datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
deepseek-v3.2-speciale-openr1-math-3kInspired by @OpenR1
The questions for this dataset were all sourced from the first 3.3k prompts in open-r1/OpenR1-Math-220k
Dataset Stats (provided by OpenRouter):
Cost: $ 21.1 (USD)
Tokens (input + output): 52.3 M
deepseek-v3.2-speciale-OpenCodeReasoning-3kThe questions for this dataset were all sourced from the first 3k prompts in nvidia/OpenCodeReasoning
Dataset Stats (provided by OpenRouter):
Cost: $ 19.2 (USD)
Tokens (input + output): 47 M
deepseek-v3.2-speciale-1000xThis is a reasoning dataset created using Deepseek v3.2 Speciale with a reasoning depth set to high. Some of these questions are from reedmayhew and the rest were generated.
The dataset is meant for creating distilled versions of Deepseek v3.2 Speciale by fine-tuning already existing open-source LLMs.
Stats
Costs: $ 1.46 (USD)
Total tokens (input + output): 3.61 M
DeepSeek-V3.2-Exp-reasoning-example
🐳 DeepSeek-V3.2-Exp-reasoning vs DeepSeek-R1-0528: Math Reasoning Comparison 🍎
Note: DeepSeek-R1-0528 has no explicit chain-of-thought, while deepseek-ai/DeepSeek-V3.2-Exp (abbrev. V3.2-Exp) produces answers with structured derivations. This report was analyzed by GPT-5-Extended-Thinking. The sample size is small; conclusions are for reference only.
Author: Soren
1. Executive Summary
Sample size: 208 problems (mixed types).
Average steps (reasoning… See the full description on the dataset page: https://huggingface.co/datasets/Jackrong/DeepSeek-V3.2-Exp-reasoning-example.DeepSeek-V3.2_with_boxeddeepseek-v3.2-speciale-OpenCodeReasoning-3kThe questions for this dataset were all sourced from the first 3k prompts in nvidia/OpenCodeReasoning
Dataset Stats (provided by OpenRouter):
Cost: $ 19.2 (USD)
Tokens (input + output): 47 M
deepseek-v3.2-thinking-html-distillation-750A small toy dataset generated using DeepSeek-V3.2-Thinking, designed for web design tasks involving HTML, CSS, and JavaScript.
claude-4.5-opus-high-reasoning-X-DeepseekV3.2-264xThis is a reasoning dataset created using Claude Opus 4.5 with a reasoning depth set to high. Some of these questions are from reedmayhew and the rest were generated.
The dataset is meant for creating distilled versions of Claude Opus 4.5 by fine-tuning already existing open-source LLMs.
Stats
Costs: $ 52.3 (USD)
Total tokens (input + output): 2.13 M