DistilKitPlus, a distillation framework between any LLMs
Over the past few months, I have built a distillation toolkit that supports cross-tokenizer distillation (e.g., distilling from LLaMA to Qwen vocab, or others). This approach has worked well on reasoning datasets like AIME, and we’ve validated on models like Phi and Qwen. We’ve also integrated Modal for quick deployment (with $30/month credits to try it out). Would love any feedback! GitHub: https://github.com/agokrani/distillKitPlus Docs: https://distillkitplus.mintlify.app/
In plain words
DistilKitPlus is a framework that distills knowledge from one large language model into another, even when they use different tokenizers. It enables cross-model distillation—for example, transferring knowledge from LLaMA to Qwen—and has shown effectiveness on reasoning tasks like AIME. The toolkit has been validated with models including Phi and Qwen, and includes integration with Modal for straightforward deployment. It is designed for machine learning engineers working with language model optimization.
written from the facts on this page · September 2026
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