OpenThinker2-32B

This model is a fine-tuned version of Qwen/Qwen2.5-32B-Instruct on the OpenThoughts2-1M dataset.

The OpenThinker2-32B model is the highest performing open-data model. This model improves upon our previous OpenThinker-32B model, which was trained on 114k examples from OpenThoughts-114k. The numbers reported in the table below are evaluated with our open-source tool Evalchemy.

Model	Data	AIME24	AIME25	AMC23	MATH500	GPQA-D	LCBv2
OpenThinker2-32B	✅	76.7	58.7	94.0	90.8	64.1	72.5
OpenThinker-32B	✅	68.0	49.3	95.5	90.6	63.5	68.6
DeepSeek-R1-Distill-Qwen-32B	❌	74.7	50.0	96.5	90.0	65.8	72.3
Light-R1-32B	✅	74.7	58.0	96.0	90.4	62.0	56.0
S1.1-32B	✅	59.3	42.7	91.5	87.4	62.0	58.7

Data

This model was trained on the OpenThoughts2-1M dataset.

The OpenThoughts2-1M dataset was constructed by augmenting OpenThoughts-114k with existing datasets like OpenR1, as well as additional math and code reasoning data. We generate the additional math and code data by ablating over 26 different question generation methodologies and sampling from the highest performing ones.

See the OpenThoughts2-1M dataset page or our blog post for additional information.

Intended uses & limitations

Apache 2.0 License

Training procedure

We used 128 4xA100 nodes to train the model for 50 hours.

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 8e-05
• seed: 42
• distributed_type: multi-GPU
• num_devices: 512
• gradient_accumulation_steps: 1
• total_train_batch_size: 512
• 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: 5.0

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.

Citation

@misc{openthoughts,
  author = {Team, OpenThoughts},
  month = jan,
  title = {{Open Thoughts}},
  howpublished = {https://open-thoughts.ai},
  year = {2025}
}

Links

• 📊 OpenThoughts2 and OpenThinker2 Blog Post
• 💻 Open Thoughts GitHub Repository
• 🧠 OpenThoughts2-1M dataset
• 🤖 OpenThinker2-7B model
• 🤖 OpenThinker2-32B model - this model.