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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o4 vs o3: 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

o4o3
Input / 1M tokens$4$2
Output / 1M tokens$16$8
Context window200K200K
Cost — 10M in + 3M out$88$44

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

Which is cheaper?

o3 is the cheaper option on a 10M-in / 3M-out workload — about $44/mo versus $88 for o4 (~2.0× 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: o4 · o3.

Frequently asked

Is o4 or o3 cheaper?

At a typical 10M input + 3M output tokens per month, o3 costs about $44 versus $88 for o4 — o3 is roughly 2.0x cheaper on this workload. Your ratio of input to output tokens changes the gap.

What's the price difference between o4 and o3?

o4 is $4/$16 per 1M input/output tokens; o3 is $2/$8. Output tokens usually dominate a bill, so compare the output price first.

Which has the bigger context window, o4 or o3?

o4 supports about 200K tokens and o3 about 200K. A bigger window costs more per call because every token in context is billed.

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Educational estimates — not affiliated with any provider.