comparison
GPT-5.4 mini vs Kimi K2 Thinking
Token pricing, context window and real monthly cost, side by side. Kimi K2 Thinking is the cheaper of the two for a typical workload — about 1.6× 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, Kimi K2 Thinking (Flagship) 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 Kimi K2 Thinking doesn't — modality, provider or ecosystem.
| metric | GPT-5.4 mini | Kimi K2 Thinking |
|---|---|---|
| Input / 1M | $0.75 | $0.60 |
| Output / 1M | $4.50 | $2.50 |
| Context | 400K | 262K |
| Technical class | Mini | Flagship |
| Cost @ typical workload | $675/mo | $430/mo |
| Modality | text + image | Text only |
| Price source | list | routed |
| Provider | OpenAI | Moonshot |
Snapshot . Cost uses a typical workload; tune it in the calculator. How we measure →
Which should you pick?
On a typical workload, Kimi K2 Thinking costs $430/mo against GPT-5.4 mini's $675/mo — roughly 1.6× 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), Kimi K2 Thinking is the larger class (Flagship) 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 Kimi K2 Thinking cheaper?
For a typical workload (1,500 input + 500 output tokens × 200,000 requests/month), Kimi K2 Thinking costs $430/mo versus $675/mo for GPT-5.4 mini — about 1.6× 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 Kimi K2 Thinking?
On price, GPT-5.4 mini is $0.75/$4.50 per 1M (in/out) and Kimi K2 Thinking is $0.60/$2.50. By technical class (size & context) it's Mini (GPT-5.4 mini) versus Flagship (Kimi K2 Thinking). GPT-5.4 mini has the larger context window at 400K tokens. Only GPT-5.4 mini accepts image input.
Is Kimi K2 Thinking in the same class as GPT-5.4 mini?
No. By size & context, Kimi K2 Thinking is a Flagship and GPT-5.4 mini is a Mini — 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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- Claude Sonnet 4.6 vs GPT-5.4 mini
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Related
- GPT-5.4 mini and Kimi K2 Thinking — full specs and price history.
- API cost calculator — compare on your own workload.
- All comparisons — the full head-to-head index.