The economics of LLM operations every business leader should know

Market dynamics overview: The enterprise AI market is experiencing a dramatic decrease in the cost of LLM operations, measured in tokens (the basic units of text that AI models process).

• The cost of LLM performance is declining approximately 10x annually, making advanced AI capabilities increasingly accessible to businesses
• This price reduction is driven by smaller models, open-source developments, and improved optimization techniques
• Companies like OpenAI, Meta, Google, and Anthropic are competing to deliver better performance at lower costs

Technical benchmarks and measurements: Performance evaluation relies on standardized testing methods to assess LLM capabilities across various domains.

• The MMLU (Measuring Massive Multitask Language Understanding) score tests LLM performance across humanities, social sciences, and other disciplines
• GPT-3 achieved an MMLU score of 42, with initial costs around $60 per million tokens
• From early to mid-2023, token costs decreased approximately 90%, demonstrating rapid price efficiency improvements

Fundamental market principles: Three key laws help explain the technological advancement driving these changes.

• Moore’s Law predicts the doubling of transistor density on circuits, enabling continued hardware improvements
• Dennard scaling describes how transistor miniaturization maintains power efficiency while improving performance
• Edholm’s Law addresses telecommunications advancement rates across wireless, roaming, and cable networks

Emerging terminology: New market dynamics are creating novel industry terminology that requires clear definition.

• “LLMflation” refers to the declining cost of inference in AI models
• Unlike traditional inflation which describes rising prices, LLMflation represents decreasing costs
• This terminology reflects the unique economic patterns emerging in the AI industry

Market maturity and future implications: The rapid evolution of LLM economics presents both opportunities and uncertainties for enterprise adoption.

• The dramatic cost reductions are enabling new enterprise use cases and applications
• Pricing models remain in early stages, with market dynamics still developing
• Industry experts acknowledge significant uncertainty about future market trends and developments

Looking ahead: While the current trajectory suggests continued price efficiency improvements, the nascent state of LLM markets means that long-term patterns and stabilization points remain unclear, particularly as new technologies and competitive forces emerge.