DeepSeek V3.2 vs GPT-4.1
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | DeepSeek V3.2 | GPT-4.1 |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Input Price (1M) | $0.28 | $2.00 |
| Output Price (1M) | $0.42 | $8.00 |
| Context Window | 128,000 | 1,000,000 |
Verdict
DeepSeek V3.2 costs $0.28 per 1M input tokens and $0.42 per 1M output tokens. GPT-4.1 costs $2.00 per 1M input tokens and $8.00 per 1M output tokens. DeepSeek V3.2 is 86% cheaper on input tokens than GPT-4.1. For output tokens, DeepSeek V3.2 is the more affordable option at $0.42/1M vs $8.00.
On context window, GPT-4.1 supports 1,000,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose DeepSeek V3.2
- ✓ You need the lowest input token cost ($ 0.28/1M)
- ✓ Your workload is output-heavy — DeepSeek V3.2 generates text cheaper
- ✓ You are already integrated with DeepSeek
When to choose GPT-4.1
- ✓ You need a larger context window (1,000,000 tokens)
- ✓ You are already integrated with OpenAI
Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.
Frequently Asked Questions
Is DeepSeek V3.2 cheaper than GPT-4.1? ▼
DeepSeek V3.2 is cheaper on input tokens at $0.28/1M vs $2.00/1M for GPT-4.1 — a 86% saving.
What is the context window of DeepSeek V3.2 vs GPT-4.1? ▼
DeepSeek V3.2 has a 128,000-token context window. GPT-4.1 has a 1,000,000-token context window. GPT-4.1 supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: DeepSeek V3.2 or GPT-4.1? ▼
The best choice depends on your use case. For cost efficiency on input tokens, DeepSeek V3.2 is the cheaper option. For maximum context length, GPT-4.1 supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.