> BNP Paribas runs Mistral models on-prem for KYC in Belgium, with sensitive data staying within the bank's walls. Abanca is using agent orchestration to handle sensitive customer information at a huge scale (2 million customers in their app). For European companies in regulated industries, this is a good alternative to relying on US hyperscalers.
Mistral leaning into on-prem and European-hosted models is very smart.
My take is that Mistral is not focusing on generating contents such as code, images, or videos. They focus on multi-lingual models, OCR, voice, and others I believe. Their model intro page manifests that although it always confuses me because it's too colorful and there are too many categories, not to mention model names. I hope their decisions will pay off.
> Abanca is using agent orchestration to handle sensitive customer information at a huge scale (2 million customers in their app).
Maybe my perspective is skewed on what "huge scale" means, but 2 million users? That's like a few hundred megabytes of data? Or a couple GBs if there's a lot of per-user data?
I was at the event, and was impressed by the attendance, all the leaders from the major european listed companies were there.
Also interesting to note the number of partners they invited. Going from Microsoft, Accenture and EY to startups like alpic.ai or lingo.dev . Seems like they are ramping up their M&A game too
OK, I'm 100% rooting for both Mistral and task focused small models.
But Mistral has fall really far behind since 2025Q3. It seems they can't get good reasoning models working at even medium context sizes, which is necessary to be at the table right now.
Gemma4 and Qwen3.6 are currently best in the small size; Mistral's "small" model has ~4x the parameter count at 120B and isn't even competing with models a quarter its size.
Back one year ago with Mistral Small 3.1 they were keeping up, but they've fallen into irrelevancy right now.
If Mistral seriously wants to play the on-prem and small task-specific model game, a decent proxy would be to build models that get the r/localLlama crowd excited
I find Mistral Medium 3.5 with OpenCode is perfectly fine if you're willing to talk to it in a more fine-grained way about actual code. For me that's fine because even with huge frontier models I don't like trying to vibe prompt like a product manager.
Mistral is entering the "let's extract has much money from EU taxpayers as we can" phase of European tech company which did not get bought by a US one.
They'll end like Dailymotion, just a zombie company.
I think it really depends on what you’re doing. I use mistral for many tasks in https://phrasing.app and they blow models many times their size out of the water.
None of my tasks use reasoning though (reasoning actually kills the performance) so perhaps that’s why. Still, I just had to rewrite my pipeline, and mistral was both faster, cheaper, and substantially better than any alternative
I've said it before that Mistral is underrated. They are looking at real world use of LLMs and tooling. Bespoke models are very appealing to lots of non-tech centered companies and state agencies. Also, Mistral's actual platform is useful. While others are watching performance leaderboards like this is some eSports stream, they are building real world uses.
I really want Europe to be part of the AI development and research. And I strongly cheered for Mistral. But they are accumulating too much technological delay. This needs to be fixed, otherwise it will turn into yet another proof we are not able to run large tech with good results. Basically any Chinese lab is doing much better. It's not Mistral that created I don't want to say DeepSeek, but MiMo 2.5, Minimax 2.7, and so forth. There are only weaker and/or larger and slower (no MoE) models. Not good.
Wasn't even aware Mistral was around and I think that just shows you how irrelevant it has become and not a very good sign for EU in general when the best talent are working for American AI companies.
I saw Tibo's tweet a while back and it was basically a legitimate complaint about the extreme taxation he faced back in EU (France I think) and its pretty obvious how much of a hinderance top down centralized regulation is to innovation.
While I welcome competition and independence, nobody can argue with American innovation and its ability to attract the best of the best. Once it takes seat of the AI reigns there is very little chance for other countries to compete, very much similar to semiconductor field and how only a few select countries have the talent and monopoly over its particular supply chain.
It's clear to anyone looking in that whatever EU is doing is not working (not just AI) and will not work as they do not seem flexible or humble enough to steer itself.
I was also at the event and was pretty disappointed. Most of the talks were pretty low on information. I was at the “build” stage, which supposedly was the technical stage, but the talks there didn’t really go into technical specifics.
Sounds like they don’t have a moat at all. It’s like software consultancy with a data centre. And then the article mentions many customers using these models on prem (so data centre is not really a plus).
What’s stopping any country backed startup from fine-tuning small open source models?
Maybe because distilling small models from bigger ones that you control gives you better small models than fine-tuning from bigger models you don't control?
(I am not claiming it is the case, but stating this as an assumption)
No one in Europe will buy from a random startup, the consultancy part is a MUST to do businesses with big corps, banks, finances, insurances, governs, public administration ...
their moat is where they are based from and that they are making their own models. they have been before the distillation era in the open-weights model.
their model's efficacy for the mainstream comparisons may not be up to the task, but they are pivoting to their own lane for it. but the scope beyond the local market, it is yet to be seen.
I believe that Mistral team is doing the best they can do. I like the directions they push; open models for various tasks, on-prem has a lot of potential. Sure, I use Claude code mostly for coding. But there are so many tasks other than just coding. Even for coding, eventually, I am certain they will catch up and Vibe becomes tolerable soon.
Does anyone else always read "Mistrial" instead of "Mistral"? Always think I'm about to read a juicy gossip piece, and let down when it's just a standard update on an AI company.
edit A lot of AI company names are really strange, actually. "Claude" is really the best a trillion+ dollar company could come up with? It sounds like the name of a grandpa or something.
I just got an email from them saying that they’re retiring some (most?) of the dedicated models like devstral gradually through August and one should now use the general model. Cost grows exponentially
Devstral 2 (devstral-2512 and devstral-latest) → We recommend transitioning to Mistral Medium 3.5 (mistral-medium-3-5 with reasoning_effort set to "high"), a stronger model, priced $1.5/$7.5 per million input/output tokens (change from the previous $0.4/$2).
I have been on a lecture from great government IT person, they are evaluating models and are very unhappy about the situation, because they’d love to use Mistral, in some cases it’s the only EU based model they can use … and they know it’s really bad and falling more behind.
It is well possible that Mistral can make a profitable business by being bad, but still the only possible model for EU uses. Sad story, sad to witness.
Excited to see more about their partnership they with Alexa+. In agentic and tool-calling, Mistral’s model architecture excels at the exact structured JSON output Alexa needs to trigger APIs and smart home routines without breaking.
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[ 2.7 ms ] story [ 61.9 ms ] threadI really like the direction and the transparency of Mistral, among those players.
Mistral leaning into on-prem and European-hosted models is very smart.
Maybe my perspective is skewed on what "huge scale" means, but 2 million users? That's like a few hundred megabytes of data? Or a couple GBs if there's a lot of per-user data?
Also interesting to note the number of partners they invited. Going from Microsoft, Accenture and EY to startups like alpic.ai or lingo.dev . Seems like they are ramping up their M&A game too
But Mistral has fall really far behind since 2025Q3. It seems they can't get good reasoning models working at even medium context sizes, which is necessary to be at the table right now.
Gemma4 and Qwen3.6 are currently best in the small size; Mistral's "small" model has ~4x the parameter count at 120B and isn't even competing with models a quarter its size.
Back one year ago with Mistral Small 3.1 they were keeping up, but they've fallen into irrelevancy right now.
If Mistral seriously wants to play the on-prem and small task-specific model game, a decent proxy would be to build models that get the r/localLlama crowd excited
They'll end like Dailymotion, just a zombie company.
It's a very charitable take, as Mistral has never really left the realm of irrelevancy.
It's only a matter of time before EU falls back to hosting Chinese models in EU datacenters.
None of my tasks use reasoning though (reasoning actually kills the performance) so perhaps that’s why. Still, I just had to rewrite my pipeline, and mistral was both faster, cheaper, and substantially better than any alternative
How so? Catching up is easier and cheaper than spearheading the lead.
1. They give up on building competitive models. It’s time to drink wine not to struggle with competition
2. Because of #1 they will talk a bit about something around llms maybe coding agents , and after start talking about sovereignty.
I saw Tibo's tweet a while back and it was basically a legitimate complaint about the extreme taxation he faced back in EU (France I think) and its pretty obvious how much of a hinderance top down centralized regulation is to innovation.
While I welcome competition and independence, nobody can argue with American innovation and its ability to attract the best of the best. Once it takes seat of the AI reigns there is very little chance for other countries to compete, very much similar to semiconductor field and how only a few select countries have the talent and monopoly over its particular supply chain.
It's clear to anyone looking in that whatever EU is doing is not working (not just AI) and will not work as they do not seem flexible or humble enough to steer itself.
The papyrus talk was awesome though.
What’s stopping any country backed startup from fine-tuning small open source models?
(I am not claiming it is the case, but stating this as an assumption)
their model's efficacy for the mainstream comparisons may not be up to the task, but they are pivoting to their own lane for it. but the scope beyond the local market, it is yet to be seen.
edit A lot of AI company names are really strange, actually. "Claude" is really the best a trillion+ dollar company could come up with? It sounds like the name of a grandpa or something.
https://ainowinstitute.org/
Almost feels like name squatting
Devstral 2 (devstral-2512 and devstral-latest) → We recommend transitioning to Mistral Medium 3.5 (mistral-medium-3-5 with reasoning_effort set to "high"), a stronger model, priced $1.5/$7.5 per million input/output tokens (change from the previous $0.4/$2).
It is well possible that Mistral can make a profitable business by being bad, but still the only possible model for EU uses. Sad story, sad to witness.