What is the primary benefit of oMLX for coding agents?

It uses paged SSD KV caching to persist previously seen prefixes, which can cut time-to-first-token from 30-90 seconds down to under five seconds for long-context coding agents.

Which operating systems and hardware does oMLX support?

oMLX is exclusively for Apple Silicon Macs running macOS 15 or later. It does not support Linux, Windows, or NVIDIA hardware.

Does oMLX support standard API endpoints for integration?

Yes, it exposes both OpenAI-compatible /v1/chat/completions and a native Anthropic /v1/messages endpoint, along with a one-click config generator for downstream tools.

Is oMLX free to use and what is its license?

oMLX is free to download as a DMG or build from source and is released under the Apache 2.0 open-source license.

Can oMLX host multiple models simultaneously?

Yes, it supports multi-model hosting with LRU eviction for LLMs, VLMs, embeddings, and rerankers, and can reuse an existing LM Studio model directory.

oMLX

Native macOS LLM inference server built on MLX, with paged SSD KV caching for Apple Silicon agents.

Free· Free, Apache 2.0 open sourceCodingMulti-model (Qwen, Llama, Mistral, Gemma, DeepSeek, MiniMax, GLM)7.5 / 10

Visit website →

In short

oMLX is a native macOS inference server built on MLX that optimizes local LLM performance for coding agents. It features paged SSD KV caching to reduce time-to-first-token and supports OpenAI-compatible APIs. It is ideal for developers running agentic tools on M-series Macs.

Best for

Pick oMLX if you run Claude Code, Cursor or other long-context coding agents locally on a beefy Apple Silicon Mac and want sub-5s TTFT.

Skip if

Skip it if you are on Linux, Windows, NVIDIA, or just want a hosted API - oMLX is Apple Silicon-only and you bring the hardware.

oMLX is a native macOS inference server built on Apple's MLX framework, packaged as a signed menu-bar app with a web dashboard. Its headline trick is paged SSD KV caching: a two-tier hot-RAM / cold-SSD architecture in safetensors format that persists previously seen prefixes across requests and even server restarts, so coding agents on long contexts cut TTFT from the typical 30-90 seconds you see in Ollama or LM Studio down to under five seconds. It also adds continuous batching via mlx-lm's BatchGenerator (up to ~4.14x speedup at 8x concurrency) and multi-model hosting with LRU eviction for LLMs, VLMs, embeddings and rerankers loaded at once.

The target user is obvious: developers running Claude Code, Cursor, OpenClaw or other agentic coding tools locally on an M-series Mac (ideally an M3 Ultra, though M1+/macOS 15+/64GB is the realistic floor). It exposes both OpenAI-compatible /v1/chat/completions and a native Anthropic /v1/messages endpoint, with a one-click config generator that emits the exact CLI command for each downstream tool. Tool calling is broad - JSON, Qwen, Gemma, GLM, MiniMax formats plus MCP - and reasoning models get automatic <think> tag handling.

oMLX is Apache 2.0 and free to download as a DMG or build from source; there is no paid tier advertised. It reuses an existing LM Studio model directory and has a built-in HuggingFace downloader, so onboarding is painless if you already run local models. Caveat: it is Apple Silicon only - no Linux, no Windows, no NVIDIA - and the published benchmarks are skewed toward a 512GB M3 Ultra, which is not what most readers actually own.

Editor's take

The SSD-paged KV cache is the real story here - it directly fixes the recompute-on-context-shift pain that makes Ollama and LM Studio painful for agents. If you have an M-series Mac with 64GB+ and you live in Claude Code, oMLX is the most credible local backend we have seen this year. Just temper your expectations against the M3 Ultra benchmarks.

— The AI Tool Bible editorial team

Pros

✅ Paged SSD KV cache slashes agent TTFT from 30-90s to <5s on long contexts
✅ Drop-in OpenAI and native Anthropic /v1/messages endpoints for Claude Code, Cursor, OpenClaw
✅ Continuous batching delivers ~4.14x generation speedup at 8x concurrency
✅ Native signed/notarized menu-bar app (not Electron) with web dashboard
✅ Apache 2.0, reuses your existing LM Studio model directory

Cons

⚠️ Apple Silicon and macOS 15+ only - no Linux, Windows or NVIDIA
⚠️ Best benchmarks assume an M3 Ultra 512GB few readers actually own
⚠️ Young project (VLM support only since v0.2.0) - feature surface still maturing
⚠️ No hosted/cloud option; you supply the hardware

Use cases

local-llm-inferencecoding-agentsapple-siliconopenai-compatible-apimlx

Frequently asked

What is the primary benefit of oMLX for coding agents?: It uses paged SSD KV caching to persist previously seen prefixes, which can cut time-to-first-token from 30-90 seconds down to under five seconds for long-context coding agents.
Which operating systems and hardware does oMLX support?: oMLX is exclusively for Apple Silicon Macs running macOS 15 or later. It does not support Linux, Windows, or NVIDIA hardware.
Does oMLX support standard API endpoints for integration?: Yes, it exposes both OpenAI-compatible /v1/chat/completions and a native Anthropic /v1/messages endpoint, along with a one-click config generator for downstream tools.
Is oMLX free to use and what is its license?: oMLX is free to download as a DMG or build from source and is released under the Apache 2.0 open-source license.
Can oMLX host multiple models simultaneously?: Yes, it supports multi-model hosting with LRU eviction for LLMs, VLMs, embeddings, and rerankers, and can reuse an existing LM Studio model directory.