Run Qwen2.5 1.5B Instruct locally on iPhone, iPad & Mac

Generalists · 0.99 GB download · needs 3 GB RAM · Q4_K_M GGUF

Strong for its size. Balanced everyday choice.

In privateSLM, Qwen2.5 1.5B Instruct is an everyday assistant for chat, writing, summarising and quick questions. You download the model once, and from then on every conversation runs entirely on your device — no cloud, no account, no tracking, and it keeps working with the radio off.

At a glance

ModelQwen2.5 1.5B Instruct
CategoryGeneralists
Download size0.99 GB (one time)
QuantizationQ4_K_M (GGUF)
Minimum device RAM3 GB
Runs offlineYes — fully on-device after download
SourceHugging Face

Will it run on my device?

Qwen2.5 1.5B Instruct needs a device with at least 3 GB of RAM — that means iPhone 12 and later, recent iPads, and any Apple Silicon Mac. The privateSLM catalog states the RAM requirement for every model up front, so you know before you download.

How to run Qwen2.5 1.5B Instruct in privateSLM

  1. Get privateSLM on the App Store — one-time purchase, no subscription.
  2. Open Models, pick Qwen2.5 1.5B Instruct, and tap Download (0.99 GB, once).
  3. Select it as your active model and chat — airplane mode included.

On iPhones, iPads and Macs with Apple Intelligence, privateSLM can also answer instantly with the built-in system model — zero downloads. A catalog model like Qwen2.5 1.5B Instruct is for when you want this particular specialist, offline, under your control.

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FAQ

Does Qwen2.5 1.5B Instruct run offline on iPhone?

Yes. After a one-time 0.99 GB download inside privateSLM, Qwen2.5 1.5B Instruct runs entirely on-device via llama.cpp. Airplane mode works — nothing is ever sent to a server.

How much RAM does Qwen2.5 1.5B Instruct need?

A device with at least 3 GB of RAM — in practice iPhone 12 and later, recent iPads, and any Apple Silicon Mac.

Is Qwen2.5 1.5B Instruct free to use in privateSLM?

The model itself is open-weights (Q4_K_M GGUF) and the download is free. privateSLM is a one-time purchase — no subscription, no per-message fees.