Text Generation
MLX
Safetensors
qwen2
4-bit precision
4bit
apple-silicon
chain-of-thought
chat
conversational
deepseek
deepseek-r1
deepseek-r1-distill
edge-ai
function-calling
instruct
local-llm
m1
m2
m3
m4
mac
mac-mini
mac-studio
macbook-air
macbook-pro
macos
metal
mlx-community
mlx-lm
no-cloud
offline
on-device
outlier
outlier-app
private
quantized
r1
r1-distill
reasoning
thinking
Instructions to use Outlier-Ai/DeepSeek-R1-Distill-Qwen-32B-MLX-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Outlier-Ai/DeepSeek-R1-Distill-Qwen-32B-MLX-4bit with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("Outlier-Ai/DeepSeek-R1-Distill-Qwen-32B-MLX-4bit") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use Outlier-Ai/DeepSeek-R1-Distill-Qwen-32B-MLX-4bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "Outlier-Ai/DeepSeek-R1-Distill-Qwen-32B-MLX-4bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "Outlier-Ai/DeepSeek-R1-Distill-Qwen-32B-MLX-4bit" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Outlier-Ai/DeepSeek-R1-Distill-Qwen-32B-MLX-4bit", "messages": [ {"role": "user", "content": "Hello"} ] }' - Atomic Chat
docs(card): SEO + cross-link refresh (HF-DISCOVERABILITY-001)
Browse files
README.md
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content: A train leaves station A at 60 mph and another leaves station B, 180
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miles away, at 40 mph toward each other. When do they meet?
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---
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# DeepSeek-R1-Distill-Qwen-32B
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4-bit
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M1, M2, M3, and M4 Macs via `mlx_lm`. Faithful port of the upstream weights — no
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fine-tuning, no merge.
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##
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- **
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- **Runtime:** mlx-lm, LM Studio, Jan, Outlier desktop app
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- **Publisher:** Outlier-Ai (solo, Mac-native AI platform)
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##
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```bash
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pip install
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python -m mlx_lm.generate \
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--model Outlier-Ai/DeepSeek-R1-Distill-Qwen-32B-MLX-4bit \
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--prompt "
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--max-tokens 256
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```
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picker under `reasoning`.
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## Why this repo exists
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This is a canonically-named twin of [Outlier-Ai/Outlier-R1-Distill-32B-MLX-4bit](https://huggingface.co/Outlier-Ai/Outlier-R1-Distill-32B-MLX-4bit).
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Same weights, same quant, different name. The branded repo carries the Outlier
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identity; this one carries the upstream identity so it's findable via searches
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like "deepseek-r1-distill-qwen-32b 4bit mlx". Use whichever path you came across — both
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point to the same files.
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## Provenance
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- Converted via `mlx_lm.convert --q-bits 4 --q-group-size 64`
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- Source: [DeepSeek-R1-Distill-Qwen-32B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-32B)
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- Date produced: 2026-04-19 (Day 19)
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- Conversion factory: Outlier MEGA-INFINITE phase3
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##
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- **Outlier org on HuggingFace:** [Outlier-Ai](https://huggingface.co/Outlier-Ai)
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- **Desktop app:** [outlier.host](https://outlier.host)
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- **Founders lifetime ($200, 500-seat cap):** [buy.polar.sh](https://buy.polar.sh/polar_cl_mJfYZsEpEMDcYrgxzvTdnahSeSQNq1UYLqV0l08CUhW)
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- **Discord:** [discord.gg/Hapennmdn9](https://discord.gg/Hapennmdn9)
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- **Outlier Research MoE:** [huggingface.co/collections/Outlier-Ai/outlier-research-69e2fb3a71984614b3c7a279](https://huggingface.co/collections/Outlier-Ai/outlier-research-69e2fb3a71984614b3c7a279)
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- **Outlier Server V3.2:** [huggingface.co/collections/Outlier-Ai/outlier-server-v32-69e2fb4b71984614b3c7a4a3](https://huggingface.co/collections/Outlier-Ai/outlier-server-v32-69e2fb4b71984614b3c7a4a3)
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##
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## License
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[DeepSeek-R1-Distill-Qwen-32B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-32B) when using this conversion.
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content: A train leaves station A at 60 mph and another leaves station B, 180
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miles away, at 40 mph toward each other. When do they meet?
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---
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> **Run this on your Mac with [Outlier](https://outlier.host/?utm_source=hf&utm_medium=modelcard&utm_campaign=deepseek_r1_distill_qwen_32b_mlx_4bit)** — a one-click app that loads MLX models locally. macOS arm64, free download.
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# DeepSeek-R1-Distill-Qwen-32B (MLX 4-bit)
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MLX 4-bit conversion of [`deepseek-ai/DeepSeek-R1-Distill-Qwen-32B`](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-32B), repackaged for Apple Silicon. Original weights, original license — see frontmatter above. This repo only changes the on-disk format (safetensors, MLX 4-bit, `chat_template.jinja`, tokenizer).
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## About this conversion
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- **Format:** MLX 4-bit safetensors (group size 64, symmetric)
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- **Tooling:** `mlx-lm` 0.31.x compatible
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- **Files:** `model.safetensors` shards · `config.json` · tokenizer · `chat_template.jinja`
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- **License:** inherits from the upstream base model — see YAML `license` field
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### Load directly with `mlx-lm`
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```bash
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pip install mlx-lm
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python -m mlx_lm.generate \
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--model Outlier-Ai/DeepSeek-R1-Distill-Qwen-32B-MLX-4bit \
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--prompt "Hello, world." \
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--max-tokens 256
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```
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Or in Python:
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```python
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from mlx_lm import load, generate
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model, tokenizer = load("Outlier-Ai/DeepSeek-R1-Distill-Qwen-32B-MLX-4bit")
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print(generate(model, tokenizer, prompt="Hello, world.", max_tokens=256))
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```
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## What is Outlier?
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Outlier is a free macOS app that runs language models on your Mac, fully offline. Pick a model from a tier picker, click download, and chat — no API keys, no cloud round-trips, no usage caps. It ships with its own curated tier of MLX-4bit models and can also load any compatible MLX conversion (including this one) via the model picker.
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➡ Download Outlier (free, Apple Silicon): **[outlier.host](https://outlier.host/?utm_source=hf&utm_medium=modelcard&utm_campaign=deepseek_r1_distill_qwen_32b_mlx_4bit)**
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For benchmark numbers (MMLU, HumanEval, tok/s on M-series Macs) with full provenance, see [outlier.host/benchmarks](https://outlier.host/benchmarks?utm_source=hf&utm_medium=modelcard&utm_campaign=deepseek_r1_distill_qwen_32b_mlx_4bit).
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## Other Outlier conversions
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- [DeepSeek-R1-Distill-Qwen-7B (MLX 4-bit) — MLX 4-bit conversion (1,932 downloads)](https://huggingface.co/Outlier-Ai/DeepSeek-R1-Distill-Qwen-7B-MLX-4bit)
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- [DeepSeek-R1-Distill-Llama-8B (MLX 4-bit) — MLX 4-bit conversion (1,148 downloads)](https://huggingface.co/Outlier-Ai/DeepSeek-R1-Distill-Llama-8B-MLX-4bit)
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- [DeepSeek-R1-Distill-Qwen-14B (MLX 4-bit) — MLX 4-bit conversion (1,087 downloads)](https://huggingface.co/Outlier-Ai/DeepSeek-R1-Distill-Qwen-14B-MLX-4bit)
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- [Outlier-Core-27B (MLX 4-bit) — MLX 4-bit conversion (55 downloads)](https://huggingface.co/Outlier-Ai/Outlier-Core-27B-MLX-4bit)
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- [Outlier-Nano-4B (MLX 4-bit) — MLX 4-bit conversion (67 downloads)](https://huggingface.co/Outlier-Ai/Outlier-Nano-4B-MLX-4bit)
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## License
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This conversion preserves the upstream license declared in the frontmatter (`mit`). Refer to the upstream base model card for the canonical license text and any usage restrictions.
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