Run DeepSeek R1 Distill Qwen 14B on iPad & Mac
Step-by-step reasoning distilled from DeepSeek R1 into Qwen2.5 14B
DeepSeek R1 Distill Qwen 14B runs 100% private on iPad & Mac inside Private LLM — no internet connection required, no data sent to any server.
Model on Hugging Face
Specifications
- Parameters
- 14.8B
- Context window
- 131K tokens
- License
- MIT
- Quantization
- GPTQ-Int4
- Family
- DeepSeek R1 Distill
What DeepSeek R1 Distill Qwen 14B is good at
When tackling math, code, or logic problems, DeepSeek R1 Distill Qwen 14B works through detailed step-by-step reasoning before delivering a final answer. It has 14.8 billion parameters and a context window of 131,072 tokens. This model is a distilled version of the larger DeepSeek R1, fine-tuned from Qwen2.5 14B using reasoning examples generated by the full model. It performs well on benchmarks like AIME 2024 and MATH-500, though it does not match the largest models in the family. For best results, users should set a temperature around 0.6, avoid adding any system prompt, and for mathematical problems include an instruction such as “Please reason step by step, and put your final answer within \boxed{}.”
Which of your devices can run it
iPad
Mac
How to run DeepSeek R1 Distill Qwen 14B in Private LLM
- Download Private LLM from the App Store.
- Open the in-app model library and choose DeepSeek R1 Distill Qwen 14B.
- Download the model once, then chat fully offline.
Variants & related models
DeepSeek R1 Distill Llama 70B
Reasoning model distilling DeepSeek R1 reasoning into Llama 3.3 70B
DeepSeek R1 Distill Llama 8B
Reasoning with chain-of-thought, distilled from DeepSeek R1 into Llama 3.1 8B
DeepSeek R1 Distill Llama 8B Abliterated
Uncensored DeepSeek R1 Distill 8B via refusal abliteration
DeepSeek R1 Distill Qwen 32B Abliterated
Uncensored proof-of-concept removing alignment guardrails from DeepSeek R1 Distill
DeepSeek R1 Distill Qwen 7B
Step-by-step reasoning distilled from DeepSeek R1 into Qwen 7B
Fuse O1 DeepSeek R1 QwQ SkyT1 32B
Reasoning model merging three chain-of-thought experts for math, coding, and science
Frequently asked questions
DeepSeek R1 Distill Qwen 14B is too large for current iPhones. It runs on Mac with enough unified memory inside Private LLM, fully offline.
Yes. DeepSeek R1 Distill Qwen 14B 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 14B 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 14B 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 14B 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 14B'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.