AI Model Token Economics
Know What Your AI Product Actually Costs to Run
Inference costs compound with every user you add, and most teams find out too late. We model token usage and cost by provider, forecast spend against growth, and find where model choice or prompt efficiency cuts cost, using the same rigor we apply to on-chain tokenomics.
AI model token economics applies economic modelling to a different kind of token: the tokens your AI product consumes on every inference call. Blockphrase forecasts inference cost against usage growth, builds unit economics per user or feature, and identifies where model selection or prompt efficiency reduces spend: the same rigor we apply to on-chain tokenomics, applied to LLM cost management.
AI Model Token Economics
What’s Included
Token usage and cost modelling across providers
Inference cost forecasting
Cost optimization strategy
Unit economics analysis
Ongoing token spend monitoring framework
Tokenomics
Other Tokenomics Services
- Tokenomics AuditFind What Breaks Before the Market DoesFind What Breaks Before the Market Does
- Tokenomics Design & ModellingBuilt for the Market a Year From Now, Not Launch DayBuilt for the Market a Year From Now, Not Launch Day
- Tokenomics SimulationsKnow How It Breaks Before the Market Tells YouKnow How It Breaks Before the Market Tells You
Common questions
What people ask before they call.
The economics of the tokens an AI product consumes on every inference call. Blockphrase models token usage and cost by provider, forecasts spend against growth, and finds where model choice or prompt efficiency cuts cost.
No. It applies to the tokens an LLM-based product consumes and pays for. The discipline is the same as on-chain tokenomics: model the flows, forecast them against growth, and optimize.
Token usage and cost modelling across providers, inference cost forecasting, a cost optimization strategy, unit economics analysis, and an ongoing token spend monitoring framework.
Let’s See If We’re the Right Fit
We take on a limited number of engagements at a time to keep advisory quality high. A short scoping call tells us both, quickly, whether this is a fit.