Cost Bridge Chart (2026) — Side-by-Side AI Chip Cost Comparison
As of February 2026, compare manufacturing costs of 13 AI accelerators side by side. Select any two chips from Nvidia H100 (~$3,320 BOM), H200 (~$4,800), B200 (~$6,400), GB200 (~$13,200), AMD MI300X (~$5,300), MI355X, Intel Gaudi 3, Google TPU v5p, AWS Trainium 2, Microsoft Maia 100, and Meta MTIA v2. Visualize cost component deltas across logic die, HBM memory, advanced packaging (CoWoS, SoIC), and assembly. Analyze gross margin differences and cost-per-TFLOP efficiency ratios.
Cost Bridge Chart
Compare manufacturing costs of AI accelerators side by side. Select two chips to visualize how cost components differ and identify the key drivers of the cost delta.
AMD MI300X costs +$2.0K (+59.6%) more to manufacture than NVIDIA H100 SXM5
Cost per FP8 TFLOP: NVIDIA H100 SXM5 = $0.84 · AMD MI300X = $1.01
Gross margin: NVIDIA H100 SXM5 = 88.1% ($24.7K) · AMD MI300X = 64.7% ($9.7K)
Cost + Margin to Sell Price
Mfg cost stacked with gross margin = sell price. Chips not commercially sold show cost only.
Cost Bridge (Waterfall)
Component Cost Breakdown
| Component | NVIDIA H100 SXM5 | AMD MI300X | Delta | % Change |
|---|---|---|---|---|
| Logic Die | $300 | $600 | +$300 | +100.0% |
| HBM Memory | $1.4K | $2.9K | +$1.6K | +114.8% |
| Packaging | $750 | $1.2K | +$450 | +60.0% |
| Test & Assembly | $920 | $600 | $-320 | -34.8% |
| Total Manufacturing Cost | $3.3K | $5.3K | +$2.0K | +59.6% |
| Pricing & Margin | ||||
| Sell Price | $28.0K | $15.0K | ||
| Gross Margin | $24.7K (88.1%) | $9.7K (64.7%) | ||
Specifications Comparison
| Specification | NVIDIA H100 SXM5 | AMD MI300X |
|---|---|---|
| Vendor | NVIDIA | AMD |
| Process Node | TSMC 4N | N5/N6 chiplet |
| Die Size | 814 mm² | 1725 mm² |
| Memory | 80 GB HBM3 | 192 GB HBM3 |
| Memory BW | 3.35 TB/s | 5.3 TB/s |
| FP8 TFLOPS (sparse) | 3,958 | 5,230 |
| BF16 TFLOPS (dense) | 989 | 1,307 |
| Package | CoWoS-S | CoWoS-S + SoIC |
| Interconnect | NVLink 4 | Infinity Fabric |
| Est. Sell Price | $28.0K | $15.0K |
| Gross Margin | 88.1% | 64.7% |
Data Sources & Methodology
Manufacturing cost estimates derived from Epoch AI Monte Carlo models, Raymond James semiconductor research, TrendForce quarterly reports, and SemiAnalysis teardown data. Cost components include wafer fabrication (logic die), HBM memory stacks, advanced packaging (CoWoS, SoIC), and test/assembly. Estimates are directional and may vary ±15-20% from actual costs.
Cloud-only chips (TPU, Trainium, Maia, MTIA) show $0 sell price as they are not commercially sold. Gross margin is not applicable for internal/cloud-only products.
Related Analysis
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NVIDIA GPU Prices Double as AI Demand Overwhelms Supply
Pricing context for cost bridge data: RTX 5090 doubles and data center spillover effects.
Microsoft Maia 200: A Plan to Cut Billions in NVIDIA Spending
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NVIDIA AI Accelerator Market Share 2024-2026
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Manufacturing Cost Breakdown for AI Chips
Every AI accelerator's manufacturing cost can be decomposed into four major layers: logic die fabrication, HBM memory, advanced packaging, and assembly/test. This AI chip cost breakdown comparison reveals how design decisions, supplier relationships, and technology choices drive dramatically different cost structures across competing chips.
The Four Cost Layers
The logic die cost depends on process node, die area, and wafer yield. A large monolithic die on TSMC 4N (like the H100) costs $250–350 in wafer cost alone, while a chiplet approach (like MI300X with its multi-die design) can improve yield at the expense of more complex packaging. HBM memory has become the dominant cost component for many AI chips—6–8 stacks of HBM3E can add $700–$1,500 to the GPU manufacturing cost. Packaging (CoWoS, EMIB, or organic substrate) adds $500–$1,500+, and test/assembly adds $100–$500.
Memory as the Dominant Cost Driver
For the latest generation of AI accelerators, HBM memory often represents 40–50% of total manufacturing cost. This is a structural shift from earlier GPU generations where the logic die was the primary cost center. The chip BOM analysis in this tool shows this clearly: compare the H100 (5 HBM3 stacks) against the B200 (8 HBM3E stacks) and you can see how memory cost scales with capacity and generation.
Comparing Design Strategies Through Cost Bridges
Cost bridge charts are powerful because they reveal strategic differences between vendors. NVIDIA's approach prioritizes maximum performance with premium packaging (CoWoS-L for B200). AMD's MI300X uses a multi-die chiplet design that trades packaging complexity for better logic die yields. Google's TPU v5p optimizes for internal workloads with a more balanced cost profile. By comparing these bridges side by side, procurement teams can understand what they're paying for and where negotiation leverage exists.
Related: Chip Price Calculator · Packaging Cost Model · Price/Performance Frontier
Custom Chip Comparison
Add your own chip to the cost bridge and benchmark against industry leaders.
AI Accelerator Manufacturing Cost Reference
Estimated manufacturing costs for 16 AI accelerators. Select any two chips in the interactive tool above to see a detailed cost bridge comparison. Data as of February 2026.
| Chip | Vendor | Process | Die (mm²) | Memory | Package | Logic Cost | HBM Cost | Pkg Cost | Total COGS | Sell Price | Margin |
|---|---|---|---|---|---|---|---|---|---|---|---|
| AMD Instinct MI355X | AMD | N3P/N6 chiplet | 2,100 | HBM3e 288GB | CoWoS-S + SoIC | $750 | $4,350 | $1,400 | $8,000 | $25,000 | 68% |
| AMD Instinct MI300X | AMD | N5/N6 chiplet | 1,725 | HBM3 192GB | CoWoS-S + SoIC | $600 | $2,900 | $1,200 | $5,300 | $15,000 | 64.7% |
| AMD Instinct MI325X | AMD | N5/N6 chiplet | 1,725 | HBM3e 256GB | CoWoS-S + SoIC | $600 | $2,200 | $500 | $3,800 | $20,000 | 81% |
| AWS Trainium 2 | AWS | TSMC 5nm | — | HBM3 96GB | CoWoS SiP | $1,200 | $1,440 | $800 | $5,000 | Internal | — |
| Google TPU v5p | TSMC 5nm | — | HBM3 95GB | Custom ASIC | $2,000 | $950 | $500 | $4,500 | Internal | — | |
| Groq LPU | Groq | Samsung 14nm | — | Custom SRAM 80GB | Custom | $1,500 | $0 | $500 | $3,500 | $20,000 | 82.5% |
| Intel Gaudi 3 | Intel | TSMC 5nm | — | HBM2e 128GB | OAM | $1,500 | $1,950 | $1,200 | $6,500 | $15,625 | 58.4% |
| Intel Gaudi 2 | Intel | TSMC 7nm | — | HBM2e 96GB | OAM | $700 | $960 | $500 | $2,500 | $12,000 | 79.2% |
| Meta MTIA v2 | Meta | TSMC 5nm | 421 | LPDDR5 + SRAM 128GB | Standard (no HBM) | $1,200 | $0 | $300 | $2,500 | Internal | — |
| Microsoft Maia 100 | Microsoft | TSMC 5nm | 820 | HBM2e 64GB | CoWoS-S | $2,000 | $960 | $1,000 | $7,500 | Internal | — |
| Nvidia GB200 | NVIDIA | TSMC 4NP | 3,200 | HBM3e 384GB | Custom Superchip | $1,700 | $5,800 | $2,200 | $13,500 | $65,000 | 79.2% |
| Nvidia Blackwell B100 | NVIDIA | TSMC 4NP | 1,600 | HBM3e 192GB | CoWoS-L | $850 | $2,900 | $1,100 | $6,500 | $32,000 | 79.7% |
| Nvidia Blackwell B200 | NVIDIA | TSMC 4NP | 1,600 | HBM3e 192GB | CoWoS-L | $850 | $2,900 | $1,100 | $6,400 | $40,000 | 84% |
| Nvidia H200 | NVIDIA | TSMC 4N | 814 | HBM3e 141GB | CoWoS-S | $300 | $1,500 | $750 | $4,250 | $38,000 | 88.8% |
| Nvidia H100 (SXM) | NVIDIA | TSMC 4N | 814 | HBM3 80GB | CoWoS-S | $300 | $1,350 | $750 | $3,320 | $28,000 | 88.1% |
| Nvidia H100 PCIe | NVIDIA | TSMC 4N | 814 | HBM2e 80GB | CoWoS-S | $300 | $1,200 | $650 | $2,750 | $27,500 | 90% |
AI Chip Cost Comparison FAQ
- How much does it cost to manufacture an NVIDIA H100 GPU?
- The estimated manufacturing cost of an NVIDIA H100 SXM5 is approximately $3,320, including the logic die (~$300 on TSMC 4N), HBM3 memory (~$1,350), CoWoS-S packaging (~$750), and test & assembly (~$920). NVIDIA sells the H100 at roughly $28,000, implying a gross margin of approximately 88%.
- What is a cost bridge chart for semiconductors?
- A cost bridge (or waterfall) chart visualizes the manufacturing cost breakdown of a chip into its components: logic die cost, HBM memory, advanced packaging (CoWoS, EMIB), substrate and assembly, and test. Comparing two chips side by side reveals where cost differences originate—whether from larger dies, more HBM stacks, or costlier packaging.
- Why is the NVIDIA B200 more expensive to manufacture than the H100?
- The B200 costs more due to its dual-die Blackwell architecture (two large dies vs one), 8 stacks of 12-high HBM3E (vs 6 stacks of 8-high HBM3), and the move to CoWoS-L packaging for the larger interposer. These changes roughly double the HBM cost and increase packaging cost by 30–50% compared to the H100.
- What are the cost components of a semiconductor chip?
- Semiconductor chip manufacturing cost breaks down into four main components: (1) Logic die cost — determined by wafer price, die area, and yield (typically 30–50% of total for AI chips); (2) HBM memory — $200–$500 per stack, 6–8 stacks per AI accelerator (30–45% of total); (3) Advanced packaging — CoWoS-S $300–$800, CoWoS-L $800–$2,000 (10–20% of total); (4) Assembly, test, and substrate (5–10% of total). Use our cost bridge tool to see exact breakdowns for 13 chips.
- How do AMD MI300X manufacturing costs compare to NVIDIA H100?
- The AMD MI300X has an estimated manufacturing cost of approximately $5,300, higher than the H100's ~$3,300. The MI300X uses a multi-chiplet design with N5 and N6 dies on a large interposer with 8 HBM3 stacks (192GB). However, AMD prices the MI300X at ~$15,000 vs NVIDIA's ~$25,000–30,000 for the H100, resulting in lower margins (~65% vs ~88%) but a more competitive acquisition cost for customers.
- Which AI chip has the highest gross margin?
- NVIDIA's H100 has the highest estimated gross margin at approximately 88% ($3,300 manufacturing cost vs ~$28,000 sell price). The B200 follows at ~84% ($6,400 vs ~$40,000). Intel Gaudi chips achieve ~82–83% margins. AMD MI300X has the lowest among major AI accelerators at ~65% ($5,300 vs ~$15,000), reflecting AMD's aggressive pricing strategy to gain market share.
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- NVIDIA GPU Price Analysis — Manufacturing costs and supply chain economics
- NVIDIA AI Accelerator Market Share 2024–2026 — Competitive breakdown vs AMD, Google, Intel
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