Model comparison
DeepSeek-V3.2-Speciale vs DeepSeek-V3.2-Exp
- Input
- $0.28 / 1M tokens (cache miss)
- Output
- $0.42 / 1M tokens
- Context
- 128K
- Released
- 2025-12-01
- Input
- $0.28 / 1M tokens (cache miss)
- Output
- $0.42 / 1M tokens
- Context
- 128K
- Released
- 2025-09-29
DeepSeek-V3.2-Speciale scores higher on 4 of the 4 benchmarks both models report; both charge the same $0.3 per 1M input tokens.
Specs and pricing side by side
| Spec | DeepSeek-V3.2-Speciale | DeepSeek-V3.2-Exp |
|---|---|---|
| Maker | DeepSeek | DeepSeeksame |
| Released | 2025-12-01 | 2025-09-29 |
| Context window | 128K | 128Ksame |
| Max output | 128K | 64K |
| Input price | $0.28 / 1M tokens (cache miss) | $0.28 / 1M tokens (cache miss)same |
| Output price | $0.42 / 1M tokens | $0.42 / 1M tokenssame |
| Parameters | 671B total / 37B active (MoE) | 685B total (~37B active, MoE) |
| License | MIT | MITsame |
| Weights | Open weights | Open weightssame |
| Modalities | Text | Textsame |
| Knowledge cutoff | Not disclosed | not published |
Benchmarks both models report
| Benchmark | DeepSeek-V3.2-Speciale | DeepSeek-V3.2-Exp |
|---|---|---|
| AIME 2025 | 96% | 89.3% |
| LiveCodeBench | 88.7% | 74.1% |
| GPQA Diamond | 85.7% | 79.9% |
| Humanity's Last Exam | 30.6% | 19.8% |
Scores are as published by each maker or its cited source; harness, reasoning effort and date can differ between rows, so treat small gaps as ties. Sources are listed on each model page.
Which one should you pick?
Pick DeepSeek-V3.2-Speciale if…
- You care about AIME 2025, LiveCodeBench, GPQA Diamond (it scores higher on 4 shared benchmarks).
- Your use case is: solving competition-grade mathematics and writing formal mathematical proofs.
Pick DeepSeek-V3.2-Exp if…
- Your use case is: long-context document, codebase, and transcript analysis where attention cost dominates.
FAQ
Which is better, DeepSeek-V3.2-Speciale or DeepSeek-V3.2-Exp?
DeepSeek-V3.2-Speciale scores higher on 4 of the 4 benchmarks both models report; both charge the same $0.3 per 1M input tokens. The better pick depends on whether you value benchmark scores, price per token, context length or openness for your workload.
How do DeepSeek-V3.2-Speciale and DeepSeek-V3.2-Exp pricing compare?
DeepSeek-V3.2-Speciale: $0.28 / 1M tokens (cache miss) input, $0.42 / 1M tokens output. DeepSeek-V3.2-Exp: $0.28 / 1M tokens (cache miss) input, $0.42 / 1M tokens output (list API prices as published by each maker).
What are the context windows of DeepSeek-V3.2-Speciale and DeepSeek-V3.2-Exp?
DeepSeek-V3.2-Speciale offers 128K with up to 128K output; DeepSeek-V3.2-Exp offers 128K with up to 64K output.
Is DeepSeek-V3.2-Speciale newer than DeepSeek-V3.2-Exp?
DeepSeek-V3.2-Speciale was released 2025-12-01; DeepSeek-V3.2-Exp was released 2025-09-29.
Go deeper
- DeepSeek-V3.2-Speciale: full specs, pricing and benchmarks
- DeepSeek-V3.2-Exp: full specs, pricing and benchmarks
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