title: OpenThoughts: Data Recipes for Reasoning Models
summary: Reasoning models have made rapid progress on many benchmarks involving math,
  code, and science. Yet, there are still many open questions about the best
  training recipes for reasoning since state-of-the-art models often rely on
  proprietary datasets with little to no public information available. To address
  this, the goal of the OpenThoughts project is to create open-source datasets
  for training reasoning models. After initial explorations, our OpenThoughts2-1M
  dataset led to OpenThinker2-32B, the first model trained on public reasoning
  data to match DeepSeek-R1-Distill-32B on standard reasoning benchmarks such as
  AIME and LiveCodeBench. We then improve our dataset further by systematically
  investigating each step of our data generation pipeline with 1,000+ controlled
  experiments, which led to OpenThoughts3. Scaling the pipeline to 1.2M examples
  and using QwQ-32B as teacher yields our OpenThinker3-7B model, which achieves
  state-of-the-art results: 53% on AIME 2025, 51% on LiveCodeBench 06/24-01/25,
  and 54% on GPQA Diamond. All of our datasets and models are available on
  https://openthoughts.ai.
paper_authors._id: 68417762d777f13c594dd03c
paper_authors.name: Etash Guha
paper_authors._id: 68417762d777f13c594dd03d
paper_authors.name: Ryan Marten
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-06-07T05:49:20.703Z
paper_authors._id: 626c182a030a6e7363b6fe0a
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/626c182a030a6e7363b6fe0a/NaMcIOPVgJ6JFt8fojZWU.jpeg
paper_authors.fullname: Ryan Marten
paper_authors.type: user
paper_authors.user: ryanmarten
paper_authors._id: 68417762d777f13c594dd03e
paper_authors.name: Sedrick Keh
paper_authors._id: 68417762d777f13c594dd03f
paper_authors.name: Negin Raoof
paper_authors._id: 68417762d777f13c594dd040
paper_authors.name: Georgios Smyrnis
paper_authors._id: 68417762d777f13c594dd041
paper_authors.name: Hritik Bansal
paper_authors._id: 68417762d777f13c594dd042
paper_authors.name: Marianna Nezhurina
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-06-07T05:49:22.779Z
paper_authors._id: 62500f361684e0335e527bc6
paper_authors.avatarUrl: /avatars/8d2bc4c9cfa8ea82049196431cc3ebea.svg
paper_authors.fullname: Marianna Nezhurina
paper_authors.type: user
paper_authors.user: marianna13
paper_authors._id: 68417762d777f13c594dd043
paper_authors.name: Jean Mercat
paper_authors._id: 68417762d777f13c594dd044
paper_authors.name: Trung Vu
paper_authors._id: 68417762d777f13c594dd045
paper_authors.name: Zayne Sprague
paper_authors._id: 68417762d777f13c594dd046
paper_authors.name: Ashima Suvarna
paper_authors._id: 68417762d777f13c594dd047
paper_authors.name: Benjamin Feuer
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-06-07T05:49:16.121Z
paper_authors._id: 62f7f4efe7c1c9bf10c81465
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/62f7f4efe7c1c9bf10c81465/AYlOg0fkP1o4GAP-8Y3xt.jpeg
paper_authors.fullname: Benjamin Feuer
paper_authors.type: user
paper_authors.user: penfever
paper_authors._id: 68417762d777f13c594dd048
paper_authors.name: Liangyu Chen
paper_authors._id: 68417762d777f13c594dd049
paper_authors.name: Zaid Khan
paper_authors._id: 68417762d777f13c594dd04a
paper_authors.name: Eric Frankel
paper_authors._id: 68417762d777f13c594dd04b
paper_authors.name: Sachin Grover
paper_authors._id: 68417762d777f13c594dd04c
paper_authors.name: Caroline Choi
paper_authors._id: 68417762d777f13c594dd04d
paper_authors.name: Niklas Muennighoff
paper_authors._id: 68417762d777f13c594dd04e
paper_authors.name: Shiye Su
paper_authors._id: 68417762d777f13c594dd04f
paper_authors.name: Wanjia Zhao
paper_authors._id: 68417762d777f13c594dd050
paper_authors.name: John Yang
paper_authors._id: 68417762d777f13c594dd051
paper_authors.name: Shreyas Pimpalgaonkar
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-06-06T07:41:50.414Z
paper_authors._id: 6444e4417a7b94ddc2d14e1d
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/6444e4417a7b94ddc2d14e1d/kC9bUAHujBf2XQs1c2QfS.png
paper_authors.fullname: Shreyas Pimpalgaonkar
paper_authors.type: user
paper_authors.user: pimpalgaonkar
paper_authors._id: 68417762d777f13c594dd052
paper_authors.name: Kartik Sharma
paper_authors._id: 68417762d777f13c594dd053
paper_authors.name: Charlie Cheng-Jie Ji
paper_authors._id: 68417762d777f13c594dd054
paper_authors.name: Yichuan Deng
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-06-06T07:41:52.871Z
paper_authors._id: 63f39ca90be81bdc5d94acc5
paper_authors.avatarUrl: /avatars/2eb069023671d8a9c118dd3c771d2d74.svg
paper_authors.fullname: Ethan Deng
paper_authors.type: user
paper_authors.user: SGEthan
paper_authors._id: 68417762d777f13c594dd055
paper_authors.name: Sarah Pratt
paper_authors._id: 68417762d777f13c594dd056
paper_authors.name: Vivek Ramanujan
paper_authors._id: 68417762d777f13c594dd057
paper_authors.name: Jon Saad-Falcon
paper_authors._id: 68417762d777f13c594dd058
paper_authors.name: Jeffrey Li
paper_authors._id: 68417762d777f13c594dd059
paper_authors.name: Achal Dave
paper_authors._id: 68417762d777f13c594dd05a
paper_authors.name: Alon Albalak
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-06-07T05:49:18.246Z
paper_authors._id: 611a7ec4289467cafea62d13
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/611a7ec4289467cafea62d13/pck-0fmPQkoU7yzh6-WoL.jpeg
paper_authors.fullname: Alon Albalak
paper_authors.type: user
paper_authors.user: alon-albalak
paper_authors._id: 68417762d777f13c594dd05b
paper_authors.name: Kushal Arora
paper_authors._id: 68417762d777f13c594dd05c
paper_authors.name: Blake Wulfe
paper_authors._id: 68417762d777f13c594dd05d
paper_authors.name: Chinmay Hegde
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-06-07T05:49:13.873Z
paper_authors._id: 631620f6894404e25068856f
paper_authors.avatarUrl: /avatars/52c30caa0ee11347f82420a14ec19996.svg
paper_authors.fullname: Chinmay Hegde
paper_authors.type: user
paper_authors.user: chegde
paper_authors._id: 68417762d777f13c594dd05e
paper_authors.name: Greg Durrett
paper_authors._id: 68417762d777f13c594dd05f
paper_authors.name: Sewoong Oh
paper_authors._id: 68417762d777f13c594dd060
paper_authors.name: Mohit Bansal
paper_authors._id: 68417762d777f13c594dd061
paper_authors.name: Saadia Gabriel
paper_authors._id: 68417762d777f13c594dd062
paper_authors.name: Aditya Grover
paper_authors._id: 68417762d777f13c594dd063
paper_authors.name: Kai-Wei Chang
paper_authors._id: 68417762d777f13c594dd064
paper_authors.name: Vaishaal Shankar
paper_authors._id: 68417762d777f13c594dd065
paper_authors.name: Aaron Gokaslan
paper_authors._id: 68417762d777f13c594dd066
paper_authors.name: Mike A. Merrill
paper_authors._id: 68417762d777f13c594dd067
paper_authors.name: Tatsunori Hashimoto
paper_authors._id: 68417762d777f13c594dd068
paper_authors.name: Yejin Choi
paper_authors._id: 68417762d777f13c594dd069
paper_authors.name: Jenia Jitsev
paper_authors._id: 68417762d777f13c594dd06a
paper_authors.name: Reinhard Heckel
paper_authors._id: 68417762d777f13c594dd06b
paper_authors.name: Maheswaran Sathiamoorthy
paper_authors._id: 68417762d777f13c594dd06c
paper_authors.name: Alexandros G. Dimakis
paper_authors._id: 68417762d777f13c594dd06d
paper_authors.name: Ludwig Schmidt
paper_title: OpenThoughts: Data Recipes for Reasoning Models
paper_summary: Reasoning models have made rapid progress on many benchmarks involving math,
  code, and science. Yet, there are still many open questions about the best
  training recipes for reasoning since state-of-the-art models often rely on
  proprietary datasets with little to no public information available. To address
  this, the goal of the OpenThoughts project is to create open-source datasets
  for training reasoning models. After initial explorations, our OpenThoughts2-1M
  dataset led to OpenThinker2-32B, the first model trained on public reasoning
  data to match DeepSeek-R1-Distill-32B on standard reasoning benchmarks such as
  AIME and LiveCodeBench. We then improve our dataset further by systematically
  investigating each step of our data generation pipeline with 1,000+ controlled
  experiments, which led to OpenThoughts3. Scaling the pipeline to 1.2M examples
  and using QwQ-32B as teacher yields our OpenThinker3-7B model, which achieves
  state-of-the-art results: 53% on AIME 2025, 51% on LiveCodeBench 06/24-01/25,
  and 54% on GPQA Diamond. All of our datasets and models are available on
  https://openthoughts.ai.
paper_ai_summary: The OpenThoughts project created open-source datasets leading to reasoning models that match or exceed state-of-the-art benchmarks in math, code, and science.
paper_ai_keywords: reasoning models OpenThoughts project OpenThoughts2-1M OpenThinker2-32B DeepSeek-R1-Distill-32B standard reasoning benchmarks AIME LiveCodeBench OpenThoughts3 OpenThinker3-7B GPQA Diamond