Home/Evaluation & Observability/whichllm

whichllm

Andyyyy64/whichllm

Command-line tool to find and benchmark local LLM performance

GitHub

GraphCanon updated Aug 12, 2026 · GitHub synced Aug 12, 2026

31views this month

6.2k stars330 forksLast push Aug 5, 2026 Python MIT

Decision brief

whichllm is designed to help users identify and benchmark local large language models that perform well on their specific hardware configuration via real-time benchmarks.

Good fit when

When you need to quickly discover which locally available LLM runs most efficiently on your Apple Silicon or GPU infrastructure using Python scripts
If the evaluation based on live, recent benchmarks is more important than considering only the model parameters for decision making

Avoid when

In scenarios where extensive customization of benchmarking criteria beyond what this tool offers is required
When you are working in a non-Python environment and prefer not to introduce Python scripts into your workflow

Observed Jul 17, 2026 · Source: enrich:decision_facts

whichllm alternatives Trust report

Verify the decision

Maintenance and security

Full trust report

Maintenance: Active (7d since push); As of Aug 12, 2026
Provenance: Not a fork · Personal account; As of Aug 12, 2026
Security (OSV): No lockfile; As of Jul 15, 2026

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install whichllm

PyPI

Similar tools

Same-category neighbours. No typed graph edges are catalogued for this tool yet.

llmfit

Hundreds of models & providers. One command to find what runs on your hardware.

37k★

litgpt

20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.

14k★

open-llms

📋 A list of open LLMs available for commercial use.

13k★

Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

A Python-based CLI tool for discovering which local large language models run best on your hardware through real-time benchmarks.

Capability facts

CLI: CLI entrypoint
Source: pyproject.toml:[project.scripts] · Aug 12, 2026
Languages: python
Source: github.language+pyproject.toml · Aug 12, 2026

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Aug 12, 2026)

- Python 3.11+

Source link

README

Quick start Run the recommendation command once, with no project setup. Simulate a GPU before you buy hardware. Install it when you use it often. Other install paths. Auto pick the best model for your hardware and chat whichllm run Auto detect hardware and show best models whichl...

For agents

This page has a .md twin and JSON over the API.

/tools/andyyyy64-whichllm.md GET /api/graphcanon/tools/andyyyy64-whichllm GET /api/graphcanon/graph?tool=andyyyy64-whichllm