Mistral ships Le Chat – enterprise AI assistant that can run on prem

[codingbot3000]

I think this is a game changer, because data privacy is a legitimate concern for many enterprise users.

Btw, you can also run Mistral locally within the Docker model runner on a Mac.

[simonw]

There are plenty of other ways to run Mistral models on a Mac. I'm a big fan of Mistral Small 3.1.

I've run that using both Ollama (easiest) and MLX. Here are the Ollama models: https://ollama.com/library/mistral-small3.1/tags - the 15GB one works fine.

For MLX https://huggingface.co/mlx-community/Mistral-Small-3.1-24B-I... and https://huggingface.co/mlx-community/Mistral-Small-3.1-24B-I... should work, I use the 8bit one like this:

  llm install llm-mlx
  llm mlx download-model mlx-community/Mistral-Small-3.1-Text-24B-Instruct-2503-8bit -a mistral-small-3.1
  llm chat -m mistral-small-3.1

The Ollama one supports image inputs too:

  llm install llm-ollama
  ollama pull mistral-small3.1
  llm -m mistral-small3.1 'describe this image' \
    -a https://static.simonwillison.net/static/2025/Mpaboundrycdfw-1.png

Output here: https://gist.github.com/simonw/89005e8aa2daef82c53c2c2c62207...

[kergonath]

> I think this is a game changer, because data privacy is a legitimate concern for many enterprise users.

Indeed. At work, we are experimenting with this. Using a cloud platform is a non-starter for data confidentiality reasons. On-premise is the way to go. Also, they’re not American, which helps.

> Btw, you can also run Mistral locally within the Docker model runner on a Mac.

True, but you can do that only with their open-weight models, right? They are very useful and work well, but their commercial models are bigger and hopefully better (I use some of their free models every day, but none of their commercial ones).

[lolinder]

Game changer feels a bit strong. This is a new entry in a field that's already pretty crowded with open source tooling that's already available to anyone with the time and desire to wire it all up. It's likely that they execute this better than the community-run projects have so far and make it more approachable and Enterprise friendly, but just for reference I have most of the features that they've listed here already set up on my desktop at home with Ollama, Open WebUI, and a collection of small hand-rolled apps that plug into them. I can't run very big models on mine, obviously, but if I were an Enterprise I would.

The key thing they'd need to nail to make this better than what's already out there is the integrations. If they can make it seamless to integrate with all the key third-party enterprise systems then they'll have something strong here, otherwise it's not obvious how much they're adding over Open WebUI, LibreChat, and the other self-hosted AI agent tooling that's already available.

[abujazar]

Actually you shouldn't be running LLMs in Docker on Mac because it doesn't have GPU support. So the larger models will be extremely slow if they'll even produce a single token.

[burnte]

I have an M4 Mac Mini with 24GB of RAM. I loaded Studio.LM on it 2 days ago and had Mistral NeMo running in ten minutes. It's a great model, I need to figure out how to add my own writing to it, I want it to generate some starter letters for me. Impressive model.

[raxxorraxor]

I think the the standard setup for vscode continue for ollama is already 99% of ai coding support I need. I think it is even better than commercial offerings like cursor, at least in the projects and languages I use and have tested it.

We had a Mac Studio here nobody was using and it we now use it as a tiny AI station. If we like, we could even embed our codebases, but it wasn't necessary yet. Otherwise it should be easy to just buy a decent consumer PC with a stronger GPU, but performance isn't too bad even for autocomplete.

[Palmik]

I really don't see the big deal. Gemini also allows on-prem in similar fashion: https://cloud.google.com/blog/products/ai-machine-learning/r...

[nicce]

> Btw, you can also run Mistral locally within the Docker model runner on a Mac.

Efficiently? I thought macOS does not have API so that Docker could use GPU.

[v3ss0n]

What's the point when we can run much powerful models now? Qwen3 , Deepseek

[ulnarkressty]

I think many in this thread are underestimating the desire of VPs and CTOs to just offload the risk somewhere else. Quite a lot of companies handling sensitive data are already using various services in the cloud and it hasn't been a problem before - even in Europe with its GDPR laws. Just sign an NDA or whatever with OpenAI/Google/etc. and if any data gets leaked they are on the hook.

[dzhiurgis]

How many is many? Literally all of them use cloud services.

[ATechGuy]

Why not use confidential computing based offerings like Azure's private inference for privacy concerns?

[beernet]

Mistral really became what all the other over-hyped EU AI start-ups / collectives (Stability, Eleuther, Aleph Alpha, Nyonic, possibly Black Forest Labs, government-funded collaborations, ...) failed to achieve, although many of them existed way before Mistral. Congrats to them, great work.

[Palmik]

It feels to me they turned into a generic AI consulting & solutions company. That does not mean it's a bad business, especially since they might benefit from the "built in EU" spin (whether through government contracts, regulation, or otherwise).

One can deploy similar solution (on-prem) using better and more cost efficient open-source models and infrastructure already.

What Mistral offers here is managing that deployment for you, but there's nothing stopping other companies doing the same with fully open stack. And those will have the benefit of not wasting money on R&D.

[stogot]

I’m wondering why. More funding, better talent, strategy, or something else?

[bobxmax]

is Mistral really doing anything here? Llama models are open source, Cohere runs on prem etc

[retinaros]

what did they achieve exactly?

[85392_school]

This announcement accompanies the new and proprietary Mistral Medium 3, being discussed at https://news.ycombinator.com/item?id=43915995

[Havoc]

Not quite following. It seems to talk about features common associated with local servers but then ends with available on gcp

Is this an API point? A model enterprises deploy locally? A piece of software plus a local model?

There is so much corporate synergy speak there I can’t tell what they’re selling

[frabcus]

They mention Google Cloud Marketplace (not Google Cloud Platform), this seems to be their listing there:

https://console.cloud.google.com/marketplace/product/mistral...

Which says:

"Managed Services are fully hosted, managed and supported by the service providers. Although you register with the service provider to use the service, Google handles all billing."

My assumption is that they're using Google Marketplace for discovery and billing, and they offer a hosted option or an on-prem option.

But agreed, it isn't clear!

[_pdp_]

While I am rooting for Mistral, having access to a diverse set of models is the killer app IMHO. Sometimes you want to code. Sometimes you want to write. Not all models are made equal.

[the_clarence]

Tbh I think the one general model approach is winning. People don't want to figure out which model is better at what unless its for a very specific task.

[downsplat]

Same here. Since I started using LLMs a bit more, the killer step for me was to set up API access to a variety of providers (Mistral, Anthropic, Gemini, OpenAI), and use a unified client to access them. I'm usually coding at the CLI, so I installed 'aichat' from github and it does an amazing job. Switch models on the fly, switch between one-shot and session mode, log everything locally for later access, and ask casual questions with a single quick command.

I think all providers guarantee that they will not use your API inputs for training, it's meant as the pro version after all.

Plus it's dirt cheap, I query them several times per day, with access to high end thinking models, and pay just a few € per month.

[binsquare]

Well that sounds right up the alley of what I built here: www.labophase.com

[I_am_tiberius]

I really love using le chat. I feel much more save giving information to them than to openai.

[victorbjorklund]

Why use this instead of an open source model?

[_mlbt]

> our world-class AI engineering team offers support all the way through to value delivery.

[starik36]

I don't see any mention of hardware requirements for on prem. What GPUs? How many? Disk space?

[tootie]

I'm guessing it's flexible. Mistral makes small models capable of running on consumer hardware so they can probably scale up and down based on needs. And what is available from hosts.

[adamsiem]

Parsing email...

The intro video highlights searching email alongside other tools.

What email clients will this support? Are there related tools that will do this?

[guerrilla]

Interesting. Europe is really putting up a fight for once. I'm into it.

[fortifAI]

Mistral isn't really Europe, it's France. Europe has some plans but as far as I can tell their goal isn't to make something that can really compete. The goal is to make EU data stay in the EU for businesses, meanwhile every user that is not forced by their company sends their data to the US or China.

[resource_waste]

Expected this comment.

Mistral has been consistently last place, or at least last place among ChatGPT, Claude, Llama, and Gemini/Gemma.

I know this because I had to use a permissive license for a side project and I was tortured by how miserably bad Mistral was, and how much better every other LLM was.

Need the best? ChatGPT

Need local stuff? Llama(maybe Gemma)

Need to do barely legal things that break most company's TOS? Mistral... although deepseek probably beats it in 2025.

For people outside Europe, we don't have patriotism for our LLMs, we just use the best. Mistral has barely any usecase.

[qwertox]

This is so fast it took me by surprise. I'm used to wait for ages until the response is finished on Gemini and ChatGPT, but this is instantaneous.

[amelius]

I'm curious about the ways in which they could protect their IP in this setup.

[badmonster]

interesting take. i wonder if other LLM competitors would do the same.

[mxmilkiib]

the site doesn't work with dark mode, the text is dark also

[phupt26]

Another new model ( Medium 3) of Mistral is great too. Link: https://newscvg.com/r/yGbLTWqQ

[m-hodges]

I love that "le chat" translates from French to English as "the cat".

[Jordan-117]

Also, "ChatGPT" sounds like chat, j’ai pété ("cat, I farted")

[debugnik]

Their M logo is a pixelated cat face as well.

[AceJohnny2]

I wonder if they mean to reference the Belgian comic Le Chat by Philippe Geluck.

https://en.wikipedia.org/wiki/Le_Chat

[caseyy]

This will make for some very good memes. And other good things, but memes included.

[iamnotagenius]

Mistral models though are not interesting as models. Context handling is weak, language is dry, coding mediocre; not sure why would anyone chose it over Chinese (Qwen, GLM, Deepseek) or American models (Gemma, Command A, Llama).

[tensor]

Command A is Canadian. Also mistral models are indeed interesting. They have a pretty unique vision model for OCR. They have interesting edge models. They have interesting rare language models.

And also another reason people might use a non-American model is that dependency on the US is a serious business risk these days. Not relevant if you are in the US but hugely relevant for the rest of us.

[tootie]

I flip back and forth with Claude and Le Chat and find them comparable. Le Chat always feels very quick and concise. That's just vibes not benchmarks.

[amai]

Data privacy is a thing - in Europe.

[FuriouslyAdrift]

GPT4All has been running locally for quite a while...

[curiousgal]

Too little too late, I work in a large European investment bank and we're already using Anthropic's Claude via Gitlab Duo.

[croes]

Is there are replacement for the Safe Harbor replacement?

Otherwise it could be illegal to transfer EU data to US companies

[jagermo]

AI data residency is an issue for several of our customers, so I think there is still a big enough market for this.

[alwayseasy]

Your bank sticks with any tech that comes out first? How is this a cogent argument?