Downloads · 30 days
22
10% of all-time downloads
Outlier-Ai/Outlier-Code-27B-MLX-4bit
Outlier-Code-27B-MLX-4bit is a text generation model from Outlier-Ai. Use it when you need the model to write or continue text. It is set up for mlx. The card lists the license as apache-2.0.
Part of the Outlier shipping lineup. Outlier is a free macOS app that runs this model locally, with one click. Apple Silicon only.
Downloads · 30 days
22
10% of all-time downloads
All-time downloads
222
Public
Parameters
26.9B
15.2 GB on disk
Likes
0
Public
Click a slice to open those files.
.safetensors15.1 GB · 100%
How the weights are stored.
U3226.9B · 100%
From the Hugging Face model README
Part of the Outlier shipping lineup. Outlier is a free macOS app that runs this model locally, with one click. Apple Silicon only.
Code-tuned configuration of the Core 27B weights — same safetensors, different chat template, lower temperature, and code-specialized system prompt. Use this if your primary workflow is code generation or repo-aware editing.
The simplest way to use this model is through the Outlier app — open the tier picker, select Outlier Code, click download, and chat. No setup, no Python, no MLX install, no token quotas.
➡ Download Outlier — outlier.host
A screenshot of the tier picker is at outlier.host/screenshots/tier-picker.png.
If you want the raw MLX-4bit weights without the app:
pip install mlx-lm
python -m mlx_lm.generate \
--model Outlier-Ai/Outlier-Code-27B-MLX-4bit \
--prompt "Write a quicksort in Python." \
--max-tokens 512
from mlx_lm import load, generate
model, tokenizer = load("Outlier-Ai/Outlier-Code-27B-MLX-4bit")
print(generate(model, tokenizer, prompt="Hello", max_tokens=256))
For σ-qualified MMLU, HumanEval, and Mac inference-speed numbers — with full provenance (source file, command, n, stderr, date) — see outlier.host/benchmarks.
Apache 2.0 (inherits from upstream base model). Conversion artifact only — the underlying weights are governed by the base model's license.