comparison
Gemini 3.1 Pro vs GPT-5.4 mini
Token pricing, context window and real monthly cost, side by side. GPT-5.4 mini is the cheaper of the two for a typical workload — about 2.7× less.
Positioned by published specs — size, context and modality — not measured performance; a smaller model can sometimes outperform a larger one on your task.
Gemini 3.1 Pro (Flagship) is two classes above GPT-5.4 mini (Mini) — different use-case territory. Weigh the saving against how hard your task is; treat them as alternatives, not equals.
| metric | Gemini 3.1 Pro | GPT-5.4 mini |
|---|---|---|
| Input / 1M | $2.00 | $0.75 |
| Output / 1M | $12.00 | $4.50 |
| Context | 1.0M | 400K |
| Technical class | Flagship | Mini |
| Cost @ typical workload | $1,800/mo | $675/mo |
| Modality | text + image + audio + video | text + image |
| Price source | list | list |
| Provider | OpenAI |
Snapshot . Cost uses a typical workload; tune it in the calculator. How we measure →
Which should you pick?
On a typical workload, GPT-5.4 mini costs $675/mo against Gemini 3.1 Pro's $1,800/mo — roughly 2.7× cheaper. But the ranking depends on your output-to-input ratio: output is the pricier direction for both, so an output-heavy job (code generation, long answers) widens the gap while an input-heavy one (summarization, retrieval) narrows it. If you need to fit more in a single prompt, Gemini 3.1 Pro has the larger 1.0M-token window (~1,573 pages). By technical class (size and context, not measured capability), Gemini 3.1 Pro is a Flagship and GPT-5.4 mini a Mini — so the lower price partly reflects a smaller class, not just a discount.
These are list and routed market prices, not measured outcomes. Two models at the same rate can still cost different amounts to finish the same task, because verbose or reasoning-heavy models emit more tokens. That gap is exactly what measured cost-per-task captures. The technical-class read above is likewise spec-based — size, context and modality, not measured performance — so a smaller model can still outperform a larger one on your specific task.
Frequently asked questions
Is Gemini 3.1 Pro or GPT-5.4 mini cheaper?
For a typical workload (1,500 input + 500 output tokens × 200,000 requests/month), GPT-5.4 mini costs $675/mo versus $1,800/mo for Gemini 3.1 Pro — about 2.7× less. Because output is priced higher than input, the winner can flip if your workload writes much more or less than this; check your own numbers in the calculator.
What's the main difference between Gemini 3.1 Pro and GPT-5.4 mini?
On price, Gemini 3.1 Pro is $2.00/$12.00 per 1M (in/out) and GPT-5.4 mini is $0.75/$4.50. By technical class (size & context) it's Flagship (Gemini 3.1 Pro) versus Mini (GPT-5.4 mini). Gemini 3.1 Pro has the larger context window at 1.0M tokens.
Is GPT-5.4 mini in the same class as Gemini 3.1 Pro?
No. By size & context, GPT-5.4 mini is a Mini and Gemini 3.1 Pro is a Flagship — 2 classes apart, so they're not drop-in substitutes. This is a spec comparison (size, context, modality), not a measured-performance one; a smaller model can still win on a task it's suited to.
More comparisons
- GPT-5.5 vs GPT-5.4 mini
- GPT-5.5 vs Gemini 3.1 Pro
- GPT-5.4 vs GPT-5.4 mini
- GPT-5.4 vs Gemini 3.1 Pro
- GPT-5.4 mini vs GPT-5.4 nano
- GPT-5.4 mini vs gpt-oss-120b
Related
- Gemini 3.1 Pro and GPT-5.4 mini — full specs and price history.
- API cost calculator — compare on your own workload.
- All comparisons — the full head-to-head index.