thumbnail: https://huggingface.co/Outlier-Ai/README/resolve/main/assets/thumbnail.png
Outlier
Frontier AI on hardware you own.
Nano (1.7B) · Lite (7B) · Compact (14B) · Max (32B)
What is Outlier
A family of small, fast, local language models designed for the hardware people actually own — Apple Silicon Macs, consumer NVIDIA GPUs, and CPU-only laptops via GGUF.
Four tiers from 1.7B to 32B, shipped in three formats:
| Format | Use case | Runtime |
|---|---|---|
| MLX 4-bit | Apple Silicon Macs | Outlier Desktop app, mlx_lm |
| AutoAWQ 4-bit | NVIDIA GPUs (datacenter) | vLLM, transformers+awq |
| GGUF Q4_K_M / Q5_K_M | CPU-portable, any OS | llama.cpp, Ollama, LM Studio |
Quickstart — Apple Silicon
pip install mlx-lm
python -c "
from mlx_lm import load, generate
model, tok = load('Outlier-Ai/Outlier-Lite-7B-MLX-4bit')
print(generate(model, tok, prompt='Hello', max_tokens=100))
"
Quickstart — Ollama
ollama pull hf.co/Outlier-Ai/Outlier-Lite-7B-GGUF
ollama run hf.co/Outlier-Ai/Outlier-Lite-7B-GGUF "Hello"
Desktop app
Outlier ships a native Mac desktop app with streaming chat, markdown rendering, session history, model switching, and a full settings panel. See outlier.host (coming soon) or download from the Releases page.
Research
Three provisional patents filed April 2026 (61 claims total) on the Path F+ BTX merge architecture that produces the tier family from base models. Non-provisional consolidation due April 2027.
License
Apache 2.0 on all models. Base weights inherit Qwen 2.5's license. Post-training artifacts released under the same terms.
Contact
mattkerr09@gmail.com — Matt Kerr, solo founder, Michigan.