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Run Qwen 2.5 Coder 32B on Mac

Coding specialist trained on 5.5T tokens, with 32k context for large files

Qwen 2.5 Coder 32B runs 100% private on Mac inside Private LLM — no internet connection required, no data sent to any server.

32.8BMaccoding

Model on Hugging Face

Specifications

Parameters
32.8B
Context window
33K tokens
License
Apache 2.0
Quantization
GPTQ-Int4
Family
Qwen 2.5 32B

What Qwen 2.5 Coder 32B is good at

Qwen 2.5 Coder 32B is an instruction-tuned model for code completion, refactoring, explanation, and fixing, with a 32,768-token context window that helps it work across large files. It uses 32.5 billion parameters from the Qwen 2.5 32B family and was trained on 5.5 trillion tokens of source code, text-code grounding, and synthetic data. The model matches GPT-4o on coding tasks and supports many programming languages.

Which of your devices can run it

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)

Browse every model that fits iPhone or Mac.

How to run Qwen 2.5 Coder 32B in Private LLM

  1. Download Private LLM from the App Store.
  2. Open the in-app model library and choose Qwen 2.5 Coder 32B.
  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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Roleplay and storywriting finetune of Qwen 2.5 32B with flexible tone control

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OpenHands LM 32B v0.1

32.8B

Autonomous software issue resolution based on Qwen 2.5 32B

33K contextMac
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Qwen 2.5 32B

32.8B

General-purpose instruction model excelling at coding and mathematics

33K contextMac
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CodeNinja 1.0 OpenChat 7B

7.2B

Code completion and refactoring specialist built on OpenChat 3.5

8K contextiPhone & iPad · Mac
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Llama 3 WhiteRabbitNeo 8B v2.0

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Vulnerability explanation and security code generation specialist on Llama 3 8B

8K contextiPhone & iPad · Mac
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OpenHands LM 7B v0.1

7.6B

Solves GitHub issues and refactors code, built on Qwen 2.5

33K contextiPhone & iPad

Frequently asked questions

  • Qwen 2.5 Coder 32B is too large for current iPhones. It runs on Mac with enough unified memory inside Private LLM, fully offline.

  • Yes. Qwen 2.5 Coder 32B 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), fully on-device in Private LLM.

  • Yes. Once downloaded in Private LLM, Qwen 2.5 Coder 32B 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 Qwen 2.5 Coder 32B in Private LLM

Private LLM has run local AI on iPhone, iPad, and Mac since 2023, well before Apple Intelligence, LM Studio, Ollama, etc. existed. Inference happens on your device, so your Qwen 2.5 Coder 32B 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 Qwen 2.5 Coder 32B'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.