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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.

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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)

Total Cost increase Cost decrease

Component Cost Breakdown

ComponentNVIDIA H100 SXM5AMD MI300XDelta% 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

SpecificationNVIDIA H100 SXM5AMD MI300X
VendorNVIDIAAMD
Process NodeTSMC 4NN5/N6 chiplet
Die Size814 mm²1725 mm²
Memory80 GB HBM3192 GB HBM3
Memory BW3.35 TB/s5.3 TB/s
FP8 TFLOPS (sparse)3,9585,230
BF16 TFLOPS (dense)9891,307
PackageCoWoS-SCoWoS-S + SoIC
InterconnectNVLink 4Infinity Fabric
Est. Sell Price$28.0K$15.0K
Gross Margin88.1%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.

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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.

ChipVendorProcessDie (mm²)MemoryPackageLogic CostHBM CostPkg CostTotal COGSSell PriceMargin
AMD Instinct MI355XAMDN3P/N6 chiplet2,100HBM3e 288GBCoWoS-S + SoIC$750$4,350$1,400$8,000$25,00068%
AMD Instinct MI300XAMDN5/N6 chiplet1,725HBM3 192GBCoWoS-S + SoIC$600$2,900$1,200$5,300$15,00064.7%
AMD Instinct MI325XAMDN5/N6 chiplet1,725HBM3e 256GBCoWoS-S + SoIC$600$2,200$500$3,800$20,00081%
AWS Trainium 2AWSTSMC 5nmHBM3 96GBCoWoS SiP$1,200$1,440$800$5,000Internal
Google TPU v5pGoogleTSMC 5nmHBM3 95GBCustom ASIC$2,000$950$500$4,500Internal
Groq LPUGroqSamsung 14nmCustom SRAM 80GBCustom$1,500$0$500$3,500$20,00082.5%
Intel Gaudi 3IntelTSMC 5nmHBM2e 128GBOAM$1,500$1,950$1,200$6,500$15,62558.4%
Intel Gaudi 2IntelTSMC 7nmHBM2e 96GBOAM$700$960$500$2,500$12,00079.2%
Meta MTIA v2MetaTSMC 5nm421LPDDR5 + SRAM 128GBStandard (no HBM)$1,200$0$300$2,500Internal
Microsoft Maia 100MicrosoftTSMC 5nm820HBM2e 64GBCoWoS-S$2,000$960$1,000$7,500Internal
Nvidia GB200NVIDIATSMC 4NP3,200HBM3e 384GBCustom Superchip$1,700$5,800$2,200$13,500$65,00079.2%
Nvidia Blackwell B100NVIDIATSMC 4NP1,600HBM3e 192GBCoWoS-L$850$2,900$1,100$6,500$32,00079.7%
Nvidia Blackwell B200NVIDIATSMC 4NP1,600HBM3e 192GBCoWoS-L$850$2,900$1,100$6,400$40,00084%
Nvidia H200NVIDIATSMC 4N814HBM3e 141GBCoWoS-S$300$1,500$750$4,250$38,00088.8%
Nvidia H100 (SXM)NVIDIATSMC 4N814HBM3 80GBCoWoS-S$300$1,350$750$3,320$28,00088.1%
Nvidia H100 PCIeNVIDIATSMC 4N814HBM2e 80GBCoWoS-S$300$1,200$650$2,750$27,50090%

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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