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jundot / omlx

LLM inference server with continuous batching & SSD caching for Apple Silicon — managed from the macOS menu bar

Why this job: says: inference server, llm inference; topics: apple-silicon, mlx

oMLX Admin Dashboard

What it does

  • Hot tier (RAM). Frequently accessed blocks stay in memory for fast access.
  • Cold tier (SSD). When the hot cache fills up, blocks are offloaded to SSD in safetensors format. On the next request with a matching prefix, they're restored from disk instead of recomputed from scratch - even after a server restart.
  • LRU eviction. Least-recently-used models are evicted automatically when memory runs low.
  • Manual load/unload. Interactive status badges in the admin panel let you load or unload models on demand.
  • Model pinning. Pin frequently used models to keep them always loaded.

Get started

No single install command. Read the steps in the README (opens in new tab)

Maintenance
Active
Last commit 4 days ago
Stars
23,475
+198 this week
Licence
Apache-2.0
Allows business use
Downloads for
Mac
From the latest release
Latest version
v0.7.4.dev1
Released 5 days ago
Built with
Python
81% of the code

Is it looked after?

Contributors
27
Last 90 days
Issues
86% closed
333 still open
Pull requests
1,288 merged
204 waiting
Releases
137
30+ in the last year

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More: download files, languages, topics and project record

Download files, v0.7.4.dev1

  • Mac5 files, 9,832 downloads

All files on GitHub (opens in new tab)

Languages

  • Python 81%
  • Swift 8%
  • HTML 5%
  • JavaScript 2%

Topics

  • apple-silicon
  • inference-server
  • llm
  • macos
  • mlx
  • openai-api

Project record

  • JobLocal LLMs
  • StatusFeatured
  • Commits3,637
  • Forks2,113
  • Watching114
  • Stars in 28 days+811
  • CreatedFeb 13, 2026
  • First seen by usNov 7, 2026
  • CheckedNov 9, 2026

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