GPT-5 Nano vs DeepSeek-V3: Detailed Comparison
Choosing between GPT-5 Nano (OpenAI) and
DeepSeek-V3 (DeepSeek) comes down to three things:
per-token pricing, context window, and which capability matters most for your workload.
GPT-5 Nano costs $0.05/M input vs
$0.27/M for DeepSeek-V3;
context windows are 400K vs
128K tokens. Detailed breakdown below.
Side-by-side specs
| Spec | GPT-5 Nano | DeepSeek-V3 |
|---|
| Provider | OpenAI | DeepSeek |
|---|
| Released | 2025-08-07 | 2024-12-26 |
|---|
| Input price |
$0.05/M |
$0.27/M |
| Output price |
$0.40/M |
$1.10/M |
| Cached input |
$0.0050/M |
$0.0700/M |
| Context window |
400K |
128K |
| Max output |
64K |
8K |
| Modalities |
text |
text |
| Tokenizer |
o200k_base |
deepseek |
Capability matrix
| Capability | GPT-5 Nano | DeepSeek-V3 |
|---|
| function calling |
Yes |
Yes |
| json mode |
Yes |
Yes |
| streaming |
Yes |
Yes |
Benchmark comparison
Higher is better for all benchmarks shown.
| Benchmark | Category | GPT-5 Nano | DeepSeek-V3 | Δ |
|---|
| MMLU-Pro |
general |
— |
75.9 |
— |
| HumanEval |
coding |
— |
82.6 |
— |
Per-call cost on typical workloads
| Workload (in/out tokens) | GPT-5 Nano | DeepSeek-V3 | Cheaper by |
|---|
| Standard chat (1K / 500) |
$0.000250 |
$0.000820 |
GPT-5 Nano by $0.000570 |
| RAG (4K / 500) |
$0.000400 |
$0.001630 |
GPT-5 Nano by $0.001230 |
| Long doc (20K / 1K) |
$0.001400 |
$0.006500 |
GPT-5 Nano by $0.005100 |
| Very long context (100K / 2K) |
$0.005600 |
$0.028650 |
GPT-5 Nano by $0.023050 |
When to choose GPT-5 Nano over DeepSeek-V3
- Per-token input cost is 81% lower — meaningful for high-volume workloads.
- Larger context window (400K vs 128K) — relevant when whole documents or long histories must fit in a single call.
When to choose DeepSeek-V3 over GPT-5 Nano
- DeepSeek-V3 fits when your stack is already on DeepSeek.
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