Contamination MapText / LLM / Model
DeepSeek-V3.2-Exp
- Organisation
- DeepSeek-AI
- Family
- DeepSeek · version V3.2-Exp
- Released
- 2025-09-29 (DeepSeek API Docs news entry 'DeepSeek-V3.2-Exp Release 2025/09/29', https://api-docs.deepseek.com/news/news1226)
- Checkpoints
- deepseek-ai/DeepSeek-V3.2-Exp-Base, deepseek-ai/DeepSeek-V3.2-Exp
- Weights
- Open · MIT
- Links
- PaperModel card
Training data disclosure: Vague
Level determined for 0% of benchmark cells.
- TestTest data seen0
- SeenSeen, split unclear0
- TrainTraining data seen0
- Related data seen0
- NoNot seen0
- ?Unknown15
“the distribution of training data is totally aligned with the 128K long context extension data used for DeepSeek-V3.1-Terminus.”
Other declared training data
-
continued pre-training data aligned with the DeepSeek-V3.1-Terminus 128K long-context extension data (not yet matched to a dataset) · split: unknown
Evidence
“the distribution of training data is totally aligned with the 128K long context extension data used for DeepSeek-V3.1-Terminus.”
huggingface.co · paper · Section 2.1.1 · retrieved 2026-10-15 “Starting from a base checkpoint of DeepSeek-V3.1-Terminus, whose context length has been extended to 128K, we perform continued pre-training followed by post-training”
huggingface.co · paper · Section 2.1.1 · retrieved 2026-10-15
Benchmark cells
Classic LLM benchmarks
Unknown MMLU (Measuring Massive Multitask Language Understanding) · training data not disclosed in enough detail
Unknown GSM8K (Grade School Math 8K) · training data not disclosed in enough detail
Unknown MATH (Mathematics Aptitude Test of Heuristics) · training data not disclosed in enough detail
Unknown HumanEval · training data not disclosed in enough detail
Unknown ARC-Challenge (AI2 Reasoning Challenge, Challenge Set) · training data not disclosed in enough detail
Unknown HellaSwag · training data not disclosed in enough detail
Unknown TruthfulQA · training data not disclosed in enough detail
Unknown WinoGrande · training data not disclosed in enough detail
Recent LLM benchmarks
Unknown GPQA Diamond · training data not disclosed in enough detail
Unknown MMLU-Pro · training data not disclosed in enough detail
Unknown LiveCodeBench (code generation, release_v6) · training data not disclosed in enough detail
Unknown SWE-bench Verified · training data not disclosed in enough detail
Unknown AIME 2024 · training data not disclosed in enough detail
Unknown AIME 2025 · training data not disclosed in enough detail
Unknown MATH-500 · training data not disclosed in enough detail
Notes
Adds DeepSeek Sparse Attention to V3.1-Terminus via continued pre-training (2.1B + 943.7B tokens); training configuration deliberately aligned with V3.1-Terminus.
Sources
- DeepSeek-V3.2-Exp model card · model card · retrieved 2026-10-15
- DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models · paper · retrieved 2026-10-15