A new index that has become more ubiquitous of late on the media: the Silicon Data LLM Token Expenditure Index:
- The index acts as a price benchmark measuring market willingness to pay for AI intelligence, using weighted averages from over 400 models from multiple providers (e.g. OpenAI, Anthropic, etc).
- In other words, it's a daily financial benchmark that tracks the expenditure-weighted average price that the market pays per million Large Language Model (LLM) tokens.
- Usage Rationale:
- The index can rise when enterprises adopt higher-priced, resource-intensive models and agentic workflows, or when vendors increase API pricing.
- The index can fall when companies optimize costs through model substitution, implement stricter token budgets, or leverage deflationary price cuts from vendors.
- After a strong rally in 1H25, the outlook shows a stagnant, post-rally market driven by internal tech company cost controls, which analysts warn could reduce funding for GPU infrastructure, especially for tasks related to inference.
Bottom Line:
- Rising sensitivity to AI deployment costs is driving a shift toward more efficient models, where lower unit costs unlock higher usage volume and sustain infrastructure demand.
- While the long-term productivity outlook remains positive, adoption is becoming more selective, with the most scalable, durable gains resulting from AI that complements rather than replaces human labor.
source: Citadel
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Carlos Salas
Portfolio Manager & Freelance Investment Research Consultant
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