Neywa-Labs/mlx-vlm
MLX-VLM is a package for inference and fine-tuning of Vision Language Models (VLMs) on your Mac using MLX.
⚡ Executive Summary & Quick Facts
Authoritative Sourcemlx-vlm is mlx-vlm is an open-source project written in Python: MLX-VLM is a package for inference and fine-tuning of Vision Language Models (VLMs) on your Mac using MLX..
“According to real-time open source telemetry recorded on GitHubRepo.cloud (as of November 2026), Neywa-Labs/mlx-vlm has accumulated 5,838 GitHub stars and 888 forks. It is written in Python, licensed under MIT, and ranks #2,640 globally. It is actively maintained with the latest commit recorded on Nov 12, 2026.”
| Repository | Neywa-Labs/mlx-vlm ↗ |
|---|---|
| Primary Category | apple silicon |
| Language & Stack | Python |
| Software License | MIT |
| Community Traction | ★ 5.8K stars · ⑂ 888 forks · #2,640 globally |
| Maintenance | ● Active (Last commit: Nov 12, 2026) · 266 open issues |
| Target Audience | Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads. |
🛡️ Repository Maintenance & Health Audit (2026)
Health Score: 92/100 · Grade AYes, mlx-vlm is actively maintained. Continuous telemetry recorded the last code commit on Nov 12, 2026 (1 days ago). Supported by 5,838 stars and 888 community forks, this repository holds a calculated health index of 92/100, reflecting very active (commits within last 14 days) and active community feedback (266 open).
Star History
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+276
STARS · LAST 30 DAYS
9
PER DAY
#420
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +65 | +276 | +810 |
| Per day | 9 | 9 | 9 |
| Forks gained | +9 | +77 | +44 |
mlx-vlm gained 276 stars in the last 30 days, about 9 a day, and now has 5.8K. It is about 3 years old and has averaged roughly 1.9K stars a year. It ranks #420 among Python repositories and #2,640 across all languages on GitHubRepo.
Trending Record
42
DAYS ON TRENDING
#568
BEST RANK
Sep 26, 2026
FIRST APPEARANCE
Active
STATUS TODAY
mlx-vlm has maintained a continuous presence across global trending indexes, peaking at #568. Below is the 30-day activity profile:
💡 Overview
mlx-vlm is an open-source project written in Python: MLX-VLM is a package for inference and fine-tuning of Vision Language Models (VLMs) on your Mac using MLX.
Engineered for speed, consistency, and developer ease, it solves common hurdles in apple-silicon, florence2, idefics. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Python for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ pip install mlx-vlm⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
mlx-vlm coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with mlx-vlm.
Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.
Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.
Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.
🚀 Getting Started
Install mlx-vlm using your package manager: `pip install mlx-vlm`
Initialize your project workspace or configuration file for mlx-vlm.
Import mlx-vlm into your codebase or invoke it directly from your terminal.
Execute your test suite or run `mlx-vlm --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
Neywa-Labs/mlx-vlm is currently ranked #2,640 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
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| #2,640 | Neywa-Labs/mlx-vlm This Project | Python | ★ 5.8K | |
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Frequently Asked Questions
What does mlx-vlm do? +
MLX-VLM is a package for inference and fine-tuning of Vision Language Models (VLMs) on your Mac using MLX.
Is mlx-vlm actively maintained in 2026? +
Yes, mlx-vlm is actively maintained. The latest code push was recorded on Nov 12, 2026 (1 days ago). It holds a calculated Maintenance Health Score of 92/100 (A rating) with 5,838 stars and 266 open issues.
What language is mlx-vlm written in? +
The primary language is Python. Topics include: apple-silicon, florence2, idefics, llava, llm.
How many stars does mlx-vlm have? +
mlx-vlm has 5,838 stars and 888 forks on GitHub.
How does mlx-vlm rank among GitHub repositories? +
With 5,838 stars, Neywa-Labs/mlx-vlm is ranked #2,640 globally across all repositories tracked on GitHubRepo and #420 among Python projects.
What license is mlx-vlm distributed under? +
The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.
