Choose LM Studio if
- · You need Windows or Linux (we're Mac-only)
- · Free is non-negotiable
- · You're researching GGUF quants in particular
- · You don't need agents — single-turn chat is enough
Honest comparison
AiLocally vs LM Studio
LM Studio is the reason a lot of devs (us included) realised local AI could feel friendly. It's a great product. We built AiLocally because we wanted to push the UX one step further on Apple Silicon — native Swift instead of Electron, agents and pipelines instead of just a chat window, and memory that survives sessions. Here's the apples-to-apples.
Choose AiLocally if
- · You're on Apple Silicon and want native MLX performance
- · You want a real Mac app, not Electron
- · Multi-agent workflows are part of how you work
- · You want memory + tools + an API server — bundled, not bolted-on
- · $49 once is fine if it saves you setup time forever
Side-by-side
Both teams ship fast. If you spot something out of date, tell us.
| Feature | AiLocally | LM Studio |
|---|---|---|
| Price | $29–129 lifetime | Free for personal; paid for commercial |
| Platforms | macOS 26.1+ Apple Silicon only | macOS, Windows, Linux |
| Runtime | Apple MLX (native) | llama.cpp (Metal-accelerated) |
| App technology | Native Swift + SwiftUI | Electron |
| Memory footprint idle | ~80 MB | ~400–600 MB |
| Built-in agents | 22 agents + custom builder | System prompt presets only |
| Visual pipelines | Yes (multi-agent flow editor) | No |
| Persistent memory | Yes, Markdown-backed, cross-conv | No (per-chat history only) |
| OpenAI-compatible server | Yes | Yes |
| Hugging Face integration | Native browser, filters, MLX-first | Native browser, GGUF-first |
| Tool execution | Yes, per-call approval | Limited (function calling spec) |
| Auto-updates | Sparkle (planned) | In-app updater |
| Open source | No | No (proprietary, free tier) |
| Support | Email + Discord | Community Discord + GitHub |
Why "native" matters
Electron vs Swift on Apple Silicon
LM Studio is built on Electron. That's how it ships the same UI to Mac, Windows, and Linux from one codebase — a real engineering win for a small team. The trade-off is that every menu, every chat bubble, every scrollbar is rendered by Chromium. On a 16 GB Mac with a 30 B model loaded, those ~500 MB matter.
AiLocally is native SwiftUI. Same UX you'd expect from a first-party Apple app: real menus, real shortcuts, real drag-and-drop, native quick look. Idle memory ~80 MB. We trade portability for fidelity — that's the bet.
MLX over ggml
Apple's framework on Apple's silicon
llama.cpp + Metal does a great job. LM Studio uses it well. But MLX was written by Apple for Apple Silicon, with awareness of unified memory and the Neural Engine. On bigger models (30 B+) we see 20–35% throughput improvement vs comparable GGUF quants in our internal benchmarks.
On 7 B–13 B models, the gap is small and either is fine. If your usual driver is a 70 B model on a maxed-out MacBook Pro, MLX changes what's practical.
Beyond the chat box
Agents, pipelines, memory — bundled
LM Studio's "presets" let you save a system prompt + parameters per session. That's useful. It's also where it stops.
AiLocally ships 22 first-party agents specialised for different jobs (coding, writing, research, ops, …) and a visual flow editor where you compose them. Run "Researcher → Outliner → Doc Writer" as one pipeline, with shared memory between steps. Tool execution is gated by your approval, not a YAML file. If your workflow has more than one prompt in it, this is the difference between assembling agents in code and getting back to the actual work.
Long-term memory
AI that remembers across sessions
In LM Studio, conversation history is per-chat. Close the window, start a new one — the model is amnesic. That's the right default for a runtime.
AiLocally writes structured memory entries to disk as plain Markdown. The agent decides what's worth remembering (with your approval) and recalls it on demand via a tool. You can open the folder in Finder, edit entries, delete them. Memory is yours, on disk, debuggable — not a black-box vector store.
Use what feels right.
LM Studio is a great way to get started with local AI. If you grow into needing native performance, agents, and memory, we're here.