Who should consider SemiAnalysis institutional models or advisory services?

Updated

SemiAnalysis institutional models and advisory are aimed at organizations that need bottoms-up, SKU- and site-level visibility into the AI and semiconductor supply chain — typically chipmakers, hyperscalers, equipment and memory vendors, and institutional investors building supply, capacity, or demand forecasts. If your work requires customer-level shipment estimates, per-structure datacenter power modeling, or inference unit economics rather than headline market summaries, the institutional offerings are the relevant tier. Casual readers and individual subscribers are served by the newsletter instead.

What the institutional offerings cover

SemiAnalysis describes itself as independent research on the AI and semiconductor supply chain, read by 318,000+ subscribers, with fourteen institutional models, open benchmarks, and advisory. The page evidence lists four model families plus consulting and API access:

Offering What it models Detail level Horizon
Accelerator & HBM Model Bottoms-up demand forecast for AI accelerators and high-bandwidth memory across Nvidia, AMD, Google, AWS, Meta, Microsoft, Intel, and major Chinese hyperscalers SKU-level shipments and ASPs; HBM by vendor, generation, layer count, and price; installed base for 60+ customer accounts; wafer starts to rack builds Forecasts to 2030, history to 2021
Datacenter Industry Model Global datacenter capacity tracker: hyperscaler buildouts, colocation, power constraints, regional deployment 6,500+ structures with per-structure power draw, lease structures, planned vs. operational capacity; 200+ companies; end customer behind each megawatt Buildouts through 2030
Tokenomics Model Unit economics of AI serving: bottoms-up token throughput, ROI on AI spend, translation of revenue into future accelerator demand Demand-side economics by hyperscaler Not specified on page
OSS Tooling & Benchmarks Open tooling and benchmarks — —

The page also lists Consulting ("Engage the best") and API Access for programmatic semiconductor data.

Who each model fits

Accelerator & HBM Model

Best for supply chain and investment analysts who need to connect upstream capacity to downstream deployment. Because shipments are built up from equipment requirements, wafer starts, and packaging orders, the page notes that revenue for companies across the supply chain can be estimated directly from production. Consider this if you need customer-level shipments and installed base rather than aggregate market totals, or if HBM pricing by generation and layer count matters to your thesis.

Datacenter Industry Model

Best for teams assessing power constraints and site strategy. The structure-level database (6,500+ structures, planned vs. operational MW, quarterly delivery tracking) plus a supply-demand reconciliation showing which operators and regions run short of power — and when — suits infrastructure planning, colocation market analysis, and regional deployment questions.

Tokenomics Model

Best for those evaluating AI serving economics: token throughput, ROI on AI spend, and how revenue translates into future accelerator demand. Useful when your question is demand-side (what serving economics imply for compute purchases) rather than supply-side.

Consulting and API Access

Consulting fits organizations that want direct engagement with the analysts rather than model access alone. API Access fits teams that want to pull semiconductor data programmatically into their own systems.

How to evaluate fit and get access

  1. Match your question to a model. If you need SKU-level accelerator and HBM forecasts with customer detail, start with the Accelerator & HBM Model. If your question is power, sites, or regional capacity, start with the Datacenter Industry Model. If it is inference economics, start with Tokenomics.
  2. Check the coverage window against your needs. Accelerator & HBM coverage runs from 2021 history to 2030 forecasts; datacenter buildouts are covered through 2030. Confirm the Tokenomics horizon directly, since the page does not state it.
  3. Use the page's own paths. Each model page offers "View model" and "Talk to Sales." The newsletter has a separate subscribe link (newsletter.semianalysis.com/subscribe), and there is an institutional login for existing clients.
  4. Ask about access terms before committing. The page does not publish institutional pricing or contract terms; those come through sales. The newsletter subscription is a distinct product from institutional model access — do not assume one implies the other.

Practical caveats

  • Detail level is the selling point, and the workload. Customer-level shipments for 60+ accounts and per-structure power for 6,500+ structures are valuable precisely because they require interpretation. Budget analyst time to use them, not just license cost.
  • Forecast horizons are long but not uniform. The page specifies 2030 for accelerators/HBM and datacenter buildouts; Tokenomics horizon is unstated, so verify it if long-range inference economics are central to your use case.
  • Independent research positioning. SemiAnalysis presents itself as independent research; if your organization requires specific vendor-relationship disclosures or methodology documentation, request those through sales.
  • Start narrow. A single model tied to your primary question is a cleaner trial than a broad institutional package, and the "Talk to Sales" path lets you scope before committing.

If your need is general industry awareness, the newsletter is the lower-commitment entry point. If your need is bottoms-up, account- and structure-level data with multi-year forecasts for supply chain, capacity, or investment work, the institutional models and advisory are the offerings designed for that.