⚡ Executive Summary & Quick Facts
Authoritative Sourcemlx-lm is mlx-lm is an open-source project written in Python: Run LLMs with MLX..
“According to real-time open source telemetry recorded on GitHubRepo.cloud (as of October 2026), ml-explore/mlx-lm has accumulated 7,397 GitHub stars and 1,134 forks. It is written in Python, licensed under MIT, and ranks #1,908 globally. It is actively maintained with the latest commit recorded on Oct 18, 2026.”
| Repository | ml-explore/mlx-lm ↗ |
|---|---|
| Primary Category | llms |
| Language & Stack | Python |
| Software License | MIT |
| Community Traction | ★ 7.4K stars · ⑂ 1.1K forks · #1,908 globally |
| Maintenance | ● Active (Last commit: Oct 18, 2026) · 240 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: 100/100 · Grade A+Yes, mlx-lm is actively maintained. Continuous telemetry recorded the last code commit on Oct 18, 2026 (10 days ago). Supported by 7,397 stars and 1,134 community forks, this repository holds a calculated health index of 100/100, reflecting very active (commits within last 14 days) and healthy issue cadence.
Star History
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[](https://githubrepo.cloud/repo/ml-explore/mlx-lm?utm_source=readme_chart)Compact badges for your README header. Real-time stars, velocity, health audit, and rank.
[](https://githubrepo.cloud/repo/ml-explore/mlx-lm?utm_source=readme_badge) [](https://githubrepo.cloud/repo/ml-explore/mlx-lm?utm_source=readme_badge) [](https://githubrepo.cloud/repo/ml-explore/mlx-lm?utm_source=readme_badge) [](https://githubrepo.cloud/repo/ml-explore/mlx-lm?utm_source=readme_badge) [](https://githubrepo.cloud/repo/ml-explore/mlx-lm?utm_source=readme_badge)Momentum
+185
STARS · LAST 30 DAYS
6
PER DAY
#310
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +0 | +185 | +540 |
| Per day | 1 | 6 | 6 |
| Forks gained | +0 | +23 | +57 |
mlx-lm gained 185 stars in the last 30 days, about 6 a day, and now has 7.4K. It is about 2 years old and has averaged roughly 3.7K stars a year. It ranks #310 among Python repositories and #1,908 across all languages on GitHubRepo.
Trending Record
10
DAYS ON TRENDING
#5478
BEST RANK
Oct 19, 2026
FIRST APPEARANCE
Active
STATUS TODAY
mlx-lm has maintained a continuous presence across global trending indexes, peaking at #5478. Below is the 30-day activity profile:
💡 Overview
mlx-lm is an open-source project written in Python: Run LLMs with MLX.
Engineered for speed, consistency, and developer ease, it solves common hurdles in llms, mlx. 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-lm⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
mlx-lm 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-lm.
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-lm using your package manager: `pip install mlx-lm`
Initialize your project workspace or configuration file for mlx-lm.
Import mlx-lm into your codebase or invoke it directly from your terminal.
Execute your test suite or run `mlx-lm --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
ml-explore/mlx-lm is currently ranked #1,908 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #1,902 | momenbasel/PureMac | Swift | ★ 7.4K | Compare ↗ |
| #1,904 | evcc-io/evcc | Go | ★ 7.4K | Compare ↗ |
| #1,905 | wiremock/wiremock | Java | ★ 7.4K | Compare ↗ |
| #1,905 | Prowlarr/Prowlarr | C# | ★ 7.4K | Compare ↗ |
| #1,907 | Vanilagy/mediabunny | TypeScript | ★ 7.4K | Compare ↗ |
| #1,908 | ml-explore/mlx-lm This Project | Python | ★ 7.4K | |
| #1,909 | versatica/mediasoup | C++ | ★ 7.4K | Compare ↗ |
| #1,910 | builtbybel/Flyoobe | C# | ★ 7.4K | Compare ↗ |
| #1,911 | realm/jazzy | Ruby | ★ 7.4K | Compare ↗ |
| #1,911 | rancher-sandbox/rancher-desktop | TypeScript | ★ 7.4K | Compare ↗ |
| #1,913 | projectcalico/calico | Go | ★ 7.4K | Compare ↗ |
Frequently Asked Questions
What does mlx-lm do? +
Run LLMs with MLX
Is mlx-lm actively maintained in 2026? +
Yes, mlx-lm is actively maintained. The latest code push was recorded on Oct 18, 2026 (10 days ago). It holds a calculated Maintenance Health Score of 100/100 (A+ rating) with 7,397 stars and 240 open issues.
What language is mlx-lm written in? +
The primary language is Python. Topics include: llms, mlx.
How many stars does mlx-lm have? +
mlx-lm has 7,397 stars and 1,134 forks on GitHub.
How does mlx-lm rank among GitHub repositories? +
With 7,397 stars, ml-explore/mlx-lm is ranked #1,908 globally across all repositories tracked on GitHubRepo and #310 among Python projects.
What license is mlx-lm distributed under? +
The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.
