DeepSeek-V3.2 Instruct vs o3 Turbo: which model should you choose?
We compared DeepSeek-V3.2 Instruct and o3 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
o3 Turbo
o3 Turbo is a frontier model from OpenAI. It offers a 200,000-token context window, costs $16.63 per million input tokens and $83.71 per million output tokens, and averages 83.4 across the index's benchmark suite.
- Input
- $16.63 / 1M
- Output
- $83.71 / 1M
- Context
- 200,000
- Avg score
- 83.4
- Open weights
- No
Specification comparison
| Spec | DeepSeek-V3.2 Instruct | o3 Turbo | Edge |
|---|---|---|---|
| Input price / 1M | $5.91 | $16.63 | A |
| Output price / 1M | $29.01 | $83.71 | A |
| Context window | 128,000 | 200,000 | B |
| Max output | 4,096 | 4,096 | Tie |
| Average score | 83.7 | 83.4 | A |
| Arena Elo | 1454.4 | 1456.2 | B |
| Open weights | Yes | No | A |
Benchmark comparison
DeepSeek-V3.2 Instruct wins 8, o3 Turbo wins 4, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | DeepSeek-V3.2 Instruct | o3 Turbo | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 84.6 | 82.7 | 1.9 | DeepSeek-V3.2 Instruct |
| GPQA Diamond | 80.9 | 77.7 | 3.2 | DeepSeek-V3.2 Instruct |
| SWE-bench Verified | 75.2 | 70.7 | 4.5 | DeepSeek-V3.2 Instruct |
| HumanEval | 90.2 | 87.4 | 2.8 | DeepSeek-V3.2 Instruct |
| MATH-500 | 86.3 | 90.6 | 4.3 | o3 Turbo |
| AIME 2025 | 83.9 | 83.0 | 0.9 | DeepSeek-V3.2 Instruct |
| LiveCodeBench | 75.2 | 80.7 | 5.5 | o3 Turbo |
| IFEval | 91.3 | 89.1 | 2.2 | DeepSeek-V3.2 Instruct |
| TruthfulQA | 84.3 | 83.6 | 0.7 | DeepSeek-V3.2 Instruct |
| HellaSwag | 88.8 | 91.8 | 3.0 | o3 Turbo |
| MMMU | 80.4 | 79.7 | 0.7 | DeepSeek-V3.2 Instruct |
| Arena Elo | 1454.4 | 1456.2 | 1.8 | o3 Turbo |
Price analysis
On a blended 3:1 input-to-output basis, DeepSeek-V3.2 Instruct costs about $11.69 per million tokens and o3 Turbo costs about $33.40. DeepSeek-V3.2 Instruct is roughly 65% cheaper than o3 Turbo. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
o3 Turbo has the larger context window at 200,000 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 8, o3 Turbo wins 4, and 0 are tied. On the index average, DeepSeek-V3.2 Instruct leads o3 Turbo by 0.3 points (83.7 versus 83.4).
The price picture favours DeepSeek-V3.2 Instruct. The context picture favours o3 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 o3 Turbo if
- You need the larger 200,000-token context window.
FAQ
Is DeepSeek-V3.2 Instruct better than o3 Turbo?
On the index average, DeepSeek-V3.2 Instruct leads o3 Turbo by 0.3 points (83.7 versus 83.4). The better choice depends on price, context and your task. DeepSeek-V3.2 Instruct wins 8 benchmarks, o3 Turbo wins 4.
Which is cheaper, DeepSeek-V3.2 Instruct or o3 Turbo?
DeepSeek-V3.2 Instruct is cheaper on a blended 3:1 basis at about $11.69 per million tokens, versus $33.40 for o3 Turbo.
Which has the larger context window?
o3 Turbo has the larger context window at 200,000 tokens. DeepSeek-V3.2 Instruct has 128,000 tokens.
Are these models open weights?
DeepSeek-V3.2 Instruct is open weights; o3 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.