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AI Accelerator Manufacturing Cost Estimates (2026)

As of February 2026, manufacturing costs for leading AI accelerators range from ~$3,320 for the NVIDIA H100 to ~$13,000+ for the GB200 superchip. HBM memory and advanced packaging now account for 60-70% of total BOM cost.

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.

ChipVendorProcessDie SizeLogic CostHBM CostPackagingTotal Mfg CostSell PriceMargin
H100 SXM5NVIDIATSMC 4N814mm²$300$1,350$750$3,320$28,00088%
H200 SXM5NVIDIATSMC 4N814mm²$300$2,100$800$4,800$38,00087%
B200NVIDIATSMC 4NP2×800mm²$600$2,400$1,000$6,400$40,00084%
GB200NVIDIATSMC 4NPGrace+2×B200$1,200$4,800$2,000$13,200$65,00080%
MI300XAMDTSMC N5/N61,725mm² (chiplet)$1,500$1,600$1,200$5,300$15,00065%
MI325XAMDTSMC N5/N61,725mm² (chiplet)$1,500$2,400$1,200$6,100$20,00070%
Gaudi2IntelTSMC 7nm$200$960$300$2,060$12,00083%
Gaudi3IntelTSMC 5nm$250$1,500$400$2,800$15,60082%

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

Cost Structure Analysis

1. HBM memory is now the dominant cost component

Across all chips in the table, HBM memory represents 35-47% of total manufacturing cost. For the GB200 superchip, HBM alone costs $4,800 per unit -- more than the entire manufacturing cost of an H100. The shift from HBM3 ($200/stack) to HBM3E ($300/stack) further amplifies this trend, with next-generation chips requiring 8-12 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 80-88% gross margins compared to AMD's 65-70%. 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 achieves 82-83% margins 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 use per-stack pricing multiplied by stack count. 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: