They do! E.g. Cursor. See earlier discussions like "Cursor IDE support hallucinates lockout policy, causes user cancellations"[1].

[1]: https://news.ycombinator.com/item?id=43683012

It's "good" from the perspective of a company that's annoyed to have to spend money on actually fixing things.

Sample of two, but I'm assuming french companies don't like to being contacted n English.

The hard part is justifying pure LLM development financially. Models are all very similar. OpenAI justified it originally by being a 'charity' dedicated to pure research (not financial). Anthropic justified it by saying OpenAI didn't care enough about safety and splitting from them (not financial). Elon justified it by saying that AI would be woke and untruthful unless he built Grok (not financial). Google did Gemini because, well, they're where it all started and because AI research was one of the core missions Larry & Sergey gave it when they started it (but then sat on it for financial reasons).

Then there's the Chinese models. It's unclear what their motives are tbh. I've never seen a really great explanation, only hypotheses. But as they're giving them away for free or very underpriced, their motivation doesn't seem to be financial either.

But Mistral is a normal company. It doesn't have rich backers giving it money based on narratives about cosmic destiny, so it needs to justify what it's doing with ROI. So that more or less rules out large scale LLM training.

There's also EU regulation to consider. When I looked at this in the past I found lots of odd rules that kill off any chance of having a European tech industry. The UK had one that said you could only crawl the internet for research purposes!

https://knowledgerights21.org/news-story/the-uks-copyright-l...

And without the First Amendment you're at much greater risk of being prosecuted for things your models say. See how Germany has taken Google to court over things its models put in its search result pages.

So the benefit isn't clear and the legal risks are very high.

The only way to avoid this is to stop playing the game as it is today, and start using proper industrial policy to build up a competitive industry (like China did). There has been no appetite for that the last decades, but Trump is making it completely clear that the state is back, and Europe is slowly acknowledging it as well.

and now they get to sit in the chair in the corner and watch as its citizens use American and Chinese models.

Leanstral 1.5 - June 30, 2026 An updated Lean 4 formal proof engineering model optimised for automated theorem proving and autoformalization. 119B total parameters, 6.5B active.

https://web.archive.org/web/20260630223430/https://docs.mist...

Technical questions are unfortunately hit or miss. I'm lately pretty much always using a system prompt that emphasizes short answers [1], and Opus regularly one-shots it while Mistral needs a follow up. I use big-AGI as a model router [2] (dumb name, great software), which makes switching midway very easy though. For coding I'm still using Claude Code mostly out of inertia (although I really want to move to an OSS harness) and the one time I tried their `vibe` tool months ago it was a bit rough.

Mistral TTS with diarization is also great and cheap. That's the only thing for which I use their web UI.

[1] Give a short but helpful answer to the question the user asks. When helping with a computer-related task, unless the user asks, don't give any installation or setup instructions, but just get straight to the point. When the user asks a follow up question, give a more complete and longer answer while still not overexplaining. When the user prefaces the question with "short mode off" in any question, give a full and well considered reply.

[2] https://github.com/enricoros/big-AGI

Mistral themselves focus more on b2b; financial services, manufacturing, stuff like that, and they get some big clients that way.

Despite not being their target, I started using them because they have many open models. I continue using them because, yeah EU, but also because the community is great and the tool makes me think more than Claude does. Last, I stick with them because they are one of the few AI companies that are up-front about their environmental impact and are actually trying to minimize it while still providing a decent product.

We complain too much about not having enough major competitors in the IT space, to not support a burgeoning one even if it's less powerful than SOTA labs

I’ve also found it very good at pulling info from pdfs. Even a complicated festival with multiple venues and timetables.

We cannot use open source LLMs on-prem, I asked. So that's basically a hard requirement to use mistral, even though Chinese models are strictly better on every dimension.

I am. I use them primarily through their vibe CLI.

Reason is simple: They are cheaper (by almost one order of magnitude compared to Claude) and still do the job pretty well.

For small programming tasks, quick prototyping, refactoring or anything verbose and not requiring a context too large: I first go to Mistral and then eventually to Claude if I'm unsatisfied.

I also found out some of their models to be more responsive than OpenAI ones (which is not so surprising considering the size).

My tasks are mainly C++ and Python programming. People in other languages might not share my enthusiasm.

But I admit I only consider them because they're from France. Haven't seen a dimension where they're competitive for general users

[1]: https://github.com/maxim/ringbinder

Are you trying to instruct me like an LLM?

However these days I usually have Qwen 3.6 27B already loaded so I mostly just use that instead.

LLMs are a near-afterthought at this point if you don’t have data residency requirements. I love them and they’re slightly underrated, their models are consistently well-trained, open, but as you note, behind. There is no metric that will say they’re ahead in anything.