Knowledge distillation is a common way to compress large models into smaller, faster ones, but the process itself can be expensive. A recent post on the Hugging Face blog, authored by MultiverseComputingCAI, argues that this cost can be brought down enough to make distillation practical at scale.
The post's central claim is that efficiency improvements can unlock broader adoption of distillation. Rather than treating it as a costly one-off step, the authors suggest it can become a routine part of model development.
Because the source is a single blog post, the analysis is limited to its own framing. No independent benchmarks or comparisons are provided in the source material, so the claims should be read as the authors' perspective rather than established industry consensus.