AI Accelerator Manufacturing Cost Estimates (2026)

As of August 2026, manufacturing costs for leading AI accelerators range from ~$3,320 for the NVIDIA H100 to ~$14,200 for the GB200 superchip. HBM memory and advanced packaging account for over 60% of total BOM cost on every NVIDIA and AMD part below.

Last updated: · Data sources: Epoch AI, Raymond James, TrendForce, SemiAnalysis · JSON API ·

Manufacturing Cost Comparison

Estimated bill-of-materials (BOM) manufacturing costs for 8 leading AI accelerators. All figures are per-unit estimates excluding non-recurring engineering (NRE) costs.

Manufacturing cost breakdown by accelerator

Logic die + HBM memory + advanced packaging. HBM + packaging dominate BOM on the newest parts.

ChipVendorProcessDie SizeLogic CostHBM CostPackagingTotal Mfg CostSell PriceMargin
H100 SXM5NVIDIATSMC 4N814mm²$300$1,350$750$3,320$27,00088%
H200 SXM5NVIDIATSMC 4N814mm²$300$2,400$750$5,150$38,00086%
B200NVIDIATSMC 4NP2×800mm²$850$3,250$1,100$6,750$40,00083%
GB200NVIDIATSMC 4NPGrace+2×B200$1,700$6,500$2,200$14,200$65,00078%
MI300XAMDTSMC N5/N61,725mm² (chiplet)$600$2,900$1,200$5,300$15,00065%
MI325XAMDTSMC N5/N61,725mm² (chiplet)$600$4,350$1,300$6,750$20,00066%
Gaudi2IntelTSMC 7nm$700$960$500$2,500$12,00079%
Gaudi3IntelTSMC 5nm$1,500$1,950$1,200$6,500$15,62558%

All costs are estimates based on industry consensus data. Actual costs vary by volume, contract terms, yield, and market conditions.

H100 SXM5 est. mfg cost & sell price — daily ledger

Daily ledger; history began 2026-06-06 (per-domain start may be later). Append-only — cannot be backfilled.

H100 SXM secondary-market price — residual value tracker

Median used-market price per GPU across independent public sources (sold-listing roundups, broker pages, trade press). The ledger also records the low/high band and a derived residual value (median ÷ launch price) — weekly, measured, not assumed.

Cost Structure Analysis

1. HBM memory is now the dominant cost component

Across the chips in the table, HBM memory represents 30-64% of total manufacturing cost. For the GB200 superchip, HBM alone costs $6,500 per unit -- roughly double the entire manufacturing cost of an H100. The August 2026 re-base of actively-procured parts to ~$17/GB HBM3e contract pricing amplified this further, and current flagships carry 8 or more stacks each.

2. Advanced packaging adds $300-$2,000 per chip

CoWoS-S and CoWoS-L interposer packaging is the third-largest cost element after HBM and logic dies. Multi-die designs like the B200 (two Blackwell dies on a single CoWoS-L substrate) and GB200 (Grace CPU + two B200 GPUs) push packaging costs to $1,000-$2,000 per unit. TSMC CoWoS capacity remains supply-constrained with 40-52 week lead times.

3. NVIDIA maintains significantly higher margins than AMD

NVIDIA chips command 78-88% gross margins compared to AMD's 65-66%. This margin gap reflects NVIDIA's CUDA software ecosystem lock-in, stronger enterprise demand, and first-mover advantage in data center AI. Intel's Gaudi line spans 58-79% at lower absolute price points, targeting a different market segment.

Methodology & Data Sources

Cost estimates on this page are derived from multiple independent sources and cross-validated where possible:

  • Epoch AI -- Monte Carlo cost models for semiconductor manufacturing, covering wafer cost, yield, and packaging economics
  • Raymond James -- Semiconductor equity research with bottom-up BOM cost analysis for NVIDIA and AMD accelerators
  • TrendForce -- Quarterly foundry pricing reports and HBM supply/demand tracking
  • SemiAnalysis -- Teardown analysis and cost modeling for AI accelerator products

Estimates are directional and may vary +/-15-20% from actual manufacturing costs. Logic die costs are calculated from wafer price, die area, and estimated yield. HBM costs ride the labeled contract basis in effect for each part's vintage. Packaging costs include interposer, substrate, and assembly. For full terms see Terms & Data Provenance.

Related Tools

Use our interactive tools to model custom chip cost scenarios and compare accelerators:

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