Compare/LM Studio + Locally AI vs qmd

AI tool comparison

LM Studio + Locally AI vs qmd

Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.

L

Developer Tools

LM Studio + Locally AI

LM Studio buys the best iOS local LLM app to go cross-device

Ship

75%

Panel ship

Community

Free

Entry

LM Studio, the most popular desktop app for running local large language models, has acquired Locally AI — the leading iOS and iPadOS app for on-device inference on Apple Silicon. Locally AI's creator Adrien Grondin is joining LM Studio full-time to lead cross-device native AI experiences. The acquisition signals LM Studio's ambition to own the full local AI stack: macOS, Windows, Linux, and now iPhone and iPad. Locally AI was notable for its deep Apple Silicon integration, using Core ML and Metal Performance Shaders to run models like Llama 3 and Phi-3 natively on A-series and M-series chips. The app had a dedicated following among privacy-conscious users who wanted a clean iOS interface without compromising their data to cloud services. LM Studio brings a larger model library, server mode, and a more mature MLX/GGUF toolchain. For local AI enthusiasts, this is a consolidation play in a space that was starting to fragment across too many single-platform apps. A unified LM Studio experience across desktop and mobile would be a significant UX improvement. It also sets up an interesting competition with Apple's own on-device AI ambitions in iOS 19.

Q

Developer Tools

qmd

Local doc search engine with BM25 + vectors + LLM re-ranking — by Shopify's CEO

Mixed

50%

Panel ship

Community

Free

Entry

qmd is a lightweight local search engine built by Tobi Luetke, CEO of Shopify, for indexing and querying personal knowledge bases, documentation, and meeting notes — entirely offline. It combines three retrieval approaches in a single pipeline: BM25 full-text search for exact keyword matches, vector semantic search via ONNX-based embeddings, and LLM re-ranking using GGUF models through node-llama-cpp. All three stages run locally with no cloud dependency. The tool ships in multiple deployment modes: a CLI for ad-hoc queries, a Node.js library for programmatic use, an HTTP service for local API access, and — most useful for AI workflows — a native MCP server that lets Claude Code, Cursor, and similar editors query your local knowledge base directly during coding sessions. The hybrid retrieval approach means it handles both "find the exact error message from last week's standup notes" and "what was our decision about the auth architecture" equally well. What makes this notable beyond its technical approach is provenance: Luetke shipped it as a personal tool he actually uses, not a startup product. The GitHub history shows active iteration and he's been talking about it on X. It's a credible signal of where pragmatic AI-augmented knowledge management is heading for technical users who prefer local-first tools.

Decision
LM Studio + Locally AI
qmd
Panel verdict
Ship · 3 ship / 1 skip
Mixed · 2 ship / 2 skip
Community
No community votes yet
No community votes yet
Pricing
Free (LM Studio core); Locally AI previously $0 (donation-ware)
Free, open source (MIT)
Best for
LM Studio buys the best iOS local LLM app to go cross-device
Local doc search engine with BM25 + vectors + LLM re-ranking — by Shopify's CEO
Category
Developer Tools
Developer Tools

Reviewer scorecard

Builder
80/100 · ship

This is the right move for LM Studio. The desktop client is already excellent and Locally AI's Core ML integration is the best iOS inference wrapper available. Combining Grondin's Apple-native work with LM Studio's model management and server mode could produce something genuinely special for local AI power users.

80/100 · ship

Hybrid BM25 + vector + LLM re-rank is the right architecture for personal knowledge search — each layer catches what the others miss. The MCP server mode is genuinely useful: being able to ask Claude Code 'what did we decide about X last month' against my own notes changes the workflow. MIT licensed and from someone who ships real products.

Skeptic
45/100 · skip

Acquisitions in open-source adjacent tools often mean the indie app loses what made it great. Locally AI was clean and opinionated; LM Studio is powerful but has more surface area. There's real risk the mobile experience gets de-prioritized once the acquisition honeymoon ends.

45/100 · skip

This is a well-executed weekend project, not a production tool. It requires GGUF models and manual embedding setup — a meaningful friction barrier for non-technical users. The 'built by a CEO' narrative drives GitHub stars more than the technical differentiation. Obsidian with a local AI plugin gets you here with better UX.

Futurist
80/100 · ship

The race to own the local AI client layer is just beginning. LM Studio is positioning itself as the VLC of AI — runs everything, everywhere, free. If they nail the cross-device sync story (shared model library, shared chats), they become the default for privacy-first AI.

80/100 · ship

The pattern here — local hybrid retrieval as an MCP server feeding into AI coding agents — will be ubiquitous in two years. Today it's a technical power-user tool; tomorrow it's how everyone's AI assistant knows the institutional context behind the code. qmd is an early, clean implementation of that pattern.

Creator
80/100 · ship

Being able to run the same model on my MacBook and iPhone with the same interface is a genuine quality-of-life win. I use local models for confidential creative writing and the iOS gap has always been frustrating. This closes it.

45/100 · skip

I manage a lot of notes, references, and creative briefs, but the setup friction here — GGUF models, CLI configuration — makes this inaccessible for most creators. The concept is great; the UX needs a front-end before it reaches beyond developers.

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