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Run DeepSeek R1 Distill Qwen 7B on iPhone, iPad & Mac

Step-by-step reasoning distilled from DeepSeek R1 into Qwen 7B

DeepSeek R1 Distill Qwen 7B runs 100% private on iPhone, iPad & Mac inside Private LLM — no internet connection required, no data sent to any server.

7.6BiPhoneiPadMacreasoning

Specifications

Parameters
7.6B
Context window
131K tokens
License
MIT
Quantization
GPTQ-Int4
Family
DeepSeek R1 Distill

What DeepSeek R1 Distill Qwen 7B is good at

DeepSeek R1 Distill Qwen 7B approaches problems with step-by-step reasoning, explicitly writing out its thought process before giving an answer. This 7.6 billion parameter model was created by distilling the reasoning patterns of the larger DeepSeek R1 into a Qwen architecture, fine-tuning it on 800,000 curated examples. It handles up to 131,072 tokens of context. On math benchmarks, it achieves 55.5% on AIME 2024 and 92.8% on MATH-500. It is part of the DeepSeek R1 Distill family, alongside other sizes, all released for research.

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 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)

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 DeepSeek R1 Distill Qwen 7B in Private LLM

  1. Download Private LLM from the App Store.
  2. Open the in-app model library and choose DeepSeek R1 Distill Qwen 7B.
  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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DeepSeek R1 Distill Llama 70B

70.6B

Reasoning model distilling DeepSeek R1 reasoning into Llama 3.3 70B

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DeepSeek R1 Distill Llama 8B

8B

Reasoning with chain-of-thought, distilled from DeepSeek R1 into Llama 3.1 8B

131K contextiPhone & iPad · Mac
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DeepSeek R1 Distill Llama 8B Abliterated

8B

Uncensored DeepSeek R1 Distill 8B via refusal abliteration

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DeepSeek R1 Distill Qwen 14B

14.8B

Step-by-step reasoning distilled from DeepSeek R1 into Qwen2.5 14B

131K contextiPhone & iPad · Mac
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DeepSeek R1 Distill Qwen 32B Abliterated

32.8B

Uncensored proof-of-concept removing alignment guardrails from DeepSeek R1 Distill

131K contextMac
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Fuse O1 DeepSeek R1 QwQ SkyT1 32B

32.8B

Reasoning model merging three chain-of-thought experts for math, coding, and science

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Frequently asked questions

  • Yes. DeepSeek R1 Distill Qwen 7B 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, fully on-device in Private LLM — no internet connection required.

  • Yes. DeepSeek R1 Distill Qwen 7B 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, DeepSeek R1 Distill Qwen 7B 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 DeepSeek R1 Distill Qwen 7B 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 DeepSeek R1 Distill Qwen 7B 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 DeepSeek R1 Distill Qwen 7B's Hugging Face model card, released under the MIT 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.