comparison
GPT-5.4 nano vs DeepSeek V4 Pro
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 — about 1.2× less.
Positioned by published specs — size, context and modality — not measured performance; a smaller model can sometimes outperform a larger one on your task.
DeepSeek V4 Pro (Flagship) is a much larger technical class than GPT-5.4 nano (Nano). The cheaper model only wins if it can actually do your task; on anything demanding these aren't interchangeable.
| metric | GPT-5.4 nano | DeepSeek V4 Pro |
|---|---|---|
| Input / 1M | $0.20 | $0.43 |
| Output / 1M | $1.25 | $0.87 |
| Context | 400K | 1.0M |
| Technical class | Nano | Flagship |
| Cost @ typical workload | $185/mo | $217/mo |
| Modality | text + image | Text only |
| Price source | list | list |
| Provider | OpenAI | DeepSeek |
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 DeepSeek V4 Pro's $217/mo — roughly 1.2× 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, DeepSeek V4 Pro has the larger 1.0M-token window (~1,573 pages). Only GPT-5.4 nano accepts image input — decisive if your prompts include images. By technical class (size and context, not measured capability), DeepSeek V4 Pro is a Flagship 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 DeepSeek V4 Pro cheaper?
For a typical workload (1,500 input + 500 output tokens × 200,000 requests/month), GPT-5.4 nano costs $185/mo versus $217/mo for DeepSeek V4 Pro — about 1.2× 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 DeepSeek V4 Pro?
On price, GPT-5.4 nano is $0.20/$1.25 per 1M (in/out) and DeepSeek V4 Pro is $0.43/$0.87. By technical class (size & context) it's Flagship (DeepSeek V4 Pro) versus Nano (GPT-5.4 nano). DeepSeek V4 Pro has the larger context window at 1.0M tokens. Only GPT-5.4 nano accepts image input.
Is GPT-5.4 nano in the same class as DeepSeek V4 Pro?
No. By size & context, GPT-5.4 nano is a Nano and DeepSeek V4 Pro is a Flagship — 3 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
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- Claude Haiku 4.5 vs GPT-5.4 nano
- Gemini 2.5 Flash vs GPT-5.4 nano
Related
- GPT-5.4 nano and DeepSeek V4 Pro — full specs and price history.
- API cost calculator — compare on your own workload.
- All comparisons — the full head-to-head index.