# Show HN: Shoehorn – Quantize any model down to run on your machine

> Source: <https://notactuallytreyanastasio.github.io/shoehorn/>
> Published: 2026-08-18 14:29:20+00:00

# shoehorn

Make any language model fit the memory you actually have.

Preset quantizations ignore your hardware: pick one that fits and you
either waste hundreds of megabytes of quality headroom or find out at load time it
didn't fit after all. shoehorn starts from the memory you actually have, subtracts
what inference itself needs, and solves a per-tensor mixed-precision assignment
that lands within a rounding error of the remainder — routinely using
**99.99%** of the budget, sometimes to the byte.

**weights: 519.2 MiB of 519.2 MiB budget (99.998% used, 13 KB slack)**

## What fits your machine?

Pick your hardware and this page scans Hugging Face's most-downloaded models for ones shoehorn can fit to your budget — ranked by the quality your memory affords. Runs entirely in your browser.

## Install

shoehorn needs [llama.cpp](https://github.com/ggml-org/llama.cpp)
on your PATH as the inference backend (the Homebrew install pulls it in for you).
Then `shoehorn ui`

opens the local app — pick a model, press one
button, chat.

`brew install notactuallytreyanastasio/shoehorn/shoehorn`

Or from source: `cargo install --path .`

after cloning [the repo](https://github.com/notactuallytreyanastasio/shoehorn).
All [releases](https://github.com/notactuallytreyanastasio/shoehorn/releases).

## One button, your whole budget

The local web app measures your machine, streams the fit, renders the budget as a tape measure, puts a perplexity number on what the fit cost, and ends at a Chat button.