April 2026: Fixed a PromptTrie off-by-one bug in ml-explore/mlx-lm and strengthened cache reliability. The change corrects pruning of immediate prefixes and adds tests to validate cache handling for empty tokens and immediate prefixes, reducing risk of incorrect pruning in production. This work improves correctness of prompt pruning, reliability of downstream model outputs, and maintainability through targeted tests and clear commit traceability.

March 2026: Delivered a targeted documentation improvement for ml-explore/mlx that simplifies PyTorch tensor to MLX array conversion by removing the need for intermediate NumPy arrays. This enhancement reduces setup friction and accelerates experimentation for users integrating MLX with PyTorch. The change is tracked under commit 1d44d913e63874e62527ca042dd6589fe5ad4fc1 with message “docs: fix PyTorch to MLX conversion example (#3265)”. No major bugs were reported or fixed in ml-explore/mlx this month. Overall, the work strengthens developer experience, shortens onboarding time, and improves interoperability between PyTorch and MLX.