ollama-scout

One command to find the right LLMs for your hardware.

ollama-scout scans your GPU VRAM, CPU, and RAM, then recommends compatible Ollama models grouped by use case — with an interactive guided mode for new users and full CLI flags for power users.

Demo

$ ollama-scout

  ollama-scout v0.2.0  |  LLM Hardware Advisor  (Interactive Mode)

  Welcome! Let's find the best LLMs for your hardware.
  Press Enter to scan your system, or Ctrl+C to exit.

                   System Hardware
  ┌─────────────────┬────────────────────────────────────────┐
  │ OS              │ Linux                                  │
  │ CPU             │ AMD Ryzen 9 5900X                      │
  │ Cores / Threads │ 12 cores / 24 threads                  │
  │ RAM             │ 32.0 GB                                │
  │ GPU             │ NVIDIA RTX 3080 (10.0 GB VRAM)         │
  └─────────────────┴────────────────────────────────────────┘

  What are you mainly using this for?
    1. All categories    2. Coding    3. Reasoning    4. Chat

  Coding Models
  Model             Tag    Quant    Size    Fit        Mode     Status
  deepseek-coder    6.7b   Q4_K_M   3.8GB   Excellent  GPU      Available
  codellama         7b     Q4_K_M   3.8GB   Excellent  GPU      Pulled

  Would you like to compare two models? [y/N]:
  Save results as a Markdown report? [y/N]:

Quick Start

# Recommended
pipx install ollama-scout

# Or with pip
pip install ollama-scout

# Or from source
git clone https://github.com/sandy-sp/ollama-scout.git
cd ollama-scout && pip install -e .

Then run:

ollama-scout          # interactive guided mode — no flags needed

Requires Python 3.10+ and Ollama installed.

Features

CLI Reference

Run ollama-scout --help for the full list. See docs/USAGE.md for detailed examples.

How Scoring Works

Apple Silicon: unified memory is treated as VRAM, so M1/M2/M3/M4 Macs get GPU-tier scoring with a 4GB system reserve.

Roadmap

• Interactive guided mode
• Real benchmark timing (ollama run)
• Model comparison mode (--compare)
• Multi-GPU support
• XDG-compliant config paths
• Model list caching (24hr TTL)
• pip installable on PyPI
• Live streaming benchmarks with progress bar
• Model search and filter by keyword
• Web UI version
• Config profiles (work / gaming / minimal)

Contributing

Contributions welcome! See CONTRIBUTING.md for setup instructions and guidelines.

License

MIT — see LICENSE.

Generated by ollama-scout