DeepSeek-V3.2 Instruct vs Gemini 2.5 Pro Turbo: which model should you choose?
We compared DeepSeek-V3.2 Instruct and Gemini 2.5 Pro Turbo on price, context window and 12 benchmarks. Gemini 2.5 Pro Turbo 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
Gemini 2.5 Pro Turbo
Gemini 2.5 Pro Turbo is a frontier model from Google DeepMind. It offers a 1,000,000-token context window, costs $16.32 per million input tokens and $72.61 per million output tokens, and averages 83.9 across the index's benchmark suite.
- Input
- $16.32 / 1M
- Output
- $72.61 / 1M
- Context
- 1,000,000
- Avg score
- 83.9
- Open weights
- No
Specification comparison
| Spec | DeepSeek-V3.2 Instruct | Gemini 2.5 Pro Turbo | Edge |
|---|---|---|---|
| Input price / 1M | $5.91 | $16.32 | A |
| Output price / 1M | $29.01 | $72.61 | A |
| Context window | 128,000 | 1,000,000 | B |
| Max output | 4,096 | 128,000 | B |
| Average score | 83.7 | 83.9 | B |
| Arena Elo | 1454.4 | 1464.0 | B |
| Open weights | Yes | No | A |
Benchmark comparison
DeepSeek-V3.2 Instruct wins 6, Gemini 2.5 Pro Turbo wins 6, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | DeepSeek-V3.2 Instruct | Gemini 2.5 Pro Turbo | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 84.6 | 82.9 | 1.7 | DeepSeek-V3.2 Instruct |
| GPQA Diamond | 80.9 | 81.7 | 0.8 | Gemini 2.5 Pro Turbo |
| SWE-bench Verified | 75.2 | 71.4 | 3.8 | DeepSeek-V3.2 Instruct |
| HumanEval | 90.2 | 88.1 | 2.1 | DeepSeek-V3.2 Instruct |
| MATH-500 | 86.3 | 90.6 | 4.3 | Gemini 2.5 Pro Turbo |
| AIME 2025 | 83.9 | 83.7 | 0.2 | DeepSeek-V3.2 Instruct |
| LiveCodeBench | 75.2 | 78.6 | 3.4 | Gemini 2.5 Pro Turbo |
| IFEval | 91.3 | 90.7 | 0.6 | DeepSeek-V3.2 Instruct |
| TruthfulQA | 84.3 | 85.9 | 1.6 | Gemini 2.5 Pro Turbo |
| HellaSwag | 88.8 | 91.2 | 2.4 | Gemini 2.5 Pro Turbo |
| MMMU | 80.4 | 78.4 | 2.0 | DeepSeek-V3.2 Instruct |
| Arena Elo | 1454.4 | 1464.0 | 9.6 | Gemini 2.5 Pro Turbo |
Price analysis
On a blended 3:1 input-to-output basis, DeepSeek-V3.2 Instruct costs about $11.69 per million tokens and Gemini 2.5 Pro Turbo costs about $30.39. DeepSeek-V3.2 Instruct is roughly 62% cheaper than Gemini 2.5 Pro Turbo. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
Gemini 2.5 Pro 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 6, Gemini 2.5 Pro Turbo wins 6, and 0 are tied. On the index average, Gemini 2.5 Pro Turbo leads DeepSeek-V3.2 Instruct by 0.2 points (83.9 versus 83.7).
The price picture favours DeepSeek-V3.2 Instruct. The context picture favours Gemini 2.5 Pro 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 Gemini 2.5 Pro Turbo for quality-sensitive work and DeepSeek-V3.2 Instruct for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.
Choose DeepSeek-V3.2 Instruct if
- Unit cost matters and you want the cheaper blended price.
- You need open weights for self-hosting or fine-tuning.
Choose Gemini 2.5 Pro Turbo if
- You want the higher average benchmark score in this index.
- 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 Gemini 2.5 Pro Turbo?
On the index average, Gemini 2.5 Pro Turbo leads DeepSeek-V3.2 Instruct by 0.2 points (83.9 versus 83.7). The better choice depends on price, context and your task. DeepSeek-V3.2 Instruct wins 6 benchmarks, Gemini 2.5 Pro Turbo wins 6.
Which is cheaper, DeepSeek-V3.2 Instruct or Gemini 2.5 Pro Turbo?
DeepSeek-V3.2 Instruct is cheaper on a blended 3:1 basis at about $11.69 per million tokens, versus $30.39 for Gemini 2.5 Pro Turbo.
Which has the larger context window?
Gemini 2.5 Pro 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; Gemini 2.5 Pro Turbo is proprietary.
Which should I choose for production?
If you need a single default, start with Gemini 2.5 Pro Turbo for quality-sensitive work and DeepSeek-V3.2 Instruct for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.