Comparison page
GPT-5.4 vs GPT-5.4 mini
Compare OpenAI's flagship model against its cheaper mini tier using the same request shape.
Side-by-side pricing
The table uses the same example request on both models so you can compare flagship versus low-cost openai usage without changing the prompt shape.
Input 1,000 / Output 250
| Model | Input / 1M | Cached input / 1M | Output / 1M | Example request | Source |
|---|---|---|---|---|---|
GPT-5.4 OpenAI's latest flagship general-purpose model for complex work. | $2.50 | No public rate | $15.0 | $0.0063 | OpenAI pricing |
GPT-5.4 mini Latest mini model in the GPT-5.4 family for coding and agentic workflows. | $0.750 | No public rate | $4.50 | $0.0019 | OpenAI pricing |
When to choose each model
GPT-5.4
Choose GPT-5.4 when you want the economics or capability profile of OpenAI and you can justify the published rate.
GPT-5.4 mini
Choose GPT-5.4 mini when you need the second option in this comparison and want to test whether it lowers spend without hurting the workflow.
Use cases
- • Choosing a default model for an internal tool.
- • Deciding when quality justifies the higher rate.
- • Estimating the tradeoff for high-volume content generation.
If the prompt is noisy or repetitive, run it through the prompt optimizer first.
If the brief is too loose, use the context engineer to tighten the instructions before you compare models again.
For the broader pricing strategy, read the LLM cost optimization pillar and the cost-per-million-tokens cheat sheet.
FAQ
Is GPT-5.4 mini always the best value?
Not always. It is usually the cheapest OpenAI option in the shared dataset, but the flagship model may still be worth it when accuracy matters more than raw token cost.
Why keep this comparison on its own page?
Because many teams want an obvious internal benchmark between the flagship model and the mini tier without comparing across providers first.
Where do I see the per-request estimate?
The comparison page shows the pricing context, while the calculator gives you a request-level estimate for the exact prompt size you expect.