datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
aqua_rat
Dataset Card for AQUA-RAT
Dataset Summary
A large-scale dataset consisting of approximately 100,000 algebraic word problems.
The solution to each question is explained step-by-step using natural language.
This data is used to train a program generation model that learns to generate the explanation,
while generating the program that solves the question.
Supported Tasks and Leaderboards
Languages
en
Dataset Structure
Data Instances… See the full description on the dataset page: https://huggingface.co/datasets/deepmind/aqua_rat.deepsearchqa
DeepSearchQA
A 900-prompt factuality benchmark from Google DeepMind, designed to evaluate agents on difficult multi-step information-seeking tasks across 17 different fields.
▶ Google DeepMind Release Blog Post▶ DeepSearchQA Leaderboard on Kaggle▶ Technical Report▶ Evaluation Starter Code
Benchmark
DeepSearchQA is a 900-prompt benchmark for evaluating agents on difficult multi-step information-seeking tasks across 17 different fields. Unlike traditional… See the full description on the dataset page: https://huggingface.co/datasets/google/deepsearchqa.DeepSWEGym2
Dataset Description
This dataset is a filtered and deduplicated version of a merge containing many high quality SWE datasets, it aims to improve benchmark results on DeepSWE-style problems, benchmarks, and general coding skills.
It is specifically filtered for rows with complex/long code problems in the original datasets, having an average row size of 214.19kb, a total uncompressed size of 17.56GB, and a total of 85974 examples.
Dataset Details
Curated by:… See the full description on the dataset page: https://huggingface.co/datasets/MoreThought/DeepSWEGym2.deepsql_training
SynSQL Data Processing
A Python tool for processing the SynSQL-2.5M dataset into optimized Parquet format for machine learning workflows.
The dataset is split into batches of 30K entries with chain of thought(COT) reasoning and the answer. This can then be preprocessed and used for training any reasoning model.
Dataset Acknowledgment
This project processes data from the SynSQL-2.5M dataset by seeklhy, which is licensed under Apache 2.0. We acknowledge and thank the… See the full description on the dataset page: https://huggingface.co/datasets/ameet/deepsql_training.DeepSWEGym2-Ultra
Dataset Description
This dataset is an EXTREMELY filtered and deduplicated version of DeepSWE-Gym2-Edu, it aims to improve benchmark results on DeepSWE-style problems, benchmarks, and general coding skills.
It is specifically filtered for rows with complex/long code problems in the original datasets, having an average row size of 8.27MB, a total uncompressed size of 8.27GB, and a total of 1000 examples.
Dataset Details
Curated by: MoreThought
Funded by:… See the full description on the dataset page: https://huggingface.co/datasets/MoreThought/DeepSWEGym2-Ultra.deepseek-v4-pro-0813-agentic
DeepSeek-V4-Pro 0813 Agentic (DS4)
A standalone, verifiable-first agentic training corpus: 19,072 training traces
plus 2,135 held-out evaluation rows (validation 1,070 / test 1,065), generated by
DeepSeek-V4-Pro 0813 (deepseek-v4-pro-0813, official API, thinking mode) across 13 verifiable task families,
each row admitted only after passing a deterministic programmatic verifier. The corpus is
designed to be directly usable for SFT, GRPO/RLVR, and NeMo Gym / NeMo RL
(verified… See the full description on the dataset page: https://huggingface.co/datasets/r0b0tlab/deepseek-v4-pro-0813-agentic.math-code-science-deepseek-r1-en
R1 Dataset Collection
Aggregated high-quality English prompts and model-generated responses from DeepSeek R1 and DeepSeek R1-0528.
Dataset Summary
The R1 Dataset Collection combines multiple public DeepSeek-generated instruction-response corpora into a single, cleaned, English-only JSONL file. Each example consists of a <|user|> prompt and a <|assistant|> response in one "text" field. This release includes:
~21,000 examples from the DeepSeek-R1-0528 Distilled Custom… See the full description on the dataset page: https://huggingface.co/datasets/Hugodonotexit/math-code-science-deepseek-r1-en.DeepSWEGym2-Edu
Dataset Description
This dataset is a filtered and deduplicated version of a merge containing many high quality SWE datasets, it aims to improve benchmark results on DeepSWE-style problems, benchmarks, and general coding skills.
It is specifically filtered for rows with complex/long code problems in the original datasets, having an average row size of 291.74kb, a total uncompressed size of 14.93GB, and a total of 53649 examples.
Dataset Details
Curated by:… See the full description on the dataset page: https://huggingface.co/datasets/MoreThought/DeepSWEGym2-Edu.deepscaler-preview-verl
DeepScaleR-Preview VERL
📊 Dataset Summary
This dataset contains 35,789 mathematical reasoning problems in VERL format, processed from agentica-org/DeepScaleR-Preview-Dataset.
Key Features:
35,789 high-quality math problems
Converted to VERL format for reward modeling
Verified ground truth answers
Ready for reinforcement learning training
🔗 Source Dataset
Original Repository
Repository:… See the full description on the dataset page: https://huggingface.co/datasets/sungyub/deepscaler-preview-verl.DeepSWEGym2-Full
Dataset Description
This dataset is a merge containing many high quality SWE datasets, it aims to improve benchmark results on DeepSWE-style problems, benchmarks, and general coding skills.
It is NOT specifically filtered for rows with complex/long code problems in the original datasets, despite still having an average row size of 169.08kb, a total uncompressed size of 19.80GB, and a total of 122791 examples.
Dataset Details
Curated by: MoreThought
Funded by:… See the full description on the dataset page: https://huggingface.co/datasets/MoreThought/DeepSWEGym2-Full.Chinese-DeepSeek-R1-Distill-data-110k
中文基于满血DeepSeek-R1蒸馏数据集（Chinese-Data-Distill-From-R1）
🤗 Hugging Face | 🤖 ModelScope | 🚀 Github | 📑 Blog
注意：提供了直接SFT使用的版本，点击下载。将数据中的思考和答案整合成output字段，大部分SFT代码框架均可直接直接加载训练。
本数据集为中文开源蒸馏满血R1的数据集，数据集中不仅包含math数据，还包括大量的通用类型数据，总数量为110K。
为什么开源这个数据？
R1的效果十分强大，并且基于R1蒸馏数据SFT的小模型也展现出了强大的效果，但检索发现，大部分开源的R1蒸馏数据集均为英文数据集。 同时，R1的报告中展示，蒸馏模型中同时也使用了部分通用场景数据集。
为了帮助大家更好地复现R1蒸馏模型的效果，特此开源中文数据集。
该中文数据集中的数据分布如下：… See the full description on the dataset page: https://huggingface.co/datasets/Congliu/Chinese-DeepSeek-R1-Distill-data-110k.DeepSWEGym-Edu
Dataset Description
This dataset is a heavily filtered version of all the SWE-bench/SWE-smith-lang datasets (expect php) merged together (originally 88k rows total), it aims to improve benchmark results on DeepSWE-style problems, benchmarks, and general coding skills.
It is specifically filtered for rows with very complex/long code problems in the original datasets, having an average row size of 101.81kb, a total uncompressed size of 4.29GB, and 42529 examples total.… See the full description on the dataset page: https://huggingface.co/datasets/MoreThought/DeepSWEGym-Edu.DeepSWEGym-Full
Dataset Description
This dataset is a merged version of all the SWE-bench/SWE-smith-lang datasets (88k rows total), it aims to improve benchmark results on DeepSWE-style problems, benchmarks, and general coding skills.
It is NOT specifically filtered for rows with complex/long code problems in the original datasets, despite still having an average row size of 85.4kb, a total uncompressed size of 7.53GB, and 88130 examples total.
Dataset Details
Curated by:… See the full description on the dataset page: https://huggingface.co/datasets/MoreThought/DeepSWEGym-Full.Chinese-DeepSeek-R1-Distill-data-110k-SFT
中文基于满血DeepSeek-R1蒸馏数据集（Chinese-Data-Distill-From-R1）
🤗 Hugging Face | 🤖 ModelScope | 🚀 Github | 📑 Blog
注意：该版本为，可以直接SFT使用的版本，将原始数据中的思考和答案整合成output字段，大部分SFT代码框架均可直接直接加载训练。
本数据集为中文开源蒸馏满血R1的数据集，数据集中不仅包含math数据，还包括大量的通用类型数据，总数量为110K。
为什么开源这个数据？
R1的效果十分强大，并且基于R1蒸馏数据SFT的小模型也展现出了强大的效果，但检索发现，大部分开源的R1蒸馏数据集均为英文数据集。 同时，R1的报告中展示，蒸馏模型中同时也使用了部分通用场景数据集。
为了帮助大家更好地复现R1蒸馏模型的效果，特此开源中文数据集。该中文数据集中的数据分布如下：
Math：共计36568个样本，
Exam：共计2432个样本，
STEM：共计12648个样本，… See the full description on the dataset page: https://huggingface.co/datasets/Congliu/Chinese-DeepSeek-R1-Distill-data-110k-SFT.covid_qa_deepset
Dataset Card for COVID-QA
Dataset Summary
COVID-QA is a Question Answering dataset consisting of 2,019 question/answer pairs annotated by volunteer biomedical experts on scientific articles related to COVID-19.
A total of 147 scientific articles from the CORD-19 dataset were annotated by 15 experts.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
The text in the dataset is in English.
Dataset Structure
Data… See the full description on the dataset page: https://huggingface.co/datasets/deepset/covid_qa_deepset.DeepScholarBench
DeepScholarBench Dataset
A comprehensive dataset of academic papers with extracted related works sections and recovered citations, designed for training and evaluating research generation systems.
📊 Dataset Overview
This dataset contains 63 academic papers from ArXiv with their related works sections and 1630 recovered citations, providing a rich resource for research generation and citation analysis tasks.
🎯 Use Cases
Research Generation: Train models… See the full description on the dataset page: https://huggingface.co/datasets/deepscholar-bench/DeepScholarBench.minimax-m3-deepsearchqa-skill-eval
MiniMax M3 DeepSearchQA Skill Eval
Evaluates minimax/minimax-m3 on google/deepsearchqa using a Pi agent, You.com MCP tools, and a research skill optimized for this harness, model, and tool surface.
MiniMax M3 Medium Reasoning with the You.com research skill reached 74.85% adjusted F1 on DeepSearchQA, above the paper's GPT-5 High Reasoning F1 result. Public artifacts are available for inspection and reproduction.
Links
GitHub:… See the full description on the dataset page: https://huggingface.co/datasets/youdotcom/minimax-m3-deepsearchqa-skill-eval.DeepResearch-traj
DeepResearch-traj
Multi-seed deep research agent trajectories with per-question correctness labels and pass@k statistics, derived from OpenResearcher/OpenResearcher-Dataset.
Dataset Summary
This dataset contains 97,630 full agent trajectories across 6,102 unique research questions, each sampled under 16 different random seeds (42–57). Every trajectory is annotated with:
seed — which random seed produced this trajectory
correct — whether the model's final answer was… See the full description on the dataset page: https://huggingface.co/datasets/IPF/DeepResearch-traj.deepcontrol_output
DeepControl Output
This dataset contains trajectories running under the DeepControl inference pipeline across seven standard QA benchmarks.
DeepControl enables an LLM agent to actively regulate information acquisition during reasoning through (1) retrieval continuation control (when to keep searching), (2) granularity control (how much information to expand), and (3) annealed control training. Each record below is a full agent rollout: the model interleaves <think>, <search>… See the full description on the dataset page: https://huggingface.co/datasets/sxiong/deepcontrol_output.deepsearchqa
DeepSearchQA
A 900-prompt factuality benchmark from Google DeepMind, designed to evaluate agents on difficult multi-step information-seeking tasks across 17 different fields.
▶ Google DeepMind Release Blog Post▶ DeepSearchQA Leaderboard on Kaggle▶ Technical Report▶ Evaluation Starter Code
Benchmark
DeepSearchQA is a 900-prompt benchmark for evaluating agents on difficult multi-step information-seeking tasks across 17 different fields. Unlike traditional… See the full description on the dataset page: https://huggingface.co/datasets/Rendy45/deepsearchqa.salabs-stem-deep-reasoning-cot-v13
🧪 SALabs Multi-Domain STEM Deep Reasoning & Chain-of-Thought (CoT) Corpus (v13.0)
[!IMPORTANT]
💳 Click Here to Purchase Enterprise Commercial License ($2,500 USD) & Instant 31.7MB Master Archive DownloadInstant download of the full lossless master package containing all 1,816 JSONL reasoning records + 13 complete uncompressed text corpora (31.72 MB uncompressed total) + commercial license certificate.
🌟 Executive Summary
The SALabs STEM Deep Reasoning… See the full description on the dataset page: https://huggingface.co/datasets/suitai/salabs-stem-deep-reasoning-cot-v13.DeepSeek-R1-Distill-Qwen-1.5B-Self-CalibrationThis dataset contains data for the paper Efficient Test-Time Scaling via Self-Calibration.
We propose an efficient test-time scaling method by using model confidence for dynamically sampling adjustment, since confidence can be seen as an intrinsic measure that directly reflects model uncertainty on different tasks. For example, we can incorporate the model’s confidence into self-consistency by assigning each sampled response $y_i$ a confidence score $c_i$. Instead of treating all responses… See the full description on the dataset page: https://huggingface.co/datasets/HINT-lab/DeepSeek-R1-Distill-Qwen-1.5B-Self-Calibration.ldr-benchmarks
LDR Community Benchmarks (Leaderboards)
Aggregated leaderboards for Local Deep Research (LDR) community benchmark
runs against SimpleQA, BrowseComp, and xbench-DeepSearch.
👉 Submit results, read raw YAMLs, open PRs:
github.com/LearningCircuit/ldr-benchmarks
This Hugging Face dataset hosts only the aggregated CSV leaderboards.
It is regenerated automatically on every merge to main in the GitHub
repo above. Each CSV row represents one benchmark run (one strategy… See the full description on the dataset page: https://huggingface.co/datasets/local-deep-research/ldr-benchmarks.Deepseek-V4-Reasoning-Code-2500
DeepSeek Reasoning and Code Distillation Dataset
This dataset contains synthetic instruction-response examples generated from coding, reasoning, and math prompts. It was generated with enforce_distillable_text enabled using DeepSeek V4 Pro and DeepSeek V4 Flash through OpenRouter. It is intended for experimentation with supervised fine-tuning, response-style distillation, reasoning-format analysis, and code-assistant behavior research.
The dataset file is:
train.csv
It contains 2… See the full description on the dataset page: https://huggingface.co/datasets/Banaxi-Tech/Deepseek-V4-Reasoning-Code-2500.SGI-DeepResearch
Probing Scientific General Intelligence of LLMs with Scientist-Aligned Workflows
Welcome to the official repository for the SGI-Bench! 👏
Scientist-aligned benchmark for evaluating Scientific General Intelligence (SGI) across the full inquiry cycle: Deliberation, Conception, Action, and Perception. The benchmark spans 10 disciplines and more than 1,000 expert‑curated samples inspired by Science’s 125 Big Questions, with an agentic evaluation framework… See the full description on the dataset page: https://huggingface.co/datasets/InternScience/SGI-DeepResearch.DeepSeek-V4-Pro-Reasoning-8000x
DeepSeek-V4-Pro-Reasoning-8000x
This dataset contains 8,014 synthetic reasoning examples generated with DeepSeek V4 Pro through the DeepSeek API.
The release is branded as 8000x for readability, while the exact row count is 8,014.
This dataset is designed for supervised fine-tuning, reasoning distillation, and experimentation with long-form visible reasoning traces.
Dataset Summary
Release label: 8000x
Actual rows: 8,014
Teacher model: DeepSeek-V4-Pro… See the full description on the dataset page: https://huggingface.co/datasets/trjxter/DeepSeek-V4-Pro-Reasoning-8000x.DeepRethink
DeepRethink
Expanding AI thinking, more thinking needed
Thinking things and Contexts.hf-sanitized.hf-sanitized-BiKIfcWn9nbC8xiwxs370 .deeprethink-title { background-image: url('https://image.pollinations.ai/prompt/gradient%20dark%20and%20blue%20green%20bottom?width=1280&height=720&seed=2184&nologo=true&model=flux'); background-cover: bottom; -webkit-background-clip: text; background-clip: text; color: transparent; -webkit-text-fill-color: transparent; margin: 0 0 1rem 0; }… See the full description on the dataset page: https://huggingface.co/datasets/kulia-moon/DeepRethink.deepseek-r1-autonomous-math-logic-cot-2026
📐 Enterprise DeepSeek-R1 Autonomous Mathematical & Logic CoT SFT/DPO Dataset (2026)
High-precision multi-turn instruction tuning and preference optimization dataset with step-by-step hypothesis exploration, error discovery, and dynamic backtracking Chain-of-Thought (<thought>) reasoning trees for fine-tuning LLMs (DeepSeek-R1-Distill-Qwen, Qwen-2.5-Math, Llama-3.3, Mistral) into World-Class Olympiad Mathematicians and Formal Verification Agents.
📊 Dataset… See the full description on the dataset page: https://huggingface.co/datasets/beatsprom/deepseek-r1-autonomous-math-logic-cot-2026.DeepResearch-Bench-Multilingual
DeepResearch Bench Multilingual Prompts
This dataset provides prompt-level multilingual translations for the 100 research tasks used in muset-ai/DeepResearch-Bench-Dataset.
The translations cover eight languages:
en
zh
es
it
ar
bn
ja
el
What is included
This repository focuses on the benchmark prompts only.
On the Hugging Face Hub, the Dataset Viewer is configured with one default subset named all plus nine explicit subset configurations: source_prompt, en, zh, es… See the full description on the dataset page: https://huggingface.co/datasets/JRQi/DeepResearch-Bench-Multilingual.DeepScaleR-EasyThe easy part (pass_rate > 4/8) of DeepScaleR
Check https://wutaiqiang.github.io/project/Art for more details
Citation:
@inproceedings{wu2026art,
title={The Art of Efficient Reasoning: Data, Reward, and Optimization},
author={Taiqiang Wu and Zenan Xu and Bo Zhou and Ngai Wong},
year={2026},
url={https://arxiv.org/pdf/2602.20945}
}