oget 1.0.2

Ollama Model Direct Downloader & Installer - get direct links and install models offline

Oget 🦙

Ollama Model Direct Downloader & Installer

Get direct download links for Ollama models and install locally downloaded models — no internet required at install time. | Blog: 🇬🇧 English | Blog: 🇹🇷 Türkçe | GitHub | PyPI

Why?

ollama pull can be slow or unreliable in some regions. Oget lets you:

• Get direct CDN download links for any Ollama model
• Download using your own download manager (IDM, aria2, wget, curl...)
• Install the downloaded files into Ollama offline

Install

via pip (all platforms)

pip install oget

via AUR (Arch Linux)

# Using yay
yay -S oget

# Using paru
paru -S oget

# Manual
git clone https://aur.archlinux.org/oget.git
cd oget
makepkg -si

Usage

Step 1 — Get download links

oget get gemma2:2b
# oget get deepseek-r1:7b
# oget get huihui_ai/deepseek-r1-abliterated:8b

Example Output:

ℹ Fetching direct download link for model: gemma2:2b

Curl command to download the manifest (run in your manifest folder):
curl -L "https://registry.ollama.ai/v2/library/gemma2/manifests/2b" -o "manifest"

Download links for layers:
1 - [1.5 GB] https://registry.ollama.ai/v2/library/gemma2/blobs/sha256:74627347...
2 - [358 B]  https://registry.ollama.ai/v2/library/gemma2/blobs/sha256:e0a42594...
...

Curl command to download all blobs (run in your blobs folder):
curl -L "https://registry.ollama.ai/v2/library/gemma2/blobs/sha256:74627347..." -o "sha256-74627347..."
curl -L "https://registry.ollama.ai/v2/library/gemma2/blobs/sha256:e0a42594..." -o "sha256-e0a42594..."
...

Step 2 — Download the files

Copy the printed curl commands and run them in two separate folders:

• One folder for the manifest
• One folder for the blobs

Step 3 — Install into Ollama

# Linux/macOS (requires sudo)
sudo oget install --model gemma2:2b --blobsPath ./downloads

# With explicit models path
sudo oget install --model gemma2:2b --blobsPath ./downloads --modelsPath ~/.ollama/models

Then run as usual:

ollama run gemma2:2b

Models Path

Oget resolves the Ollama models directory in this order:

Priority	Source
1st	--modelsPath CLI argument
2nd	OLLAMA_MODELS environment variable
Error	Helpful instructions are printed

Supported Platforms

• Linux
• macOS
• Windows

Zero Dependencies

Oget uses only Python standard library — no pip install requirements beyond Python 3.8+.

License

MIT