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GPT-5.4 nano vs MiniMax M2.5

Token pricing, context window and real monthly cost, side by side. MiniMax M2.5 is the cheaper of the two for a typical workload — about 1.4× less.

cheaper for a typical workload
MiniMax M2.5
saves 27% vs GPT-5.4 nano at 1,500 in / 500 out × 200,000/mo
GPT-5.4 nano $185/mo
MiniMax M2.5 $135/mo
Mid vs Nano cheaper and a larger technical class on spec — the stronger pick here

Positioned by published specs — size, context and modality — not measured performance; a smaller model can sometimes outperform a larger one on your task.

Cost versus technical classGPT-5.4 nano: $185/mo, Nano class. MiniMax M2.5: $135/mo, Mid class. Plotted by monthly cost (horizontal) against technical class from size and context (vertical).best valuepremiumbudgetoverpricedGPT-5.4 nano$185/mo · NanoMiniMax M2.5$135/mo · Mid← lower cost · monthly $ · higher cost →
↑ technical class (size & context)
MiniMax M2.5 is the larger class — and the cheaper one

By size & context, MiniMax M2.5 (Mid) sits above GPT-5.4 nano (Nano) yet costs less. On spec it's the straightforward pick; choose GPT-5.4 nano only for something it offers that MiniMax M2.5 doesn't — modality, provider or ecosystem.

GPT-5.4 nano versus MiniMax M2.5 specifications and price.
metric GPT-5.4 nano MiniMax M2.5
Input / 1M $0.20 $0.15
Output / 1M $1.25 $0.90
Context 400K 205K
Technical class Nano Mid
Cost @ typical workload $185/mo $135/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, MiniMax M2.5 costs $135/mo against GPT-5.4 nano's $185/mo — roughly 1.4× 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, 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 the larger class (Mid) and the cheaper of the two — on spec, the stronger pick here.

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), MiniMax M2.5 costs $135/mo versus $185/mo for GPT-5.4 nano — about 1.4× 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 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 $0.15/$0.90. By technical class (size & context) it's Nano (GPT-5.4 nano) versus Mid (MiniMax M2.5). GPT-5.4 nano has the larger context window at 400K tokens. Only GPT-5.4 nano accepts image input.

Is MiniMax M2.5 in the same class as GPT-5.4 nano?

No. By size & context, MiniMax M2.5 is a Mid and GPT-5.4 nano is a Nano — 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.

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