DeepSeek-V3.2 Instruct vs GPT-4.1 Turbo: which model should you choose?
We compared DeepSeek-V3.2 Instruct and GPT-4.1 Turbo on price, context window and 12 benchmarks. DeepSeek-V3.2 Instruct has the stronger average benchmark score; DeepSeek-V3.2 Instruct is cheaper on a blended 3:1 basis.
DeepSeek-V3.2 Instruct
DeepSeek-V3.2 Instruct is a frontier model from DeepSeek. It offers a 128,000-token context window, costs $5.91 per million input tokens and $29.01 per million output tokens, and averages 83.7 across the index's benchmark suite.
- Input
- $5.91 / 1M
- Output
- $29.01 / 1M
- Context
- 128,000
- Avg score
- 83.7
- Open weights
- Yes
GPT-4.1 Turbo
GPT-4.1 Turbo is a frontier model from OpenAI. It offers a 1,000,000-token context window, costs $16.12 per million input tokens and $69.91 per million output tokens, and averages 82.9 across the index's benchmark suite.
- Input
- $16.12 / 1M
- Output
- $69.91 / 1M
- Context
- 1,000,000
- Avg score
- 82.9
- Open weights
- No
Specification comparison
| Spec | DeepSeek-V3.2 Instruct | GPT-4.1 Turbo | Edge |
|---|---|---|---|
| Input price / 1M | $5.91 | $16.12 | A |
| Output price / 1M | $29.01 | $69.91 | A |
| Context window | 128,000 | 1,000,000 | B |
| Max output | 4,096 | 128,000 | B |
| Average score | 83.7 | 82.9 | A |
| Arena Elo | 1454.4 | 1446.2 | A |
| Open weights | Yes | No | A |
Benchmark comparison
DeepSeek-V3.2 Instruct wins 7, GPT-4.1 Turbo wins 4, and 1 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | DeepSeek-V3.2 Instruct | GPT-4.1 Turbo | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 84.6 | 84.6 | 0.0 | Tie |
| GPQA Diamond | 80.9 | 76.1 | 4.8 | DeepSeek-V3.2 Instruct |
| SWE-bench Verified | 75.2 | 74.7 | 0.5 | DeepSeek-V3.2 Instruct |
| HumanEval | 90.2 | 89.8 | 0.4 | DeepSeek-V3.2 Instruct |
| MATH-500 | 86.3 | 86.9 | 0.6 | GPT-4.1 Turbo |
| AIME 2025 | 83.9 | 77.4 | 6.5 | DeepSeek-V3.2 Instruct |
| LiveCodeBench | 75.2 | 78.7 | 3.5 | GPT-4.1 Turbo |
| IFEval | 91.3 | 88.2 | 3.1 | DeepSeek-V3.2 Instruct |
| TruthfulQA | 84.3 | 87.0 | 2.7 | GPT-4.1 Turbo |
| HellaSwag | 88.8 | 90.0 | 1.2 | GPT-4.1 Turbo |
| MMMU | 80.4 | 78.5 | 1.9 | DeepSeek-V3.2 Instruct |
| Arena Elo | 1454.4 | 1446.2 | 8.2 | DeepSeek-V3.2 Instruct |
Price analysis
On a blended 3:1 input-to-output basis, DeepSeek-V3.2 Instruct costs about $11.69 per million tokens and GPT-4.1 Turbo costs about $29.57. DeepSeek-V3.2 Instruct is roughly 60% cheaper than GPT-4.1 Turbo. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
GPT-4.1 Turbo has the larger context window at 1,000,000 tokens, compared with 128,000 for DeepSeek-V3.2 Instruct. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, DeepSeek-V3.2 Instruct wins 7, GPT-4.1 Turbo wins 4, and 1 are tied. On the index average, DeepSeek-V3.2 Instruct leads GPT-4.1 Turbo by 0.8 points (83.7 versus 82.9).
The price picture favours DeepSeek-V3.2 Instruct. The context picture favours GPT-4.1 Turbo. Those two dimensions often matter more than a few benchmark points once a model is good enough for the task.
If you need a single default, start with DeepSeek-V3.2 Instruct for quality-sensitive work, and check whether its price holds at your expected volume before committing.
Choose DeepSeek-V3.2 Instruct if
- You want the higher average benchmark score in this index.
- Unit cost matters and you want the cheaper blended price.
- You need open weights for self-hosting or fine-tuning.
Choose GPT-4.1 Turbo if
- You need the larger 1,000,000-token context window.
- You need the larger 128,000-token output limit.
FAQ
Is DeepSeek-V3.2 Instruct better than GPT-4.1 Turbo?
On the index average, DeepSeek-V3.2 Instruct leads GPT-4.1 Turbo by 0.8 points (83.7 versus 82.9). The better choice depends on price, context and your task. DeepSeek-V3.2 Instruct wins 7 benchmarks, GPT-4.1 Turbo wins 4.
Which is cheaper, DeepSeek-V3.2 Instruct or GPT-4.1 Turbo?
DeepSeek-V3.2 Instruct is cheaper on a blended 3:1 basis at about $11.69 per million tokens, versus $29.57 for GPT-4.1 Turbo.
Which has the larger context window?
GPT-4.1 Turbo has the larger context window at 1,000,000 tokens. DeepSeek-V3.2 Instruct has 128,000 tokens.
Are these models open weights?
DeepSeek-V3.2 Instruct is open weights; GPT-4.1 Turbo is proprietary.
Which should I choose for production?
If you need a single default, start with DeepSeek-V3.2 Instruct for quality-sensitive work, and check whether its price holds at your expected volume before committing.