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Run Qwen3 4B Instruct 2507 on iPhone, iPad & Mac

Qwen3 4B Instruct 2507 runs 100% private on iPhone, iPad & Mac inside Private LLM — no internet connection required, no data sent to any server.

4BiPhoneiPadMac

Download the quantized weights

These are the exact GPTQ-Int4 weights Private LLM runs for Qwen3 4B Instruct 2507, published on our Hugging Face org. They're standard weights you can load in any app that supports the format, not just Private LLM.

Specifications

Parameters
4B
Context window
262K tokens
License
Apache 2.0
Quantization
GPTQ-Int4
Family
Qwen3 4B

What Qwen3 4B Instruct 2507 is good at

general

Qwen3 4B Instruct 2507 is an updated 4 billion parameter language model that focuses on non-thinking mode responses. It is good at following instructions, logical reasoning, math, coding, and understanding long contexts up to 256,000 tokens. The model also shows improved performance in multilingual tasks and generating helpful, high-quality text for open-ended requests.

Which of your devices can run it

iPhone

iPhone 17 Pro MaxiPhone 17 ProiPhone AiriPhone 17iPhone 16 Pro / 16 Pro MaxiPhone 16 / 16 PlusiPhone 16eiPhone 15 Pro / 15 Pro MaxiPhone 15 / 15 PlusiPhone 14 / 14 Plus / 14 Pro / 14 Pro MaxiPhone 13 Pro / 13 Pro MaxiPhone 12 Pro / 12 Pro Max

iPad

iPad Pro (M5, 16GB)iPad Pro (M5, 12GB)iPad Pro (M4, 16GB)iPad Pro (M4, 8GB)iPad Pro (M2, 16GB)iPad Pro (M2, 8GB)iPad Pro (M1, 16GB)iPad Pro (M1, 8GB)iPad Air (M4)iPad Air (M3)iPad Air (M2)iPad Air (M1)iPad mini (A17 Pro)iPad (A16)

Mac

Mac (Apple Silicon, 192GB)MacBook Pro (M4 Max, 128GB)Mac Studio / Pro (Apple Silicon, 96GB)MacBook Pro (M4 Max, 64GB)MacBook Pro (M4 Max, 48GB)MacBook Pro (M4 Max, 36GB)Mac (Apple Silicon, 32GB)MacBook Air (M4, 24GB)MacBook Air (M-series, 16GB)

Browse every model that fits iPhone or Mac.

How to run Qwen3 4B Instruct 2507 in Private LLM

  1. Download Private LLM from the App Store.
  2. Open the in-app model library and choose Qwen3 4B Instruct 2507.
  3. Download the model once, then chat fully offline.
Download Private LLM on the App StoreJoin our Discord

Variants & related models

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Qwen3 4B Instruct 2507 Abliterated

4B
uncensored
262K contextiPhone & iPad · Mac
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Josiefied Qwen3 4B Instruct 2507

4B
uncensored
iPhone & iPad · Mac
Qwen logo

Qwen3 4B Instruct 2507 Heretic

4B
uncensored
262K contextiPhone & iPad · Mac
Qwen logo

Qwen3 4B Instruct 2507 Heretic NoSlop

4B
uncensored
262K contextiPhone & iPad · Mac

Frequently asked questions

  • Yes. Qwen3 4B Instruct 2507 runs on iPhone models with enough memory, such as iPhone 17 Pro Max, iPhone 17 Pro, iPhone Air, iPhone 17, iPhone 16 Pro / 16 Pro Max, iPhone 16 / 16 Plus, iPhone 16e, iPhone 15 Pro / 15 Pro Max, iPhone 15 / 15 Plus, iPhone 14 / 14 Plus / 14 Pro / 14 Pro Max, iPhone 13 Pro / 13 Pro Max, iPhone 12 Pro / 12 Pro Max, fully on-device in Private LLM — no internet connection required.

  • Yes. Qwen3 4B Instruct 2507 runs on Macs with enough unified memory, such as Mac (Apple Silicon, 192GB), MacBook Pro (M4 Max, 128GB), Mac Studio / Pro (Apple Silicon, 96GB), MacBook Pro (M4 Max, 64GB), MacBook Pro (M4 Max, 48GB), MacBook Pro (M4 Max, 36GB), Mac (Apple Silicon, 32GB), MacBook Air (M4, 24GB), MacBook Air (M-series, 16GB), fully on-device in Private LLM.

  • Yes. Once downloaded in Private LLM, Qwen3 4B Instruct 2507 runs 100% on-device — no internet connection, and nothing is sent to any server.

  • Private LLM is a one-time purchase with no subscription and no per-message cost. The models themselves are open source — once downloaded, they run offline with nothing to pay per use.

Why run Qwen3 4B Instruct 2507 in Private LLM

Private LLM has run local AI on iPhone, iPad, and Mac since 2023, before Apple Intelligence existed. Inference happens on your device, so your Qwen3 4B Instruct 2507 conversations never reach a server. The part most apps gloss over is quantization, and that is exactly where on-device quality is won or lost. Most llama.cpp and MLX wrappers ship the same off-the-shelf 4-bit RTN weights. Private LLM ships GPTQ and OmniQuant quantization, tuned per model, and our 3-bit OmniQuant models match or beat those 4-bit RTN builds on the same Apple Silicon. Run the same model both ways and you feel it in the first reply. See how our quantization works.

Specifications and summary come from Qwen3 4B Instruct 2507's Hugging Face model card, released under the Apache 2.0 license. Private LLM ships its own quantized models, built with GPTQ-Int4 quantization tuned per model, and isn't affiliated with the model's authors.