%). He has linked recent commentary to historical parallels (e.g., Cisco-era dynamics) and highlighted risks around financing structures and potential insurance for neocloud defaults tied to resale values.[3][4]

• As of mid-October 2026, Burry remains active on the topic via X and Substack references, framing it as a question of whether accounting lives match economic reality amid rapid new-chip efficiency gains.[4]
• Steve Eisman rebutted the thesis in early October 2026, calling it “overly academic” and arguing strong demand (including for older chips) means depreciation period shifts (e.g., 3–4 to 5–6 years) would not materially harm outcomes if AI growth continues.[5]
• NVIDIA has directly engaged with a multi-page analyst memo and public data points (e.g., A100 utilization and contracts) disputing the 2–3 year claim.[6]

Hyperscalers show divergent 2025 accounting tweaks disclosed in 2026 filings, with Amazon taking a more conservative step on AI-driven tech pace while Meta extended lives. These remain the most recent quantified changes.[7][8]

• Effective January 1, 2025, Amazon shortened useful lives for a subset of servers and networking equipment from 6 to 5 years (citing faster AI/ML development), increasing 2025 depreciation by ~$1.4 billion and reducing net income by ~$1.0 billion (~$0.10 per diluted share).[8][9]
• Effective the same date, Meta extended most servers and network assets to 5.5 years, cutting 2025 depreciation by $2.92 billion and boosting net income by $2.59 billion (~$1.00 per diluted share).[10][8]
• Microsoft (FY2026 10-K, ended June 2026) and Alphabet report no further changes to their 2–6 year or generally 6-year server/network policies (prior extensions from ~4 years occurred earlier). CoreWeave holds at 6 years.[11][7]

Rental prices for H100/H200 (and older chips) have risen in mid-to-late 2026, and long-term contracts for legacy GPUs extend well beyond typical depreciation schedules, providing concrete counter-data to rapid-obsolescence claims.[2][12]

• H100 on-demand median prices reached ~$3.81/GPU-hour by mid-October 2026 (up 21% YoY and +9% in the prior four weeks across tracked providers); specific provider actions include CoreWeave ~25% across SKUs in July 2026, Nebius +17% on H100 (Oct 1, second hike in three months), and AWS reserved +20% in July (after +15% in January). H100 (2022-era) on-demand rose 16% vs. a year prior.[2][12]
• CoreWeave disclosed (Q2 2026 earnings and August updates) A100 contracts running into 2029 (nine years post-2020 launch) at attractive pricing; CEO noted prior-gen pricing “at or above where it was years ago,” with strong backlog. Similar extensions noted for other operators.[10][13]
• Independent estimates (October 2026) put certain B300 servers at ~33% of purchase price after two years on resale; older A100s retain meaningful projected rental income value.[11]

NVIDIA’s data-center product cadence remains rapid (annual rhythm referenced from GTC 2025), but evidence of multi-year utilization for prior generations (A100 through 2029, H100 price resilience) and consumer-gaming delays (RTX 60 series reportedly pushed to 2028 due to AI focus) highlight a split between inference/training workloads and gaming.[14][15]

• No major new cadence announcements in the latest period, but utilization data (e.g., seven-to-nine-year-old custom chips at high utilization, A100 fleets still mission-capable) and rental trends are cited as evidence against strict 2–3 year economic lives.[10][13]

Analyst and modeled sensitivities quantify material EPS effects from shorter lives, though actual impacts depend on capex cohorts and revenue realization. Recent modeling (referencing 2026 data) shows the stakes clearly.[16]

• JPMorgan sensitivity (early 2026 framing, still referenced): Shifting recent GPU/networking capex to a 3-year life (vs. 6) would reduce 2025 EPS by ~6–7% at Amazon/Meta/Microsoft, ~6% at Alphabet, and ~17% at Oracle.[16]
• On the 2026 hyperscaler server cohort alone (~$425 billion capex), a 3-year life implies ~$142 billion annual depreciation versus ~$71 billion at 6 years.[16]
• Extension benefits already realized (e.g., Meta’s 2025 change worth ~$2.59 billion net income) illustrate the reverse sensitivity; prior extensions lifted net income by ~4–4.6% in the affected years for several firms.[17]

For competitors or entrants, the debate underscores that accounting assumptions are management estimates under GAAP principles (service period to the owner), not fixed standards; sustained rental demand, long contracts, and price resilience for older silicon currently support longer effective lives in practice, but any slowdown in AI workloads could accelerate write-down risks or force faster cycles. Recent price and contract data provide the strongest empirical pushback to shorter-life claims. No significant regulatory updates on depreciation policies appear in the period reviewed.