datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
OpenThoughts-114k
[!NOTE]
We have released a paper for OpenThoughts! See our paper here.
Open-Thoughts-114k
Open synthetic reasoning dataset with 114k high-quality examples covering math, science, code, and puzzles!
Inspect the content with rich formatting with Curator Viewer.
Available Subsets
default subset containing ready-to-train data used to finetune the OpenThinker-7B and OpenThinker-32B models:
ds = load_dataset("open-thoughts/OpenThoughts-114k"… See the full description on the dataset page: https://huggingface.co/datasets/open-thoughts/OpenThoughts-114k.OpenThoughts3-1.2M
paper |
dataset |
model
[!NOTE]
We have released a paper for OpenThoughts! See our paper here.
OpenThoughts3-1.2M
Open-source state-of-the-art reasoning dataset with 1.2M rows. 🚀
OpenThoughts3-1.2M is the third iteration in our line of OpenThoughts datasets, building on our previous OpenThoughts-114k and OpenThoughts2-1M.
This time around, we scale even further and generate our dataset in a much more systematic way -- OpenThoughts3-1.2M is the result of a… See the full description on the dataset page: https://huggingface.co/datasets/open-thoughts/OpenThoughts3-1.2M.Mixture-of-Thoughts
Dataset summary
Mixture-of-Thoughts is a curated dataset of 350k verified reasoning traces distilled from DeepSeek-R1. The dataset spans tasks in mathematics, coding, and science, and is designed to teach language models to reason step-by-step. It was used in the Open R1 project to train OpenR1-Distill-7B, an SFT model that replicates the reasoning capabilities of deepseek-ai/DeepSeek-R1-Distill-Qwen-7B from the same base model.
To load the dataset, run:
from datasets import… See the full description on the dataset page: https://huggingface.co/datasets/open-r1/Mixture-of-Thoughts.TaskTrove
TaskTrove
v5.1 (current) — independent-review source retirement — moves 15 sources with majority or unanimous REJECT verdicts out of the default config and into deprecated/. Three blinded reviewers each sampled 10 tasks per source from all 50 v5.0 source-drop candidates, read the instructions and packaged tests, and issued independent KEEP or REJECT verdicts. The 15 retired sources received at least two REJECT votes. The active catalog changes from 93 sources and 1,674,033… See the full description on the dataset page: https://huggingface.co/datasets/open-thoughts/TaskTrove.AgentTrove
AgentTrove
AgentTrove is the largest open-source collection of agentic interaction traces to date, released by the OpenThoughts-Agent team. It contains 1,696,847 rows drawn from 219 source datasets spanning code repair, shell scripting, mathematical problem-solving, competitive programming, and general computer-use tasks.
At 1.7 million rows, AgentTrove is 4× the size of the Nemotron Terminal Corpus (430 K rows), the previous largest open-source agentic trace dataset.… See the full description on the dataset page: https://huggingface.co/datasets/open-thoughts/AgentTrove.OpenThoughts2-1M
[!NOTE]
We have released a paper for OpenThoughts! See our paper here.
OpenThoughts2-1M
Open synthetic reasoning dataset with 1M high-quality examples covering math, science, code, and puzzles!
OpenThoughts2-1M builds upon our previous OpenThoughts-114k dataset, augmenting it with existing datasets like OpenR1, as well as additional math and code reasoning data.
This dataset was used to train OpenThinker2-7B and OpenThinker2-32B.
Inspect the content with rich… See the full description on the dataset page: https://huggingface.co/datasets/open-thoughts/OpenThoughts2-1M.OpenThoughts-TB-dev
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RL dataset |
SFT model
RL model
OpenThoughts-TB-Dev
Dataset Description
OpenThoughts-TB-Dev is our development benchmark for evaluating agent models on terminal and shell-based tasks. This dataset was curated to measure the effectiveness of different data sources, teacher models, and curation approaches during the development of OpenThinker-Agent-v1. We used this benchmark to ablate over many different instruction generation… See the full description on the dataset page: https://huggingface.co/datasets/open-thoughts/OpenThoughts-TB-dev.OpenThoughts-TBLite
Blog Post |
GitHub |
Dev Set v1
OpenThoughts-TBLite
A Difficulty-Calibrated Benchmark for Building Terminal Agents
By OpenThoughts Agent team, Snorkel AI, Bespoke Labs
OpenThoughts-TBLite is a curated collection of 100 Terminal-Bench tasks that closely track TB2 performance, but run much faster. It's designed to be more informative during model development, making it ideal for debugging, iteration, and training ablations.
Dataset Description… See the full description on the dataset page: https://huggingface.co/datasets/open-thoughts/OpenThoughts-TBLite.OpenThoughts-TB-dev-v2
Blog Post |
GitHub |
Dev Set v1
OpenThoughts-TB-dev-v2
A Difficulty-Calibrated Benchmark for Building Terminal Agents
By OpenThoughts Agent team, Snorkel AI, Bespoke Labs
OpenThoughts-TB-dev-v2 is a curated collection of 100 Terminal-Bench tasks that closely track TB2 performance, but run much faster. It's designed to be more informative during model development, making it ideal for debugging, iteration, and training ablations.
Dataset Description… See the full description on the dataset page: https://huggingface.co/datasets/open-thoughts/OpenThoughts-TB-dev-v2.OpenThoughts-Agent-v1-SFT
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SFT dataset |
RL dataset |
SFT model |
RL model
OpenThinker-Agent-v1-SFT
OpenThoughts-Agent is an open-source effort to curate the best datasets for training agents. Our first release includes datasets, models and our research codebase.
OpenThinker-Agent-v1 is a model trained for agentic tasks such as Terminal-Bench 2.0 and SWE-Bench.
The OpenThinker-Agent-v1 model is post-trained from Qwen/Qwen3-8B.
It is SFT-ed on the OpenThoughts-Agent-v1-SFT dataset, then… See the full description on the dataset page: https://huggingface.co/datasets/open-thoughts/OpenThoughts-Agent-v1-SFT.OpenThoughts-Agent-SFT-100K
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Code |
Collection
OpenThoughts-Agent-SFT-100K
OpenThoughts-Agent is an open-source effort to curate the best datasets for training agents. Our release includes datasets, models and our research codebase.
OpenThoughts-Agent-SFT-100K is the 100,000-example point of the OpenThoughts-Agent SFT scaling ladder (sizes 316 / 1K / 3.16K / 10K / 31.6K / 100K). It contains (task, agent-trajectory) pairs used to fine-tune OpenThinkerAgent-8B-SFT-100K and… See the full description on the dataset page: https://huggingface.co/datasets/open-thoughts/OpenThoughts-Agent-SFT-100K.MiniMax-M2.1-Mixture-of-Thoughts
MiniMax-M2.1 Mixture of Thoughts
This dataset contains responses generated by MiniMax-M2.1 for user questions from the open-r1/Mixture-of-Thoughts dataset.
Dataset Description
The dataset captures both the extended thinking process and final answers from MiniMax-M2.1, with reasoning wrapped in <think> tags for easy separation.
Metric
Value
Examples
349,317
Total Tokens
4,052,592,552
Avg Tokens/Example
11,601
Source Dataset
Name:… See the full description on the dataset page: https://huggingface.co/datasets/PursuitOfDataScience/MiniMax-M2.1-Mixture-of-Thoughts.Polyglot-Thoughts-SFT-Collection
Polyglot Thoughts SFT Collection
Polyglot Thoughts SFT Collection is a large-scale supervised fine-tuning (SFT)
corpus for reasoning-oriented language models. It combines, filters, deduplicates,
and language-extends a broad set of public reasoning datasets into a single uniform
schema centred on chain-of-thought reasoning traces.
The final corpus contains 23,896,757 examples and roughly 123 billion tokens,
spanning six languages (English, German, French, Italian, Spanish… See the full description on the dataset page: https://huggingface.co/datasets/ahmad21omar/Polyglot-Thoughts-SFT-Collection.open-thoughts-4-math-qwen3-32b-annotated
Dataset Card for Open-Thoughts-4-Math-Qwen3-32B-Annotated
This dataset is the Qwen3-32B annotated version of mlfoundations-dev/hero_run_4_math curated by the
OpenThoughts4 team. We provide the responses from Qwen3-32B in the generated_text column. These samples were generated using temperature = 0.8 and max output tokens = 7,500.
We note that many of the responses are truncated, so use this dataset wisely!
Dataset Details
Dataset Description… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-math-qwen3-32b-annotated.open-thoughts-scienceopen_thoughts3_1.2m_annotated_Qwen3-8B_sft_packingOpenThoughts-Agent-v1-RL
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RL dataset |
SFT model |
RL model
OpenThoughts-Agent-v1-RL
A curated RL dataset of ~720 tasks with instructions, environments, and verifiers for agentic training.
OpenThoughts-Agent is an open-source effort to curate the best datasets for training agents. Our first release includes datasets, models and our research codebase;
OpenThinker-Agent-v1 is a model trained for agentic tasks such as Terminal-Bench 2.0 and SWE-Bench.
We built… See the full description on the dataset page: https://huggingface.co/datasets/open-thoughts/OpenThoughts-Agent-v1-RL.open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens-n8
Open Thoughts 4 - Math (Qwen3-32B, 32K tokens, n=8)
This dataset contains math reasoning problems with 8 independent responses generated by Qwen3-32B.
Overview
Source: marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens
Model: Qwen/Qwen3-32B
Temperature: 0.8
Max tokens: 32,768
Columns
Column
Description
instruction_seed
The math problem prompt
_source
Source dataset identifier
gpt41_mini_response
Reference response from… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens-n8.open_thoughts3_300k_annotated_Qwen3-32B_sft_packingopen-thoughts-4-30k-code-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8
Open Thoughts 4 - Code (Qwen3-30B-A3B-Thinking-2507, 32K tokens, n=8)
This dataset contains code reasoning problems with 8 independent responses generated by Qwen3-30B-A3B-Thinking-2507.
Overview
Source: marin-community/open-thoughts-4-30k-code-qwen3-32b-annotated (prompts only)
Model: Qwen/Qwen3-30B-A3B-Thinking-2507
Temperature: 0.8
Max tokens: 32,768
Columns
Column
Description
instruction_seed
The code problem prompt
_source
Source dataset… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-code-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8.open-thoughts-4-30k-math-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8
Open Thoughts 4 - Math (Qwen3-30B-A3B-Thinking-2507, 32K tokens, n=8)
This dataset contains math reasoning problems with 8 independent responses generated by Qwen3-30B-A3B-Thinking-2507.
Overview
Source: marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated (base prompts)
Model: Qwen/Qwen3-30B-A3B-Thinking-2507
Temperature: 0.8
Max tokens: 32,768
Columns
Column
Description
instruction_seed
The math problem prompt
_source
Source dataset… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8.open-thoughts-4-30k-math-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8-reformatted
Dataset Card for Open-Thoughts-4-30K-Math-Qwen3-30B-A3B-Thinking-2507-Annotated-32768-Tokens-N8-Reformatted
Overview
This dataset is a reformatted version of marin-community/open-thoughts-4-30k-math-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8. The original dataset contained 29,963 samples, each with 8 responses generated by the same model with different random seeds (stored in generated_text, generated_text2, ..., generated_text8 columns). This reformatted… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8-reformatted.open-thoughts-5k
open-thoughts-5k
A fixed 4,800-problem subset of siyanzhao/Openthoughts_math_30k_opsd
(29,434 rows), drawn once so that every run trains on exactly the same problems.
Why
Our training runs are 150 optimizer steps at 32 prompts per step — 4,800 examples. Loading the
full 29,434-row set and letting the dataloader take what it needs means each run sees a
different 4,800 problems. Two runs that differ only in one hyperparameter then also differ in
their training data… See the full description on the dataset page: https://huggingface.co/datasets/williamium/open-thoughts-5k.open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens-n8
Open Thoughts 4 - Math (Qwen3-4B, 32K tokens, n=8)
This dataset contains math reasoning problems with 8 independent responses generated by Qwen3-4B.
Overview
Source: marin-community/open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens (n=1 version with 1 response per prompt)
Model: Qwen/Qwen3-4B
Temperature: 0.8
Max tokens: 32,768
Columns
Column
Description
instruction_seed
The math problem prompt
_source
Source dataset identifier… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens-n8.r1-thoughtsMerges open-thoughts/OpenThoughts-114k, cognitivecomputations/dolphin-r1, bespokelabs/Bespoke-Stratos-17k
and includes the question and response length in Qwen 2.5 tokens.
import datasets
import transformers
def ot_map_format(example):
conversation = example['conversations']
assert type(conversation) == list
assert len(conversation) == 2
problem = conversation[0]['value'].strip()
solution = conversation[1]['value'].strip()
solution =… See the full description on the dataset page: https://huggingface.co/datasets/ricdomolm/r1-thoughts.Polyglot-Thoughts-RL-Collection
Polyglot Thoughts RL Collection
Polyglot Thoughts RL Collection is a large-scale, curated corpus for
reinforcement learning from verifiable rewards (RLVR) of reasoning-oriented
language models. It combines, filters, normalises, and deduplicates a broad set
of public RL datasets into a single uniform schema in which every row carries a
machine-verifiable ground-truth signal — math equivalence, code execution,
Prolog rule induction, schema validation, multiple-choice… See the full description on the dataset page: https://huggingface.co/datasets/ahmad21omar/Polyglot-Thoughts-RL-Collection.OpenThoughts-Agent-RL-5K
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Code |
Collection
OpenThoughts-Agent-RL-5K
OpenThoughts-Agent is an open-source effort to curate the best datasets for training agents. Our release includes datasets, models and our research codebase.
OpenThoughts-Agent-RL-5K is a 5,000-task reinforcement-learning task set used to RL-finetune the cold-start SFT model into the final agentic checkpoint. Unlike the SFT datasets, which hold full (task, trajectory) pairs, this dataset holds executable agentic… See the full description on the dataset page: https://huggingface.co/datasets/open-thoughts/OpenThoughts-Agent-RL-5K.open-thoughts-4-6865-math-kimi-k2pt5-annotated-32768-tokens-n8-reformatted
open-thoughts-4-6865-math-kimi-k2pt5-annotated-32768-tokens
Math reasoning responses generated by Kimi K2.5 (moonshotai/Kimi-K2.5) via a Together AI dedicated instance.
Overview
Total rows: 54,920
Unique prompts: 6,865 (each with 8 response annotations)
Source prompts: marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens-n8-reformatted
Generation model: moonshotai/Kimi-K2.5
Max tokens: 32,768
Temperature: 0.8
Tokenizer used for stats: Qwen/Qwen2.5-3B… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-6865-math-kimi-k2pt5-annotated-32768-tokens-n8-reformatted.open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens
Dataset Card for Open-Thoughts-4-30K-Math-Qwen3-4B-Annotated-32768-Tokens
Overview
This dataset is a variant of the OpenThoughts-4 30K math subset with responses generated by Qwen/Qwen3-4B using max output tokens = 32768, allowing for longer and more complete chain-of-thought reasoning.
Generation Details
Model: Qwen/Qwen3-4B
Temperature: 0.8
Max Output Tokens: 32768
Dataset Statistics
Number of Samples: 29,963
Split: train
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens.open-thoughts-4-30k-code-qwen3-32b-annotated-32768-tokens
Dataset Card for Open-Thoughts-4-30K-Code-Qwen3-32B-Annotated-32768-Tokens
Overview
This dataset is a variant of marin-community/open-thoughts-4-30k-code-qwen3-32b-annotated with an extended maximum sequence length. The responses in the generated_text column were generated with max output tokens = 32768 (instead of 7500 in the original dataset), allowing for longer and more complete chain-of-thought reasoning.
Generation Details
Model: Qwen/Qwen3-32B… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-code-qwen3-32b-annotated-32768-tokens.