GPT-5 mini vs GPT-5.6 Luna: cost compared

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GPT-5.6 Luna is 20% cheaper on input and 40% cheaper on output than GPT-5 mini. Whether that makes it the right choice depends entirely on whether it does your task well enough — this page gives you the cost side of that trade, precisely.

Rates side by side

$ per million tokensGPT-5 miniGPT-5.6 Luna
Input$0.25$0.20
Output$2.00$1.20
Cached input$0.03$0.02
Output : input ratio8.0×6.0×

What the difference is worth

Monthly cost for the same workload on each, without caching:

WorkloadGPT-5 miniGPT-5.6 LunaDifference
Support chatbot
1,000 conversations/month · 2,000 in + 500 out each
$1.50$1.00$0.5000 saved
RAG search
10,000 queries/month · 8,000 in + 400 out each
$28.00$20.80$7.20 saved
Bulk extraction
10,000 documents · 3,000 in + 300 out each
$13.50$9.60$3.90 saved
Coding agent
100 runs/month · 400,000 in + 20,000 out each
$14.00$10.40$3.60 saved

Which to use

GPT-5.6 Luna if the task is well-specified and mechanical — extraction, classification, formatting, routine transformation. The saving is real and compounds with volume.

GPT-5 mini if the task involves genuine reasoning, long-horizon planning, or work where a wrong answer is expensive to catch. Paying 1.3× more on input is trivial compared to the cost of shipping a bad result.

Both are OpenAI models, so switching is usually a one-line change and the tokenizer is the same — which makes this a genuinely easy experiment to run. Test on your own workload before deciding.

Don't skip caching

Cached input costs $0.03 on GPT-5 mini and $0.02 on GPT-5.6 Luna. If your prompts share a stable prefix, caching on the more expensive model can beat switching to the cheaper one outright — worth checking before you migrate anything.

Sources

OpenAI rates verified 2026-08-05 (source). OpenAI rates verified 2026-08-05 (source).