Verified October 2026

Home › Compare › GPT-5.4 mini vs GPT-5.4 nano

GPT-5.4 mini vs GPT-5.4 nano

A straight cost comparison of GPT-5.4 mini (OpenAI) and GPT-5.4 nano (OpenAI), per 1,000,000 tokens, verified October 2026.

$0.75GPT-5.4 mini input / 1M
$0.20GPT-5.4 nano input / 1M
73%Blended price gap
GPT-5.4 nanoCheaper blended

Rate-by-rate comparison

USD per 1M tokens · October 2026
MetricGPT-5.4 miniGPT-5.4 nanoWinner
Input / 1M$0.75$0.20GPT-5.4 nano
Cached input / 1M$0.075$0.02GPT-5.4 nano
Cache write / 1M——Tie
Output / 1M$4.50$1.25GPT-5.4 nano
Context window400,000400,000Tie
Batch APIYesYesTie
Long-context tierNoneNone—

For per-token metrics, the lower number wins. For context window and batch support, the higher or broader option wins. A dash means the provider does not publish that rate: a missing cache-write fee means writes are not billed per token, while a missing cached-input rate means cache hits bill at the full input rate.

Blended cost: 1M input + 250K output

ModelBlended costDifference
GPT-5.4 mini$1.88+$1.36
GPT-5.4 nano$0.512Cheaper

Three workloads, two bills

WorkloadGPT-5.4 miniGPT-5.4 nanoWinner
Support chat
1,000 requests · 4K input / 600 output
$5.70$1.55GPT-5.4 nano
RAG with caching
1,000 requests · 50K input (45K cached) / 1K output
$11.66$3.16GPT-5.4 nano
Nightly batch job
10,000 requests · 10K input / 2K output
$82.50$22.50GPT-5.4 nano

Which one should you pick?

GPT-5.4 mini wins on none of the three workloads above, while GPT-5.4 nano wins on support chat, cached RAG, nightly batch job.

Beyond price, the two differ on input rate ($0.75 vs $0.20); output rate ($4.50 vs $1.25); cached-input rate ($0.075 vs $0.02).

Batch mode is available on GPT-5.4 mini and GPT-5.4 nano, which halves the nightly job. Both publish cached-input discounts, so a stable system prompt is worth caching on either.

FAQ

Is GPT-5.4 mini cheaper than GPT-5.4 nano?

On a blended 1M-input-plus-250K-output workload, GPT-5.4 nano is cheaper by 73% ($0.512 vs $1.88). The gap changes for cache-heavy prompts and for batch jobs, as the workload table shows.

Which handles longer prompts, GPT-5.4 mini or GPT-5.4 nano?

Both models share the same 400,000-token context window. Neither model publishes a long-context surcharge.

Do both models support prompt caching?

GPT-5.4 mini bills cached reads at $0.075 per 1M; GPT-5.4 nano at $0.02.

Related comparisons

Run your own token volumes