AI model comparison
GPT-5.4 Nano vs DeepSeek V3.2
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
OpenAI
GPT-5.4 Nano
GPT-5.4 nano is the most lightweight and cost-efficient variant of the GPT-5.4 family, optimized for speed-critical and high-volume tasks.
- Input / 1M
- $0.20
- Output / 1M
- $1.25
- Context
- 400K
DeepSeek
DeepSeek V3.2
DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance.
- Input / 1M
- $0.26
- Output / 1M
- $0.42
- Context
- 164K
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
DeepSeek V3.2
1.4x cheaper for a typical chat
Higher intelligence score
DeepSeek V3.2
21.5 vs 20.7 on Artificial Analysis
Larger context window
GPT-5.4 Nano
400K vs 164K tokens
Newer release
GPT-5.4 Nano
Released March 17, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Coding index
Agentic index
Pricing
GPT-5.4 Nano vs DeepSeek V3.2 API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | ||
|---|---|---|
| Input tokensPer 1M tokens | $0.20 | $0.26 |
| Output tokensPer 1M tokens | $1.25 | $0.42 |
| Cached input (read)Per 1M tokens | $0.02 | $0.14 |
| Cache writePer 1M tokens | Not available | Not available |
| Web searchPer request | $0.01 | Not available |
What it costs in practice
Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.
Chat message
2K in, 500 out
Coding task
30K in, 4K out
Long document summary
150K in, 2K out
Specs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | ||
|---|---|---|
| Context window | 400K tokens | 164K tokens |
| Max output | 128K tokens | 147K tokens |
| Input types | File, Image, Text | Text |
| Output types | Text | Text |
| Reasoning effort levels | Extra high, High, Medium, Low, None | Not available |
| Default reasoning effort | Medium | Not available |
| Release date | March 17, 2026 | December 1, 2025 |
Features
Supported features
API features available for each model.
| Metric | ||
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | Supported | Supported |
| Temperature | Not supported | Supported |
| Stop sequences | Not supported | Supported |
| Deterministic seed | Supported | Supported |
| Verbosity control | Supported | Not supported |
Our take
DeepSeek V3.2 is 1.4x cheaper for a typical chat. DeepSeek V3.2 scores higher on the Artificial Analysis Intelligence Index (21.5 vs 20.7). GPT-5.4 Nano has the larger context window (400K vs 164K tokens). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.
FAQ
Frequently asked questions
Is GPT-5.4 Nano or DeepSeek V3.2 cheaper?
DeepSeek V3.2 is cheaper for a typical chat (2K input tokens and 500 output tokens). DeepSeek V3.2 costs $0.26 per 1M input tokens and $0.42 per 1M output tokens, while GPT-5.4 Nano costs $0.20 per 1M input tokens and $1.25 per 1M output tokens.
Which has a bigger context window, GPT-5.4 Nano or DeepSeek V3.2?
GPT-5.4 Nano supports up to 400K tokens of context, compared with 164K for DeepSeek V3.2.
Is GPT-5.4 Nano smarter than DeepSeek V3.2?
On the Artificial Analysis Intelligence Index, GPT-5.4 Nano scores 20.7 and DeepSeek V3.2 scores 21.5, putting DeepSeek V3.2 ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use GPT-5.4 Nano and DeepSeek V3.2 at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see GPT-5.4 Nano and DeepSeek V3.2 answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to GPT-5.4 Nano and DeepSeek V3.2 at the same time. Compare the answers side by side and keep the best one.