Comment by doctorpangloss

I use their Voxtral Mini STT audio model to automatically transcribe my podcasts into markdown. Out of all the STT models I've tried, it's both the best performing and one of the cheapest! It's really accurate, feeding the episode notes and the podcast description ensures all names are properly spelled, and speaker diarization works really great. (I just do a Gemini flash pass at the end to identify the speakers, so it shows the host name instead of "Speaker 1")

For writing and languange learning it's very decent, especially Mistral Large. The pricing is very good too. I really like the consistently low time to first token and good token per second. Claude, especially in the past, would be very inconsistent, often with outages. Mistral mostly just always works and is very fast.

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

We are not Mistral's target audience. For instance I don't know if Leanstral performs the best as a "formal proof engineering model optimised for automated theorem proving and autoformalization" because I don't even know wth that is or who else does it.

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.

OCR is off the charts good on every metric you can think of.

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.

Mistral medium is considerably better at writing than Opus.

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

A few months ago, I had some data cleaning to do; their small model was surprisingly efficient and got the job done for 0.2x what I expected to run (Anthropic Sonnet / Haiku). Their TTS / STT is also roughly at the frontier, at least for French.

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

I use it as my workhorse for coding and general chat questions, because it's good enough 80% of the time, and indeed it's french/european (with heavy US capital tho...).

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

> Mistral because it performs the best, by whatever secular metric of your choosing?

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.

>Just focus on answering the question.

Are you trying to instruct me like an LLM?

For a defense project we're working on, we basically have a hard requirement to use european cloud provider + european llm

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 like the models for creative writing. They have a distinct voice that is different from the other llms.

I use it because it’s a simple, convenient and cheap OCR api. Specifically via my ringbinder[1] tool.

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

I use it because EU and API pricing is decent to me. And support is awesome also. They reply the same day or at most the next day, and they follow the ticket great. It isn't that bad, but neither the best.

I still prefer Mistral Nemo 12B for text summarisation tasks. It has a nice style. The Mistral Small 24B is also decent. I have a YouTube transcript summariser which I like these for.

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

I used them because they had the fastest chat response. (Dont think that’s the case anymore, and they introduced some UI blocking feature on load which is irritating, but still use it mainly due to habit)

I liked that their website didn’t ask for my phone number, IIRC.

just used mistral for a database/scraping creation tool and ended at <10k€ in token costs (via openrouter), beating gpt5.4-mini in output quality and speed and costs after actual testing A/B fairly. so its a super scoped task to be performed hundreds of thousands of time for some automation and mistral just did it better across all dimensions that gpt-5.4-mini. of course thats not a headline in terms of frontier model competitiveness, but for "the boring parts" it just was flat out better than anything else consistently. bonus points it handles mixed-language-content with nuances surprisingly well to turn web content in the wild into structured data really good and fast.

I use Claude with Kiro at work and at home Mistral stuff with pro subscription for coding and research. I don't see a fundamental difference between them in results, at least with what I use them for. The cost is lower too, but it is not the only reason why I won't use Claude at home.

Vibe (the CLI Kiro-like tool) feels more "Claude-ish" as it has more terse answers, while the Le Chat can get quite chatty if you really push it ( * ). Prompting it right gets Le Chat more focused and back to being terse.

( * ) Le Chat is by default in "Fast" mode. It also has "Think" and "Research", but I've not felt the need to use those yet.

As a practical example:

I'm doing some on-and-off family research when I can and have some time since it's the rabbit-holest of all rabbit-holes.

I already knew the answers, but decided to test how well Le Chat does. I fed a 208 year old church book page to Le Chat and asked if it can read that handwritten old cursive Swedish and tell me the contents. Le Chat had a look and then explained it could not, but it pointed me to something I had completely missed before, despite having looked for it: The Swedish Lion OCR model by Riksarkivet (Swedish National Archives) which is purpose-built for OCRing such records (the tool by READ-COOP including The Swedish Lion is at http://www.transkribus.org/).

Then, Transkribus confirmed my existing information and confirmed that I can kind of sort of read that cursive too. I did not expect any new findings here, just to verify against known facts and things were OK. The tip to Transkribus was very nice and I'll be using that tool more.

After this, I asked if Le Chat could dig up some more information about the person (it's a Swedish-Russian noble family connection so a lot of written material exists). Le Chat went about it, summarized real web pages, and the information matched with what I knew already, which was good, no hallucinations or such. I prompted Le Chat further towards the parents and grandparents and so on, it kept on replying with factual summaries and references to web pages that actually exist.

This was all in all very good. For what I earlier spent perhaps a weekend or two (taking like two weeks of wall clock time) in total, I could dig up basically the same information, with sources referenced, in a fraction of the time. Even if Le Chat could not read the page, it pointed to Transkribus and that was very helpful.

The point is: Mistral performs well for me and I see no reason to use something else. There's also the option to turn off the "use my inputs to learn the model". I don't know if Claude has it or not.

Edit: formatting Edit: READ-COOP SCE does the Transkribus