Cost Per Token
The unit economics of LLM APIs.
/ quick answer
Providers price separately for input and output tokens, usually per million. Output is typically 3-5x more expensive than input, so long context is cheap but long answers are not. The unit economics of LLM APIs.
What is Cost Per Token?
Providers price separately for input and output tokens, usually per million. Output is typically 3-5x more expensive than input, so long context is cheap but long answers are not.
What is an example of Cost Per Token?
GPT-4o mini: $0.15/M input, $0.60/M output — a $0.001 support answer at 2k in + 500 out.
Why does Cost Per Token matter for AI and automation?
The unit economics of LLM APIs. It connects to the workflows, prompts and tool stacks linked on this page, so you can move from definition to execution without leaving Onexial.
/ continue exploring
Related concepts
The vocabulary this page depends on.
- →Token Budgeting
Token budgeting is the strategic allocation and management of token usage within large language model (LLM) operations to control costs and optimize performance.
- →AI Cost Control
AI cost control is the practice of monitoring, analyzing, and managing the financial expenditures associated with developing, deploying, and operating artificial intelligence systems.
- →Token Budget
A token budget is a predefined limit on the number of tokens an AI application or specific request can consume within a given period or for a single interaction. It is a critical mechanism for controlling costs and managing resource allocation for Large Language Model (LLM) usage.
- →AI Router
A layer that picks the cheapest capable model for each request, saving cost and latency.
Related workflows
Turn this into a repeatable process.
- →Context Window Optimization Workflow
This workflow outlines steps to optimize the information fed into an LLM's finite context window, ensuring maximal relevance and efficiency while managing token limits.
- →Optimize AI Agent Token Costs
This workflow outlines steps to systematically analyze, reduce, and manage token consumption for AI agents, ensuring cost-effective operation.
- →How to Create a Website with AI
Go from idea to a live, custom-domain website in one afternoon using AI builders.
- →How to Build an AI Content System
A repeatable pipeline that turns one input into publish-ready content across every channel.
Related tool stacks
The tools that run it in production.
- →AI Research & Knowledge Stack
Default toolset for analysts, founders and creators doing deep research with AI.
Comparisons & alternatives
Pick between the options.
- →ChatGPT vs Claude
Two leading conversational AI assistants compared across reasoning, writing, coding, and pricing.
- →Lovable vs Bolt
Two AI app builders compared on speed, backend, deployment, and production readiness.
- →OpenAI API vs Anthropic API
Choosing between the two leading LLM API providers for production apps.
- →Lovable vs Cursor
Prompt-to-app builder vs AI-assisted code editor — which one should you reach for?