App Overview

MLXHub: Local AI & LLM Server icon

MLXHub: Local AI & LLM Server

Juan Colilla · Developer Tools

Run AI locally

Free · In-app purchases

PRICE
Free
In-app purchases
BUSINESS MODEL
Freemium
No overall Grossing estimate available
RATING
4.7
3 ratings · Top 15%

Evidence scope: No current overall US chart position is available. Category-chart positions shown in discovery are a separate scope. Revenue is a directional model estimate, not verified earnings.

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Build Kit

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A product spec, screen plans, and build steps for your coding agent.

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What's included15 files

A product spec, phased build plan, differentiation notes, and screen references.

  • START_HERE
  • AGENTS
  • EVIDENCE
  • SPEC
  • BUILD_PLAN
  • DIFFERENTIATION
  • skills/
  • screens/
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Illustrative example: an invoice app for independent contractors. Your kit is tailored to the app you choose; this is not its generated content.

Feature spec

Goal: Send a clear invoice after finishing a job.

  • Add a client, line items, a due date, and payment instructions.
  • Preview the total before exporting a PDF.
  • Keep an editable draft if export fails.

Screen plan

Invoice editor: Client at the top, editable line items in the middle, total and preview action at the bottom.

States: Empty draft, validation errors beside each field, exporting, and a retry action that preserves the draft.

Differentiate and validate

Hypothesis: Contractors need faster repeat invoices more than more templates.

First experiment: Test duplicating a previous job with five contractors. Watch where they hesitate before expanding the feature set.

The full kit adds a phased build plan, evidence notes, tool prompts, and implementation guidance. It is a plan for your coding agent, not a finished app.

Usage: Mechanics are fair game; never reuse the original name, branding, assets, or verbatim copy.

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Quick prompt

> SELECT BUILD PLATFORM:

Good fit for mobile-first iOS and Android prototypes with managed app scaffolding.

// RORK SYSTEM PROMPT
Rork plan preview for MLXHub: Local AI & LLM Server: map the core Developer Tools workflow, choose the smallest differentiated feature set, define the data and monetization boundaries, then prototype the riskiest user journey first.
            

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Opportunities

AI-GENERATED OPPORTUNITY HYPOTHESES

These are generated suggestions, not verified review quotations. Check current App Store reviews and speak with users before treating a possible gap as a requirement.

Hypothesis 1

Competitive pricing with generous free tier

Assumption to check: Expensive subscription

Validate with people who use this workflow before building.

Hypothesis 2

Focus on most-requested features first

Assumption to check: Missing features

Validate with people who use this workflow before building.

Hypothesis 3

Optimize for 60fps, fast load times

Assumption to check: Poor performance

Validate with people who use this workflow before building.

App evidence

Original App Store material. Ratings and screenshots describe the existing app, not proof of demand for your version.

App Store description

Run AI locally. Your device. Your data. MLXHub brings open-source language models to iPhone and iPad, powered by Apple Silicon and the mlx-swift inference engine. Your conversations never leave your device. Distributed inference across your devices (Experimental) Pool memory from several Apple Silicon devices on the same Wi-Fi network to run a model that none of them could hold alone. One device hosts; the others join and each takes a slice of the model's layers — no device stores the whole thing. The host sends each device only the files its own layers need, and caches them so the next session starts faster. What to expect: every device must be on the same Wi-Fi, you approve each device once by matching a code on both screens, and MLXHub measures each device's memory before it splits anything. This is an experimental feature — distributed generation works, but a run can still stall or drop a device, and not every model architecture can be split yet. It pays off most with large models. Joining a mesh is free on any device; hosting one is part of MLXHub Plus. Chat with powerful models Download and run LLMs and vision-language models (VLMs) directly on your device. Send text messages or attach photos — the model sees and responds without touching any server. Apple Intelligence built in On supported devices (iPhone 15 Pro / 16 and later with Apple Intelligence enabled), use Apple's on-device model for instant, private responses alongside any downloaded model. Your personality, your assistant Set a global Agent Personality to define the AI's tone and style. Override it per-conversation with custom system instructions. No prompt engineering needed — just describe what you want. Browse and install models Explore a curated catalog of optimized models — from tiny 0.6B models that fit in under 1 GB to powerful 7B models for deeper reasoning. Color-coded RAM badges tell you at a glance whether a model fits your device. Search HuggingFace directly to install any compatible model. Local LAN server Turn your iPhone or iPad into a portable, chat API-compatible inference endpoint on your local network. MLXHub's optional LAN server exposes /v1/chat/completions so any app — from a Mac running OpenCode to a custom script — can use your device's models. No internet required. Auth-protected. Bonjour-discoverable. Part of MLXHub Plus. Built for Apple Silicon MLXHub uses mlx-swift, Apple's own machine-learning framework, to run models at full Metal GPU speed. Model weights are quantized (4-bit, 8-bit) for the best quality-per-GB ratio on iPhone and iPad hardware. Privacy Model inference happens on your device and never leaves it. No account. No ads. The optional LAN server only listens on your local network and is off by default. MLXHub collects a small amount of anonymous diagnostic data to find crashes and broken model loads; it is not linked to you, and you can turn it off in Settings. Terms of Use (EULA): https://www.apple.com/legal/internet-services/itunes/dev/stdeula/

Written user reviews are not shown here. Check current App Store reviews >

Screenshots

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Build scope

Plan a focused first version with your coding agent. These are planning assumptions, not a delivery guarantee.

Define the first version

Choose one audience and one core workflow. Use the kit to agree on its screens, data, and acceptance criteria before building.

Set boundaries

Decide which secondary features, integrations, and platform support can wait. Your version does not need to reproduce everything in the original.

Check the hard parts

Validate external services, specialist technology, data access, and ongoing costs for your chosen scope.

SUGGESTED BUILD STACK
React Native
Expo
Supabase
RevenueCat
BUILD KIT DIFFICULTY
Advanced

From the Build Kit assessment.

A reliable timeline needs an agreed scope and a technical check. Ask your agent to estimate the phases in BUILD_PLAN.md after that review.