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MLX VLM Check

Lightweight CLI to run and benchmark MLX-compatible Vision-Language Models (VLMs) on Apple Silicon. Produces HTML/Markdown/gallery Markdown/TSV/JSONL reports and captures performance metrics (tokens/sec, memory, timings).

Note

This tool runs MLX-format Vision-Language Models hosted on the Hugging Face Hub. By default it runs all models found in your local HF cache (use --models to specify explicit model IDs).

Quick Start (fast path)

# Create the recommended conda environment and install runtime dependencies
bash src/tools/setup_conda_env.sh
conda activate mlx-vlm
make install

# Run all models against a folder (auto-selects most recent image) using the default built in prompt
python -m check_models --folder ~/Pictures/Processed

# Run them on a single image
python -m check_models --image /path/to/photo.jpg

First successful run (example)

python -m check_models --image ~/Pictures/sample.jpg

Expected outputs (default location: src/output/):

  • results.html
  • results.md
  • model_gallery.md
  • results.tsv
  • results.jsonl
  • results.history.jsonl
  • diagnostics.md (only when failures/harness issues are detected)
  • check_models.log
  • environment.log

Why use it (short)

  • Batch run multiple models against an image.
  • Standardized metrics + rich reports for easy comparison and qualitative review.
  • Robust error handling and metadata-aware prompts.

Documentation (full details)

Common Make Commands

make install   # install runtime dependencies
make dev       # install dev dependencies (dev + extras + torch)
make test      # run test suite
make quality   # run full gate (ruff + mypy + ty + pyrefly + pytest + shellcheck + markdownlint)

Tip

Platform: macOS with Apple Silicon is required. Python: 3.13+ is recommended and tested.

Ecosystem (quick links)

  • MLX: Array framework for Apple Silicon.
  • MLX VLM: Underlying VLM runtime.
  • Hugging Face Hub: Model source (look for mlx-community or mlx tags).

License: See the LICENSE file.

About

This repository provides a python script for running Vision Language Models via mlx-vlm

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