open-thoughts/OpenThinker-7B

Model

> [!NOTE]

139

20 commits

4 linked in READMEs

updated Jun 5, 2025

See the code

README

[!NOTE] We have released a paper for OpenThoughts! See our paper here.

OpenThinker-7B

This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct on the OpenThoughts-114k dataset dataset.

The dataset is derived by distilling DeepSeek-R1 using the data pipeline available on github. More info about the dataset can be found on the dataset card at OpenThoughts-114k dataset.

This model improves upon the Bespoke-Stratos-7B model, which used 17k examples (Bespoke-Stratos-17k dataset). The numbers reported in the table below are evaluated with our open-source tool Evalchemy.

AIME24MATH500GPQA-DiamondLCBv2 EasyLCBv2 MediumLCBv2 HardLCBv2 All
OpenThinker-7B31.383.042.475.328.66.539.9
Bespoke-Stratos-7B22.779.638.971.425.20.835.8
DeepSeek-R1-Distill-Qwen-7B6088.246.979.745.114.650.1
gpt-4o-05138.775.846.587.442.78.950.5
o1-mini6485.66092.874.739.872.8

We are fully open-source. Our model weights, datasets, data generation code, evaluation code, and training code are all publicly available.

Open WeightsOpen DataOpen Code
OpenThinker-7Bβœ…βœ…βœ…
Bespoke-Stratos-7Bβœ…βœ…βœ…
DeepSeek-R1-Distill-Qwen-7Bβœ…βŒβŒ
gpt-4o-0513❌❌❌
o1-mini❌❌❌

Intended uses & limitations

Apache 2.0 License

Training procedure

We used four 8xH100 nodes to train the model for 20 hours.

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1e-05
  • train_batch_size: 1
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 32
  • gradient_accumulation_steps: 3
  • total_train_batch_size: 96
  • total_eval_batch_size: 256
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3.0

Framework versions

  • Transformers 4.46.1
  • Pytorch 2.3.0
  • Datasets 3.1.0
  • Tokenizers 0.20.3

More info can be found in our repository: https://github.com/open-thoughts/open-thoughts.

Links

Citation

@misc{guha2025openthoughtsdatarecipesreasoning,
  title={OpenThoughts: Data Recipes for Reasoning Models}, 
  author={Etash Guha and Ryan Marten and Sedrick Keh and Negin Raoof and Georgios Smyrnis and Hritik Bansal and Marianna Nezhurina and Jean Mercat and Trung Vu and Zayne Sprague and Ashima Suvarna and Benjamin Feuer and Liangyu Chen and Zaid Khan and Eric Frankel and Sachin Grover and Caroline Choi and Niklas Muennighoff and Shiye Su and Wanjia Zhao and John Yang and Shreyas Pimpalgaonkar and Kartik Sharma and Charlie Cheng-Jie Ji and Yichuan Deng and Sarah Pratt and Vivek Ramanujan and Jon Saad-Falcon and Jeffrey Li and Achal Dave and Alon Albalak and Kushal Arora and Blake Wulfe and Chinmay Hegde and Greg Durrett and Sewoong Oh and Mohit Bansal and Saadia Gabriel and Aditya Grover and Kai-Wei Chang and Vaishaal Shankar and Aaron Gokaslan and Mike A. Merrill and Tatsunori Hashimoto and Yejin Choi and Jenia Jitsev and Reinhard Heckel and Maheswaran Sathiamoorthy and Alexandros G. Dimakis and Ludwig Schmidt},
  year={2025},
  eprint={2506.04178},
  archivePrefix={arXiv},
  primaryClass={cs.LG},
  url={https://arxiv.org/abs/2506.04178}, 
}
conversational
endpoints_compatible
full
generated_from_trainer
llama-factory
qwen2
safetensors
text-generation
text-generation-inference
transformers

Contributors

ryanmarten

16 commits

neginr

2 commits

sedrickkeh

2 commits

open-thoughts/OpenThinker-7B

Model

> [!NOTE]

139

20 commits

4 linked in READMEs

updated Jun 5, 2025

See the code

README

[!NOTE] We have released a paper for OpenThoughts! See our paper here.

OpenThinker-7B

This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct on the OpenThoughts-114k dataset dataset.

The dataset is derived by distilling DeepSeek-R1 using the data pipeline available on github. More info about the dataset can be found on the dataset card at OpenThoughts-114k dataset.

This model improves upon the Bespoke-Stratos-7B model, which used 17k examples (Bespoke-Stratos-17k dataset). The numbers reported in the table below are evaluated with our open-source tool Evalchemy.

AIME24MATH500GPQA-DiamondLCBv2 EasyLCBv2 MediumLCBv2 HardLCBv2 All
OpenThinker-7B31.383.042.475.328.66.539.9
Bespoke-Stratos-7B22.779.638.971.425.20.835.8
DeepSeek-R1-Distill-Qwen-7B6088.246.979.745.114.650.1
gpt-4o-05138.775.846.587.442.78.950.5
o1-mini6485.66092.874.739.872.8

We are fully open-source. Our model weights, datasets, data generation code, evaluation code, and training code are all publicly available.

Open WeightsOpen DataOpen Code
OpenThinker-7Bβœ…βœ…βœ…
Bespoke-Stratos-7Bβœ…βœ…βœ…
DeepSeek-R1-Distill-Qwen-7Bβœ…βŒβŒ
gpt-4o-0513❌❌❌
o1-mini❌❌❌

Intended uses & limitations

Apache 2.0 License

Training procedure

We used four 8xH100 nodes to train the model for 20 hours.

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1e-05
  • train_batch_size: 1
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 32
  • gradient_accumulation_steps: 3
  • total_train_batch_size: 96
  • total_eval_batch_size: 256
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3.0

Framework versions

  • Transformers 4.46.1
  • Pytorch 2.3.0
  • Datasets 3.1.0
  • Tokenizers 0.20.3

More info can be found in our repository: https://github.com/open-thoughts/open-thoughts.

Links

Citation

@misc{guha2025openthoughtsdatarecipesreasoning,
  title={OpenThoughts: Data Recipes for Reasoning Models}, 
  author={Etash Guha and Ryan Marten and Sedrick Keh and Negin Raoof and Georgios Smyrnis and Hritik Bansal and Marianna Nezhurina and Jean Mercat and Trung Vu and Zayne Sprague and Ashima Suvarna and Benjamin Feuer and Liangyu Chen and Zaid Khan and Eric Frankel and Sachin Grover and Caroline Choi and Niklas Muennighoff and Shiye Su and Wanjia Zhao and John Yang and Shreyas Pimpalgaonkar and Kartik Sharma and Charlie Cheng-Jie Ji and Yichuan Deng and Sarah Pratt and Vivek Ramanujan and Jon Saad-Falcon and Jeffrey Li and Achal Dave and Alon Albalak and Kushal Arora and Blake Wulfe and Chinmay Hegde and Greg Durrett and Sewoong Oh and Mohit Bansal and Saadia Gabriel and Aditya Grover and Kai-Wei Chang and Vaishaal Shankar and Aaron Gokaslan and Mike A. Merrill and Tatsunori Hashimoto and Yejin Choi and Jenia Jitsev and Reinhard Heckel and Maheswaran Sathiamoorthy and Alexandros G. Dimakis and Ludwig Schmidt},
  year={2025},
  eprint={2506.04178},
  archivePrefix={arXiv},
  primaryClass={cs.LG},
  url={https://arxiv.org/abs/2506.04178}, 
}
conversational
endpoints_compatible
full
generated_from_trainer
llama-factory
qwen2
safetensors
text-generation
text-generation-inference
transformers

Contributors

ryanmarten

16 commits

neginr

2 commits

sedrickkeh

2 commits