GPU Rental Prices and Depreciation Over Time

H100 rental prices followed a classic scarcity-to-surplus-to-rebound pattern, with spot/contract indices declining sharply from 2023 peaks before rising again in 2026 due to sustained inference and training demand.[1][2]

SemiAnalysis's H100 spot/composite index started at ~$6.57–6.62/hr in 2H 2023 (peak scarcity), fell steadily through 2025 lows around $2.79–2.91/hr (e.g., Oct 2025 spot ~$2.84/hr, 1y contracts bottoming near $1.45–2.00/hr), then stabilized or rebounded modestly to ~$2.80–2.92/hr spot and $2.00–2.70/hr for 1y contracts by early-mid 2026 amid sold-out on-demand capacity and token demand growth. Ornn, Silicon Data, and Compute Census medians in late 2026 clustered around $2.96–$3.53/hr (on-demand often $3.49 median, with floors ~$1.30–1.80 on marketplaces like Vast.ai). Hyperscaler list prices remained far higher (e.g., AWS ~$6.88/hr).[3][4]

• Marketplace/neo-cloud offers (Vast.ai, RunPod, Lambda) consistently undercut hyperscalers by 50%+ but show wide dispersion (H100 ranges often 5–18x across providers).[5]
• 1y contract indices (SemiAnalysis) rose ~40% from Oct 2025 lows (~$1.70) to ~$2.35 by Mar 2026.[6]
• Rebound tied to Blackwell supply constraints, power limits on new capacity, and inference/agent workloads favoring proven Hopper silicon.[4]

For new entrants or operators competing on H100 capacity: Secure long-term power and colo deals early; price volatility rewards those who can hold inventory through dips or pivot to spot/reserved mixes. Marketplace operators face thin margins unless utilization exceeds ~60–70% after power/hosting fees.

A100 and older generations (V100) exhibit steeper absolute price decay but retain viability for inference workloads, with A100 medians now ~$1.5–1.75/hr (floors ~$0.40–0.53 on marketplaces) versus V100 at ~$0.12–0.40/hr.[3][7]

CCIR analysis shows rental rates declining ~21% per year of chip age across generations (cross-sectional fit on 2026 data), with V100 (2017-era) recovering MSRP in ~10 months gross but now renting at fractions of newer cards; A100 (2020) crossed net recovery around 39 months and continues earning at ~0.95× MSRP-equivalent by age ~6 years.[8] SemiAnalysis and other indices show A100 softening more than H100 in 2025 corrections (broader secondary-market liquidity) but stabilizing or slightly rising in 2026 on inference demand. V100 prices have remained low and relatively stable for years, suitable only for lighter or legacy workloads.[9]

• Current snapshots (late 2026): A100 on-demand medians ~$1.75 (range $0.53–5.07); V100 ~$0.14–1.60 (floors often <$0.20 on Vast/Verda).[3][10]
• Per-bandwidth pricing narrows the gap: older cards trade at competitive $/TB/s-hr for memory-bound inference despite lower peak FLOPS.[8]
• A100 contracts extend into 2029 at CoreWeave and elsewhere, confirming sustained demand.[11]

Operators hosting older GPUs can still clear positive margins over variable costs if utilization is high and power is cheap (<$0.10–0.15/kWh effective), as power represents only 8–15% of total hosting costs for these lower-TDP cards.[12]

Approximate loaded power (GPU TDP + system/PUE overhead ~1.3–1.5×): H100 ~1.0–1.5 kW effective (~$0.10–0.30/hr at $0.08–0.20/kWh industrial rates); A100 ~0.5–0.7 kW (~$0.05–0.14/hr); V100 ~0.4 kW (~$0.03–0.08/hr). Even at marketplace floors, A100/V100 rentals exceed marginal power costs at >20–40% utilization; H100 requires higher rates or utilization to cover its higher draw.[13][14]

• Hosting economics favor A100/L40S-class cards for high-utilization inference (e.g., batch/background serving) where per-token costs can beat pricier newer GPUs.[15]
• Self-hosted enterprise utilization often lags (many clusters <50%, some as low as 5–25%), eroding margins despite low rental equivalents.[16]

For margin-focused hosts: Prioritize low-power regions and inference-optimized workloads; older chips extend payback periods but require disciplined utilization tracking. Newer chips command premiums that can offset higher power if scarcity persists.

Utilization evidence shows A100 fleets remaining heavily subscribed for inference (including multi-year contracts), while broader market signals indicate tight capacity overall, though self-hosted and spot reliability introduce caveats.[11]

On-demand H100/A100 capacity was frequently sold out across providers in 2026 per SemiAnalysis surveys; A100s serve as the "inference workhorse" with throughput holding steady while prices fell. CoreWeave and others extended A100 rentals through 2029. Marketplace listings (Vast.ai) often show high offer counts for A100s.[16][15]

Limitations: "Fully booked" often refers to committed/reserved capacity or specific providers; spot/interruptible offerings have lower effective utilization and reliability risks. Enterprise-owned fleets report low average utilization (VentureBeat survey: 83% ≤50%). Geography, interconnect (SXM vs PCIe), and workload fit (memory bandwidth) drive real billed hours far below listed availability.[5]

Entrants should differentiate on reliability SLAs, workload-specific optimization (e.g., vLLM tuning for A100 inference), or bundled software rather than raw price; pure commodity hosting faces utilization and power risks.

Overall market structure favors specialized operators who match chip age to workload (H100/H200 for training/frontier, A100/V100 or consumer for cost-sensitive inference) while hedging via diversified providers and term lengths. Price decay is real but slowed or reversed by AI demand growth; positive margins persist well beyond initial expectations for mid-generation cards. Data from indices like SemiAnalysis, Ornn, Silicon Data, and marketplaces (Vast/Lambda) enable precise benchmarking, but actual economics hinge on utilization discipline and power contracts. Additional primary transaction data or provider-specific utilization reports would further refine margin thresholds.

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Recent Findings Supplement (November 2026)

Recent GPU rental price data (post-May 2026, primarily October–November 2026 observations) shows continued high demand driving price increases even for older chips, with executed-trade indices like Ornn revealing premiums for newer architectures and sustained viability for A100/V100 at lower rates.[1][2]

Ornn Compute Price Index (Executed Trades Benchmark)

Ornn’s daily settlements (volume-weighted from neocloud transactions, distinct from listings) as of late October to early November 2026 provide the most direct recent executed-price data:[1][2]

• H100 SXM: $3.00–$3.53/GPU-hour (e.g., $3.00 on Oct 31; $3.53 on Nov 3; up ~25–43% month-over-month in recent prints).
• H200: $5.64–$7.31/GPU-hour (premium over H100 reflecting higher memory/bandwidth).
• B200: $9.41–$9.54/GPU-hour (newer Blackwell commanding the highest rates).
• A100 SXM4: $1.04–$1.08/GPU-hour (up ~7–20% since early 2026 or in recent 1M periods; notable for a 2020-era chip).
• RTX PRO 6000: ~$1.52–$1.54/GPU-hour.

These reflect transacted prices rather than advertised rates. A related X post highlighted Ornn-indexed rises (H100 +~36%, A100 +~7% since Jan 1, 2026), underscoring that older silicon retains or gains value amid demand.[3]

Marketplace and Aggregator Listings (Vast.ai, Lambda, RunPod, etc.)

Live on-demand/community/spot rates from providers and aggregators (as of early November 2026 snapshots) show wide spreads by tier and availability:[4][5][6]

• H100: Marketplace lows ~$1.5–$1.8/GPU-hour (e.g., Vast.ai community or Lium); on-demand/secure often $2.7–$4.2; spot/interruptible as low as ~$1.1–$2.6. Medians across providers ~$3.3–$4.2.
• A100 (40/80GB variants): Cheapest ~$0.27–$0.60/GPU-hour on Vast.ai/marketplaces; broader medians ~$1.0–$1.85; spot lower (e.g., ~$0.5–$1.1).
• V100: Marketplace floors ~$0.05–$0.09/GPU-hour (Vast.ai spot/on-demand); higher listings up to ~$0.5+ depending on config/region.
• Other notes: H200 ~$3.5–$5+; newer Blackwell chips (B200/B300) significantly higher. Aggregators like SiliconTicker, Silicon Lien, CCIR, and GPU Finder report similar ranges with daily/weekly refreshes (e.g., H100 family public-list medians ~$4.18).[7][8]

Prices vary by region, commitment (reserved discounts), and reliability (community vs. secure tiers); spot offers deeper discounts but with interruption risk.

Price Decay by Chip Age and Margin Thresholds

Data illustrates decay with age but with recent upward pressure reversing some prior declines: H100 (2022-era) commands 3x+ the executed rate of A100 (2020), while V100 (2017) rents at 5–20x lower.[1][6]

• Older chips retain positive margins over power/opex in many cases. One hosting analysis (Oct 2026) for A100 80GB at ~$1.43 customer rate and L40S at ~$0.92 notes power costs of ~$0.04–$0.18/GPU-hour; breakeven possible below 20–40% utilization depending on electricity rates and overhead, with higher utilization yielding clear profits after fees.[9]
• V100 at $0.05–$0.09 likely clears power easily on efficient hosts but offers lower absolute margins/revenue.

No comprehensive new “chart” of multi-year decay curves appeared in results, but month-over-month and year-to-date rises (even for A100) indicate demand is sustaining older hardware longer than typical depreciation models predicted.

Utilization Evidence and Limitations

Direct utilization metrics remain limited in public reports. Ornn dashboards reference provider-level figures (e.g., one example at 91% utilization alongside pricing tools).[10] Rising executed prices for A100 (up since Jan 2026) and sustained marketplace availability for V100/A100 imply high demand/utilization for older chips, with A100s described in prior contexts as “fully booked” in high-demand periods.[3]

Limitations: Most data is from listings or indices rather than real-time occupancy; spot/interruptible capacity can mask underlying demand; regional/provider differences exist; no broad new regulatory or policy updates noted in searches. Aggregators like Vast.ai report stock history (e.g., limited or high availability percentages), but these are snapshots.

For competitors or entrants: Newer chips (H100+) offer higher absolute revenue but face premium competition and potential future supply ramps; older A100/V100 provide lower entry barriers and positive (if thinner) margins if power/hosting costs are controlled and utilization stays elevated amid ongoing AI demand. Monitor Ornn settlements and Vast.ai-style marketplaces for real-time signals, as prices have shown volatility and upward trends into late 2026. Data evolves daily; cross-reference multiple aggregators for robustness.