comparison
GPT-5.4 nano vs MiniMax M2.5
Token pricing, context window and real monthly cost, side by side. GPT-5.4 nano is the cheaper of the two for a typical workload (near-identical cost).
Positioned by published specs — size, context and modality — not measured performance; a smaller model can sometimes outperform a larger one on your task.
MiniMax M2.5 (Mid) is two classes above GPT-5.4 nano (Nano) — different use-case territory. Weigh the saving against how hard your task is; treat them as alternatives, not equals.
| metric | GPT-5.4 nano | MiniMax M2.5 |
|---|---|---|
| Input / 1M | $0.20 | $0.27 |
| Output / 1M | $1.25 | $1.08 |
| Context | 400K | 205K |
| Technical class | Nano | Mid |
| Cost @ typical workload | $185/mo | $189/mo |
| Modality | text + image | Text only |
| Price source | list | routed |
| Provider | OpenAI | MiniMax |
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 nano costs $185/mo against MiniMax M2.5's $189/mo, essentially the same. 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, GPT-5.4 nano has the larger 400K-token window (~600 pages). Only GPT-5.4 nano accepts image input — decisive if your prompts include images. By technical class (size and context, not measured capability), MiniMax M2.5 is a Mid and GPT-5.4 nano a Nano — 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 GPT-5.4 nano or MiniMax M2.5 cheaper?
For a typical workload (1,500 input + 500 output tokens × 200,000 requests/month), GPT-5.4 nano costs $185/mo versus $189/mo for MiniMax M2.5. 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 GPT-5.4 nano and MiniMax M2.5?
On price, GPT-5.4 nano is $0.20/$1.25 per 1M (in/out) and MiniMax M2.5 is $0.27/$1.08. By technical class (size & context) it's Mid (MiniMax M2.5) versus Nano (GPT-5.4 nano). GPT-5.4 nano has the larger context window at 400K tokens. Only GPT-5.4 nano accepts image input.
Is GPT-5.4 nano in the same class as MiniMax M2.5?
No. By size & context, GPT-5.4 nano is a Nano and MiniMax M2.5 is a Mid — 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
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- GPT-5.4 mini vs GPT-5.4 nano
- GPT-5.4 mini vs MiniMax M2.5
- GPT-5.4 nano vs gpt-oss-120b
- Claude Haiku 4.5 vs GPT-5.4 nano
Related
- GPT-5.4 nano and MiniMax M2.5 — full specs and price history.
- API cost calculator — compare on your own workload.
- All comparisons — the full head-to-head index.