How LLM API Pricing Works

Tokens, input vs output, context windows — why the same task can cost 50× more on one model than another, explained simply.

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GPT-6 Luna vs GPT-5 nano: price comparison

Real 2026 API prices side by side, with the total cost of a typical 10M-input / 3M-output monthly workload.

Price & cost at a glance

GPT-6 LunaGPT-5 nano
Input / 1M tokens$0.1$0.1
Output / 1M tokens$0.5$0.4
Context window272K400K
Cost — 10M in + 3M out$2.5$2.2

Green = cheaper / larger. Prices per 1M tokens, USD. Snapshot 2026 — verify with the provider.

Which is cheaper?

GPT-5 nano is the cheaper option on a 10M-in / 3M-out workload — about $2.2/mo versus $2.5 for GPT-6 Luna (~1.1× difference). Because output tokens are billed higher, the model with the lower output price usually wins as your responses get longer.

Run your own token mix in the cost calculator, or see each model in depth: GPT-6 Luna · GPT-5 nano.

Frequently asked

Is GPT-6 Luna or GPT-5 nano cheaper?

At a typical 10M input + 3M output tokens per month, GPT-5 nano costs about $2.2 versus $2.5 for GPT-6 Luna — GPT-5 nano is roughly 1.1x cheaper on this workload. Your ratio of input to output tokens changes the gap.

What's the price difference between GPT-6 Luna and GPT-5 nano?

GPT-6 Luna is $0.1/$0.5 per 1M input/output tokens; GPT-5 nano is $0.1/$0.4. Output tokens usually dominate a bill, so compare the output price first.

Which has the bigger context window, GPT-6 Luna or GPT-5 nano?

GPT-6 Luna supports about 272K tokens and GPT-5 nano about 400K. A bigger window costs more per call because every token in context is billed.

Educational estimates — not affiliated with any provider.