Quick Start
Get Model Lens running locally with a few commands.
Prerequisites
Section titled “Prerequisites”- Python 3.10+
- A local LLM provider (we recommend LM Studio or Ollama)
- At least one model loaded in your provider
Installation
Section titled “Installation”-
Clone the repository
Terminal window git clone https://github.com/kevinjobin1/model-lens.gitcd model-lens -
Install dependencies
Terminal window pip install -r requirements.txt -
Install dev tooling (optional)
Terminal window pip install ".[dev]"pre-commit install -
Verify installation
Terminal window python apps/cli/modellens.py --help
Run your first benchmark
Section titled “Run your first benchmark”If LM Studio is running with a model loaded:
python apps/cli/modellens.py run --quickModel Lens auto-detects your provider and models.
python apps/cli/modellens.py run --provider ollama --models llama3.2 --quick# llama.cpppython apps/cli/modellens.py run --provider llama.cpp --quick
# vLLMpython apps/cli/modellens.py run --provider vllm --quick
# Open WebUIpython apps/cli/modellens.py run --provider open-webui --quickRun a workload evaluation
Section titled “Run a workload evaluation”Test models against real projects:
python apps/cli/modellens.py workload run --model qwen3.5-9bCompare two models
Section titled “Compare two models”python apps/cli/modellens.py run --framework compare --models qwen3.5 gemma-4Start the dashboard
Section titled “Start the dashboard”cd apps/dashboardbun installbun run dev # → http://localhost:4321Stream live events to the dashboard
Section titled “Stream live events to the dashboard”python apps/cli/modellens.py run --sse-port 9090Next steps
Section titled “Next steps”- Read the Architecture guide to understand how Model Lens works
- Check Provider setup guides for provider-specific configuration
- Learn about benchmark methodology and scoring