GPT-5 vs GPT-5 mini
The single biggest cost lever: dropping a tier inside the same family.
Monthly cost by workload shape
The same volume costs very different amounts depending on the shape of the traffic. No caching or batch applied.
| Workload | GPT-5 | GPT-5 mini | Difference | |
|---|---|---|---|---|
Customer support chatbot 50K/day · 800 in / 300 out | $6,088.00 | $1,217.60 | GPT-5 minisaves $4,870.40 | Model it → |
RAG / search answers 20K/day · 3000 in / 400 out | $4,718.20 | $943.64 | GPT-5 minisaves $3,774.56 | Model it → |
Agent / tool-use loop 8.0K/day · 2500 in / 600 out | $2,222.12 | $444.42 | GPT-5 minisaves $1,777.70 | Model it → |
Batch summarization 100K/day · 5000 in / 500 out | $34.2K | $6,849.00 | GPT-5 minisaves $27.4K | Model it → |
Code assistant 15K/day · 2000 in / 800 out | $4,794.30 | $958.86 | GPT-5 minisaves $3,835.44 | Model it → |
Frequently asked questions
Which is cheaper, GPT-5 or GPT-5 mini?
At a typical 3:1 input-to-output ratio, GPT-5 mini is cheaper: $0.688 blended per 1M tokens against $3.44. That holds at every input:output ratio — one model is cheaper on both rates.
What is the price difference between GPT-5 and GPT-5 mini?
GPT-5: $1.25 input, $10.00 output per 1M tokens. GPT-5 mini: $0.250 input, $2.00 output. That is 5.0x on input and 5.0x on output.
Does prompt caching change the answer?
GPT-5 caches input at $0.125/1M and GPT-5 mini caches at $0.025/1M. For input-heavy workloads with repeated context, caching can matter more than the base rate difference — model both in the calculator rather than comparing rate cards.
This page compares published prices only. It makes no claim about which model performs better on any task — that depends entirely on your evaluations.
Rate cards decide nothing on their own.
Most teams run several models at once. Finitizer TokenOps shows what each one actually costs you in production, by team and feature, so a routing decision is made on data rather than on a price page.