Sky-T1-32B-Flash

Model Details

Model Description

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This is a 32B reasoning model preference optimized on top of Sky-T1-32B-Preview to significantly reduce generation lengths while maintaining accuracy. The performance is on par with o1-preview model in both math and coding, while reducing generation lengths by up to 57% relative to Sky-T1-32B-Preview. Please see our blog post for more details.

• Developed by: NovaSky Team from Sky Computing Lab at UC Berkeley.

Training Details

Training Data

10K preference pairs in math and coding domains, generated by Sky-T1-32B-Preview.

Training Procedure

We perform Simple Policy Optimization (SimPO) with a batch size of 96, learning rate of 5e-7, gamma of 0.3, and beta of 2.0.

Speeds

We use Llama-Factory for training. On 8xH100, the SimPO training takes ~2.5 hours with DeepSpeed Zero-3 Offload.

Evaluation

Acknowledgement

We would like to thanks the compute resources from Lambda Lab and AnyScale.

License

Apache-2.0

Citation

Please considering citing our blog post if you found it useful for your research. Thank you!

@misc{reduce_overthinking_2025,
  author       = {NovaSky Team},
  title        = {Think Less, Achieve More: Cut Reasoning Costs by 50% Without Sacrificing Accuracy},
  howpublished = {https://novasky-ai.github.io/posts/reduce-overthinking},
  note         = {Accessed: 2025-01-23},
  year         = {2025}
}