## Qwen3-14B: A Smaller Model for Security A cybersecurity expert has demonstrated how fine-tuning a smaller language model can lead to significant improvements in specific areas. Using 10,000 traces derived from DeepSeek, the Qwen3-14B model showed a 20% increase in a custom security benchmark. ## Knowledge Distillation: An Effective Strategy The fine-tuning was performed to improve the ability to detect bugs and vulnerabilities in code. The author points out that while larger models (frontier models) offer superior performance, their prohibitive cost prevents their use on large codebases. Distilling specific skills into smaller models is therefore a viable alternative to reduce costs while maintaining a good level of effectiveness. ## Availability and Future Developments The fine-tuned model is available on Hugging Face for those who want to test it. A GGUF version is also planned for release. This work highlights the potential of fine-tuning to adapt language models to specific tasks, making them more accessible and affordable for a wide range of applications.