LLM Economics
Token math, model selection, and the true unit cost of every generation.
Page 6 of 8
LLM EconomicsThe Inference Inflection: Why AI Margins Now Live in Tokens, Not Training
In short: the cost and margin of an AI product have moved from one-time training to per-request inference, so your unit economics now rise and fall with token costs.
LLM EconomicsClaude Sonnet 5 Pricing: What $2/$10 per Million Tokens Means for Your Margins
Claude Sonnet 5 launches at $2 per million input tokens and $10 per million output tokens (introductory, through August 31, 2026), then $3/$15 - but a new tokenizer means your real cost depends on tokens per task, not the sticker rate.
LLM EconomicsThe Economy of Tokens: Why Faster Inference Doesn't Always Cut Your AI Bill
Faster inference frameworks like DeepSeek's DSpark speed up output by 60 to 85%, but if you call a hosted API you pay per token, not per second, so your bill only drops when you control the serving stack or cut the tokens themselves.
LLM EconomicsClaude Sonnet 5 Pricing: What the Cheaper Agent Model Really Costs
Claude Sonnet 5 launches at $2 per million input tokens and $10 per million output tokens (introductory pricing through August 31, 2026), less than half the price of Opus 4.8, but a new tokenizer and a scheduled rate increase mean your real cost depends on the workload you run.
LLM EconomicsAnthropic's California Claude Discount: What a 50% Price Cut Really Does to Your LLM Costs
A 50% discount on Claude does not just halve your bill: it changes your effective cost per token, your gross margin, and the breakeven math on every AI feature you ship.
LLM EconomicsGPT-5.6 Pricing: What Sol, Terra, and Luna Cost per Token
OpenAI's GPT-5.6 family arrives in three priced tiers, Sol at $5/$30, Terra at $2.50/$15, and Luna at $1/$6 per 1M input/output tokens, which means your model pick now moves gross margin more than your prompt does.
LLM EconomicsCustom AI Chips Will Reshape Token Prices: What Builders Should Do Now
Custom silicon from OpenAI, Google, Apple and SpaceX is built to cut inference cost, but that does not guarantee cheaper API prices for you, so model your margins across price scenarios instead of betting on one rate.
LLM EconomicsGPT-5.6 Pricing Explained: Sol vs Terra vs Luna Cost Breakdown
GPT-5.6 ships in three tiers, Sol at $5/$30, Terra at $2.50/$15, and Luna at $1/$6 per million tokens, so the cost decision is now about routing each task to the cheapest tier that clears your quality bar.
LLM EconomicsHow to Cut Your LLM API Costs and Protect Your SaaS Margins
A cheaper model can swing gross margin from roughly 30% to 85%, but only if you model your real token mix first: output tokens, not the headline input price, decide your unit economics.
LLM EconomicsOpenAI's Internal Token Use Grew Up to 56x: What It Means for Your AI Budget
OpenAI's own usage data shows median internal output tokens rising as much as 56x since November 2025, a warning that per-seat AI costs can compound far faster than headline price cuts.
LLM Economics1,000x Cheaper AI Inference: What It Would Actually Do to Your Margins
Even a 1,000x cut in inference power costs would reshape AI unit economics, but only the share of your bill that is energy moves at that rate, not hardware, overhead, or provider markup.
LLM EconomicsOpenAI's Custom Chip and What It Actually Means for Your API Bill
A custom inference chip lowers what it costs OpenAI to serve a token, but your API price only drops if they pass the savings through, so model your own cost per token instead of betting on hardware headlines.
Pricing math, in your inbox.
One short note a week on AI pricing, token economics, and margin. No spam, unsubscribe anytime.