Mlx Vlm is used in Python projects. MLX-VLM is a package for inference and fine-tuning of Vision Language Models (VLMs) and Omni Models (VLMs with audio and video support) on your Mac using MLX. It has 15 direct runtime dependencies. Check its dependency graph on PyDeps to understand the full transitive dependency tree, reverse dependents, known CVEs, and license compatibility before installing.
MLX-VLM is a package for inference and fine-tuning of Vision Language Models (VLMs) and Omni Models (VLMs with audio and video support) on your Mac usin...
mlx-vlm declares 15 direct runtime dependencies on PyPI. Each one is resolved into the full dependency tree below:
Beyond its direct dependencies, mlx-vlm can pull in further packages through its dependency tree. PyDeps resolves the entire chain from PyPI and deps.dev so you can see every transitive (nested) dependency of mlx-vlm, expand any node on demand, and understand the full set of code that ships when you run pip install mlx-vlm.
PyDeps checks mlx-vlm and every package in its dependency tree against the OSV vulnerability database in real time. For each CVE you can see the severity, the affected version ranges, and the first fixed version, so you know exactly which mlx-vlm version is safe to install before you ship.
mlx-vlm is distributed under the MIT license. PyDeps also shows the license of every dependency in the tree so you can audit license compatibility across your whole mlx-vlm install, not just the top-level package.
Install from PyPI with pip install mlx-vlm. For offline or air-gapped environments, PyDeps can download mlx-vlm together with every resolved dependency as wheel files in a single bundle, matched to your target Python version and operating system.
Switch to the dependents view to see the reverse dependencies of mlx-vlm — the PyPI packages that list mlx-vlm as a requirement. Reverse dependencies are a strong signal of how widely a package is trusted and how disruptive a breaking change would be.