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DeepSeek V3.2
deepseekdeepseek/deepseek-v3.2
Specifications
| Release date (V3.2 full) | 2025-12-02 (arXiv tech report)arxiv.org ↗ | verified |
| V3.2-Exp release | September 2025 (experimental, DSA debut)api-docs.deepseek.com ↗ | verified |
| Architecture | 671B-total / 37B-active MoE; MLA (Multi-Head Latent Attention) + DSA (DeepSeek Sparse Attention); RoPE; multi-token prediction training objectivearxiv.org ↗ | verified |
| Pretraining tokens (V3 backbone) | 14.8 trilliongithub.com ↗ | verified |
| Training cutoff | Not publicly disclosed | unknown |
Benchmarks
| Benchmark | Distribution | Score | Source |
|---|---|---|---|
MMLU (EM, Chat) From the V3 README — V3.2 benchmarks reported as on par with V3.1-Terminus, so this V3-baseline carries over within noise. | 88.5 | github.com ↗ | |
HumanEval-Mul (Pass@1, Chat) | 82.6 | github.com ↗ | |
MATH-500 (EM, Chat) | 90.2 | github.com ↗ | |
GSM8K (8-shot EM, Base) | 89.3 | github.com ↗ | |
GPQA-Diamond (Pass@1, Chat) | 59.1 | github.com ↗ | |
LiveCodeBench (Pass@1-COT) | 40.5 | github.com ↗ | |
AIME 2024 (Pass@1) | 39.2 | github.com ↗ | |
GPT-5 comparison (qualitative) Per the V3.2 tech report: with scaled post-training compute V3.2 performs comparably to GPT-5; the high-compute Speciale variant surpasses GPT-5 on reasoning and earned gold-medal scores at IMO/IOI/ICPC/CMO 2025. | Comparable to GPT-5; Speciale variant exceeds GPT-5 | arxiv.org ↗ |
Fact ledger — every claim on this page traces here
| source | URL | retrieved | |
|---|---|---|---|
| Release date (V3.2 full) | arxiv.org ↗ | 2026-05-22 | verified |
| V3.2-Exp release | api-docs.deepseek.com ↗ | 2026-05-22 | verified |
| Architecture | arxiv.org ↗ | 2026-05-22 | verified |
| Pretraining tokens (V3 backbone) | github.com ↗ | 2026-05-22 | verified |
| Training cutoff | — | — | unknown |
| License — code | github.com ↗ | 2026-05-22 | verified |
| License — weights | github.com ↗ | 2026-05-22 | verified |
| Supported inference backends | github.com ↗ | 2026-05-22 | verified |
| Successor | — | — | verified |
| MMLU (EM, Chat) | github.com ↗ | 2026-05-22 | to verify |
| HumanEval-Mul (Pass@1, Chat) | github.com ↗ | 2026-05-22 | to verify |
| MATH-500 (EM, Chat) | github.com ↗ | 2026-05-22 | to verify |
| GSM8K (8-shot EM, Base) | github.com ↗ | 2026-05-22 | to verify |
| GPQA-Diamond (Pass@1, Chat) | github.com ↗ | 2026-05-22 | to verify |
| LiveCodeBench (Pass@1-COT) | github.com ↗ | 2026-05-22 | to verify |
| AIME 2024 (Pass@1) | github.com ↗ | 2026-05-22 | to verify |
| GPT-5 comparison (qualitative) | arxiv.org ↗ | 2026-05-22 | to verify |
| DeepSeek publishes V3.2 technical report — same DSA architecture as V3.2-Exp, scaled post-training puts it on par with GPT-5 | arxiv.org/abs/2512.02556 ↗ | 2026-05-22 | verified |
| DeepSeek launches V3.2-Exp — debuts Sparse Attention (DSA), API price drops over 50% | api-docs.deepseek.com ↗ | 2026-05-22 | verified |
| What's the difference between V3.2 and V3.2-Exp? | arxiv.org ↗ | 2026-05-22 | to verify |
| What is DeepSeek Sparse Attention (DSA)? | arxiv.org ↗ | 2026-05-22 | to verify |
| Can I self-host DeepSeek V3.2? | github.com ↗ | 2026-05-22 | to verify |