comparison
GPT-5.4 mini 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 5.0× less.
Positioned by published specs — size, context and modality — not measured performance; a smaller model can sometimes outperform a larger one on your task.
By size & context, MiniMax M2.5 (Mid) sits above GPT-5.4 mini (Mini) yet costs less. On spec it's the straightforward pick; choose GPT-5.4 mini only for something it offers that MiniMax M2.5 doesn't — modality, provider or ecosystem.
| metric | GPT-5.4 mini | MiniMax M2.5 |
|---|---|---|
| Input / 1M | $0.75 | $0.15 |
| Output / 1M | $4.50 | $0.90 |
| Context | 400K | 205K |
| Technical class | Mini | Mid |
| Cost @ typical workload | $675/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 mini's $675/mo — roughly 5.0× 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 mini has the larger 400K-token window (~600 pages). Only GPT-5.4 mini 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 mini 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 $675/mo for GPT-5.4 mini — about 5.0× 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 mini and MiniMax M2.5?
On price, GPT-5.4 mini is $0.75/$4.50 per 1M (in/out) and MiniMax M2.5 is $0.15/$0.90. By technical class (size & context) it's Mini (GPT-5.4 mini) versus Mid (MiniMax M2.5). GPT-5.4 mini has the larger context window at 400K tokens. Only GPT-5.4 mini accepts image input.
Why is MiniMax M2.5 so much cheaper than GPT-5.4 mini?
MiniMax M2.5 has a much lower per-token rate — $0.90/1M output versus $4.50, and it's a smaller technical class (Mid vs Mini). The headline rate isn't the whole story, though: a verbose model can cost more to finish a task than its rate implies — that's what measured cost-per-task captures.
More comparisons
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- GPT-5.4 mini vs GPT-5.4 nano
- GPT-5.4 mini vs gpt-oss-120b
- Claude Sonnet 4.6 vs GPT-5.4 mini
- Claude Haiku 4.5 vs GPT-5.4 mini
Related
- GPT-5.4 mini 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.