llm-speed
Benchmark local LLM inference and inspect the settings behind your results. llm-speed.com publishes submitted measurements across hardware and backends. This repository contains the benchmark CLI.
Install
With Python 3.10 or newer:
pipx install llm-speed
Or use uv tool install llm-speed. On a machine without Python, the installer can provision it with your consent:
curl -fsSL https://llm-speed.com/install.sh | sh
Check dependencies and backend setup with llm-speed doctor. On an interactive terminal it offers setup steps; otherwise it prints guidance.
Run
llm-speed --version
llm-speed bench --quick --no-upload
The second command saves results locally without uploading. Choose a backend and model with --backend and --model when needed. Run llm-speed bench --help for options. Uploading is optional; review the privacy documentation before sharing results.
Supported backend integrations include Ollama, llama.cpp, MLX, vLLM, and ExLlamaV2. Availability depends on your hardware and installed backend. Measurements with different models, quantization, and workloads are not interchangeable rankings. See the methodology.
Links and license
CLI code is licensed under Apache-2.0. Shared benchmark data is licensed under CC BY 4.0.
1 maintainer
Metadata
1 maintainer
Release files for llm-speed 0.0.7
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Source distribution (sdist)
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| llm_speed-0.0.7.tar.gz | 125.5 kB | Details |
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| llm_speed-0.0.7-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 275.6 kB
Release files / llm_speed-0.0.7.tar.gz
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| Tags | Python 3 |
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