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DeepSeek-R1-Distill-Llama-8B (MLX 4-bit)

MLX 4-bit conversion of deepseek-ai/DeepSeek-R1-Distill-Llama-8B, 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).

About this conversion

Format: MLX 4-bit safetensors (group size 64, symmetric)
Tooling: mlx-lm 0.31.x compatible
Files: model.safetensors shards · config.json · tokenizer · chat_template.jinja
License: inherits from the upstream base model — see YAML license field

Load directly with `mlx-lm`

pip install mlx-lm
python -m mlx_lm.generate \
  --model Outlier-Ai/DeepSeek-R1-Distill-Llama-8B-MLX-4bit \
  --prompt "Hello, world." \
  --max-tokens 256

Or in Python:

from mlx_lm import load, generate
model, tokenizer = load("Outlier-Ai/DeepSeek-R1-Distill-Llama-8B-MLX-4bit")
print(generate(model, tokenizer, prompt="Hello, world.", max_tokens=256))

What is Outlier?

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.

➡ Download Outlier (free, Apple Silicon): outlier.host

For benchmark numbers (MMLU, HumanEval, tok/s on M-series Macs) with full provenance, see outlier.host/benchmarks.

Other Outlier conversions

License

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.