DeepSeek-V3.2 Instruct vs Gemini 2.5 Pro Max: which model should you choose?
We compared DeepSeek-V3.2 Instruct and Gemini 2.5 Pro Max on price, context window and 12 benchmarks. Gemini 2.5 Pro Max 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 Max
Gemini 2.5 Pro Max is a frontier model from Google DeepMind. It offers a 200,000-token context window, costs $16.94 per million input tokens and $64.80 per million output tokens, and averages 84.8 across the index's benchmark suite.
- Input
- $16.94 / 1M
- Output
- $64.80 / 1M
- Context
- 200,000
- Avg score
- 84.8
- Open weights
- No
Specification comparison
| Spec | DeepSeek-V3.2 Instruct | Gemini 2.5 Pro Max | Edge |
|---|---|---|---|
| Input price / 1M | $5.91 | $16.94 | A |
| Output price / 1M | $29.01 | $64.80 | A |
| Context window | 128,000 | 200,000 | B |
| Max output | 4,096 | 65,536 | B |
| Average score | 83.7 | 84.8 | B |
| Arena Elo | 1454.4 | 1450.2 | A |
| Open weights | Yes | No | A |
Benchmark comparison
DeepSeek-V3.2 Instruct wins 5, Gemini 2.5 Pro Max wins 6, and 1 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | DeepSeek-V3.2 Instruct | Gemini 2.5 Pro Max | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 84.6 | 86.7 | 2.1 | Gemini 2.5 Pro Max |
| GPQA Diamond | 80.9 | 79.8 | 1.1 | DeepSeek-V3.2 Instruct |
| SWE-bench Verified | 75.2 | 75.5 | 0.3 | Gemini 2.5 Pro Max |
| HumanEval | 90.2 | 87.0 | 3.2 | DeepSeek-V3.2 Instruct |
| MATH-500 | 86.3 | 91.6 | 5.3 | Gemini 2.5 Pro Max |
| AIME 2025 | 83.9 | 82.6 | 1.3 | DeepSeek-V3.2 Instruct |
| LiveCodeBench | 75.2 | 79.9 | 4.7 | Gemini 2.5 Pro Max |
| IFEval | 91.3 | 91.3 | 0.0 | Tie |
| TruthfulQA | 84.3 | 85.5 | 1.2 | Gemini 2.5 Pro Max |
| HellaSwag | 88.8 | 92.9 | 4.1 | Gemini 2.5 Pro Max |
| MMMU | 80.4 | 79.7 | 0.7 | DeepSeek-V3.2 Instruct |
| Arena Elo | 1454.4 | 1450.2 | 4.2 | 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 Gemini 2.5 Pro Max costs about $28.91. DeepSeek-V3.2 Instruct is roughly 60% cheaper than Gemini 2.5 Pro Max. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
Gemini 2.5 Pro Max 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 5, Gemini 2.5 Pro Max wins 6, and 1 are tied. On the index average, Gemini 2.5 Pro Max leads DeepSeek-V3.2 Instruct by 1.1 points (84.8 versus 83.7).
The price picture favours DeepSeek-V3.2 Instruct. The context picture favours Gemini 2.5 Pro Max. 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 Max 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 Max if
- You want the higher average benchmark score in this index.
- You need the larger 200,000-token context window.
- You need the larger 65,536-token output limit.
FAQ
Is DeepSeek-V3.2 Instruct better than Gemini 2.5 Pro Max?
On the index average, Gemini 2.5 Pro Max leads DeepSeek-V3.2 Instruct by 1.1 points (84.8 versus 83.7). The better choice depends on price, context and your task. DeepSeek-V3.2 Instruct wins 5 benchmarks, Gemini 2.5 Pro Max wins 6.
Which is cheaper, DeepSeek-V3.2 Instruct or Gemini 2.5 Pro Max?
DeepSeek-V3.2 Instruct is cheaper on a blended 3:1 basis at about $11.69 per million tokens, versus $28.91 for Gemini 2.5 Pro Max.
Which has the larger context window?
Gemini 2.5 Pro Max 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; Gemini 2.5 Pro Max is proprietary.
Which should I choose for production?
If you need a single default, start with Gemini 2.5 Pro Max 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.