The open platform for semiconductor cost intelligence
Free tools to model chip manufacturing costs, calculate GDPW & die yield, and analyze wafer pricing across 13 AI accelerators and 100+ global fabs. Cost breakdowns, market data, and 30+ analysis reports — open and free.
Analysis & Modeling Tools
From wafer-level cost modeling to global supply chain mapping — everything in one platform.
Chip Price Calculator
Wafer cost, yield modeling, packaging economics, and margin analysis across process nodes from 180nm to 2nm.
Packaging Model
Compare CoWoS-S, CoWoS-L, EMIB, SoIC, and flip-chip architectures with HBM stack cost analysis.
Fab Explorer
Explore 100+ semiconductor fabs from TSMC, Samsung, Intel, SMIC, and Rapidus. Filter by node, country, and capacity.
Price / Performance Frontier
Compare AI accelerators on cost, throughput, training time, and TCO — H100, B200, MI300X, TPU v5p, and more.
HBM Market Analysis
HBM market dynamics — accelerator specs, vendor market share, spot pricing, supply chain signals, and revenue forecasts.
Cost Bridge Chart
Side-by-side manufacturing cost comparison across logic die, HBM memory, packaging, and assembly for 13 AI accelerators.
Supply Chain Explorer
Interactive sunburst visualization of semiconductor supply chain chokepoints — from ASML to Zeiss optics to Japanese photoresist monopolies.
Developer API
Structured semiconductor data for AI agents and applications — accelerator costs, HBM market data, and 30+ articles. Free, no key required.
Semiconductor Cost Modeling Platform
Chip Cost Calculator
Model chip manufacturing costs across process nodes from 28nm to 2nm. Calculate GDPW, net die yield, wafer costs, CoWoS packaging, HBM memory pricing, and total chip cost with interactive parameter adjustments. Free alternative to paid die calculators.
Supply Chain Intelligence
Explore 100+ semiconductor fabs worldwide with capacity data, track HBM market dynamics with live spot pricing and vendor market share, and visualize supply chain chokepoints from ASML lithography to Japanese photoresist monopolies.
Market Analysis
30+ deep-dive reports covering TSMC wafer pricing, NVIDIA GPU economics, HBM memory shortages, export controls, and AI chip demand trends. Data-driven analysis with interactive cost models and structured data via our free API.
Built for semiconductor professionals
Latest Analysis
Deep-dive reports on semiconductor technology, supply chains, and market dynamics
NVIDIA AI Accelerator Market Share 2024–2026: Data, Trends & Competitive Analysis
NVIDIA holds 70-95% of the AI accelerator market by revenue. Detailed market share data from 2022-2026, competitive breakdown vs AMD MI300X/MI355X, Google TPU, Intel Gaudi, and custom silicon from AWS, Microsoft, and Meta.
NVIDIA commands approximately 80-90% of the AI accelerator market by revenue as of 2025, generating over $100 billion annually from data center GPUs. While percentage share will decline to ~75% by 2026 as AMD and custom silicon scale, NVIDIA's absolute revenue continues to grow because the total addressable market is expanding faster than any single competitor can capture. The structural moat — CUDA's 4M+ developer ecosystem, full-stack platform integration, and priority TSMC CoWoS allocation — ensures dominance for the foreseeable future.
Nvidia Tech Linked to China's Military AI, Igniting US Security Alarms
Deep-dive analysis into the national security implications of Nvidia's alleged assistance to DeepSeek, whose AI models were later used by China's military, and the strategic fallout for the semiconductor supply chain.
The Nvidia-DeepSeek incident reveals that algorithmic efficiency can be a powerful countermeasure to hardware-based export controls, shifting the geopolitical battlefield from silicon access to intellectual property and optimization expertise. This necessitates a fundamental rethink of technology containment strategies, as China demonstrates the ability to achieve state-of-the-art AI performance even with restricted or less powerful hardware, posing a direct challenge to U.S. technological supremacy.
Microsoft's Maia 200: A Plan to Cut Billions in NVIDIA Spending
Deep dive into Microsoft's Maia 200 AI chip, analyzing its impact on NVIDIA, TSMC, and the AI hardware supply chain, including wafer economics and TCO analysis.
Microsoft's custom silicon strategy with Maia 200 is less about competing with NVIDIA on peak performance and more about achieving a dramatically lower Total Cost of Ownership (TCO) for its high-volume, internal AI inference workloads. While this reduces direct GPU purchases, it intensifies the battle for TSMC's limited 3nm and advanced packaging capacity, potentially creating new, more complex supply chain bottlenecks for the entire industry.
NAND Prices Surge 40%+ as AI Demand Triggers SSD Shortage
NAND flash prices up 40%+ as AI training demand absorbs capacity. Impact on SSD pricing, supply forecasts, and procurement timelines. Data-driven market analysis.
The AI boom is creating a 'gravity well' for semiconductor manufacturing capacity, pulling resources away from consumer markets and towards high-margin data center components. This strategic reallocation by major memory makers like Samsung, SK Hynix, and Micron is not a temporary blip but a structural market shift, leading to a projected price surge of over 40% for client SSDs in Q1 2026. Enterprises and PC OEMs must immediately reassess procurement strategies to mitigate significant cost increases and potential shortages.
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Why Silicon Analysts
Industry-Standard Models
Built on semiconductor cost models used by leading companies. Wafer pricing, yield curves, and packaging economics from publicly available data.
Real-Time Market Data
Live ticker, HBM spot prices, and fab capacity tracking. Stay ahead of supply chain shifts with structured, programmatic data access.
Open & Transparent
Free tools, public API, documented data sources. No black boxes — every estimate links to methodology and cited research.
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