# Unsloth releases quantized Mistral Large 4 that runs locally on Mac Studio

> Original title: Mistral Large 4 is here! We made some Unsloth quants & tested across many domains! 1bit retains 91% of top-1 accuracy across coding, agen...

- Source: Daniel Han
- Published: 2026-10-29T14:32:43.000Z
- Bad Influence: https://badinfluence.news/items/edds5rg2spo9zwhzn0s9ut69l
- Original: https://x.com/danielhanchen/status/2115814087498305811

## Summary

Unsloth released quantized GGUF versions of Mistral Large 4, a 1-trillion-parameter model, and says the 1-bit version runs locally on a Mac Studio. The post says the 1-bit build keeps 91% of top-1 accuracy across coding, agentic tasks, and math while being 80% smaller, at 223GB versus 1.1TB for FP8. The author says the quants work in Unsloth Desktop and thanks Mistral for day-zero access.

## Why it matters

The post gives the quantized file size, the accuracy retention figure, and the local runtime, which helps readers judge whether the model fits their hardware.

## Post

Mistral Large 4 is here! We made some Unsloth quants & tested across many domains! 1bit retains 91% of top-1 accuracy across coding, agentic tasks, math etc whilst being 80% smaller (223GB vs 1.1TB FP8)

They all work in Unsloth Desktop now! Thank you Mistral for day zero access!

![](https://badinfluence.news/api/img-proxy?u=https%3A%2F%2Fpbs.twimg.com%2Fmedia%2FHVzg7nmaUAATH9P.png&mode=thumb&exp=1793491200&sig=8b3f54d25630f278)

## Quoted post @UnslothAI

> Mistral Le Chonk can now run locally!
> 
> The 1 trillion parameter model runs on a Mac Studio with our 1-bit GGUF which retains 91% top-1 accuracy.
> 
> Le Chonk is the strongest Western open model to date.
> 
> GGUF: https://huggingface.co/unsloth/Mistral-Large-4-1T-A52B-GGUF
> Guide: https://unsloth.ai/docs/models/mistral-large-4

https://x.com/UnslothAI/status/2115812784189620265