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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 am wondering what is keeping them back, though: Money? Compute? Skills? Training data? My fear is that you are really only getting really good models by training on very dubious data (outputs from the frontier models etc) and that Mistral is too European and too enterprisey to take those risks.
Or at least there’s been a lot of noise about that.
Not ruthless enough and no backing by a corrupt govt administration that has no morals but focuses on self-enrichment instead.
Might sound drastic but I think that's actually closer to the truth thn everbody likes to admit.
> My fear is that you are really only getting really good models by training on very dubious data (outputs from the frontier models etc) and that Mistral is too European and too enterprisey to take those risks.
Exactly.
I think an European company, taking Chinese models, perhaps doing its own post-training on them and training the Chinese-ness out, with a great chat service, enterprise API and coding agent, could be pretty valuable in itself.
Considering all their talk about new DCs and compute, and a few offhand comments, it sounded to me that compute is a big limitation.
All of the above and more. Everything holding Mistral back is the same thing that has held Europe back from competing in the entire digital revolution. See this 1991 article lamenting the loss of any viable European PC manufacturer: https://www.nytimes.com/1991/04/22/business/europe-stumbles-...
Mistral being in Europe is disadvantaged with:
1. Money: less diverse private pension fund environment = less LPs to invest in VC funds = less VC dollars to invest in new ventures. European money is vacuumed out of the private sector into state pension funds and dumped into low yielding government bonds. This starves the private sector of capital while inflating the % of GDP driven by government spending every year (government pension funds buying government bonds in circular fashion enable runaway deficit spending...just like circular AI infrastructure spending).
2. Talent & compute: due to #1, Silicon Valley can outbid Europe for the best talent and hardware. Watch an OpenAI launch video and listen to all the European accents.
3. Local market fragmentation: Europe is a collection of countries that pretend to work together while not even having a unified capital market. The average EU citizen can barely communicate with their neighbor in a common language beyond the level of a toddler (english fluency is massively overstated by Americans who only experience tourist capitals).
4. Regulatory disadvantages: In everything from company regs, employee regs, unions, privacy regs, data portability regs, etc.
It's not "culture" or Europeans being "lazy" as most people would claim. There's currently thousands of young french people working 80 hour weeks creating dumb consulting powerpoints or legacy investment banking deal memos as we speak. Ambitious people exist everywhere in equal proportion, they're just working on the wrong things.
Europe can't compete in the digital revolution the same way they could compete in the industrial revolution due to various system design choices. Culture is simply the aesthetically observed byproducts of system design.
Agreed. My own anecdote: my company is global and for the past 6 months, we've been working on getting regulatory and legal approval for an LLM-based feature. The initial proposals of going live in all of our markets have been pared back to exclude Europe altogether due to the regulatory environment.
When I took part in company-wide gen AI councils that reviewed new product rollouts, it seemed like there was a definite hesitation from higher ups from pushing out any leading edge features to European markets. And it's not that the regulations would necessarily block these features from going live but that they'd increase implementation costs to the point where it wouldn't be worth it.
Not true in my experience: even German waiters in small towns tend to have pretty fluent English.
Which countries do that? The ones in NL actually invest in US big tech.
Once Europe stops investing in USA, Europe will be better able to compete.
> Talent & compute: due to #1, Silicon Valley can outbid Europe for the best talent and hardware. Watch an OpenAI launch video and listen to all the European accents.
That just denotes European students are high quality.
Brain drain is happening due to bullying and fascism. The extend of longterm danage of current administration is unclear.
> Local market fragmentation: Europe is a collection of countries that pretend to work together while not even having a unified capital market. The average EU citizen can barely communicate with their neighbor in a common language beyond the level of a toddler (english fluency is massively overstated by Americans who only experience tourist capitals).
Bollocks. I have been in Berlin and Munich various times past decades, and people there speak English very well. Nowadays, translation is a profession which got hit by the AI club.
The people in the rural areas don't have to work together with other people from rural areas. They just need websites and tooling in their native language, or a major language.
Case in point: the French company Mistral has Dutch company ASML has one of their major investors. If you go to Eindhoven area (Netherlands mini SV called Brainport Eindhoven), you get away with English perfectly fine, and there too you will hear all kind if accents.
There is definitely a lot of truth to that. Maybe a bit of an arbitrary measure, but these are the nationalites of the people that wrote the "Attention is all you need" paper. Pretty revealing I find:
Ashish Vaswani: India
Niki Parmar: India
Jakob Uszkoreit: Germany
Llion Jones: Wales (UK)
Aidan Gomez: Canada
Łukasz Kaiser: Poland
Illia Polosukhin: Ukraine
Noam Shazeer: USA
Personally, I would much rather have good public pensions and health-care, than A.I agents.
There are supposedly streamlined paths for local residents, but I had to go through the standard corporate pipeline. I spent three months fighting a bizarre catch-22 between my notary (who cost €3k+) and the bank. To open the account, I had to prove I deposited €10k in capital. But I couldn't make the deposit without an active bank account. On top of that, the bank's compliance team kept arbitrarily canceling my application due to "incorrect answers"... refusing to tell me what the errors actually were and forcing me to restart the entire process ab initio.
I finally just gave up. I wrote off the €3,000 notary fee and €1,000 in registered office costs as a sunk cost, and incorporated a US LLC instead. It took under 10 minutes, no notary, fees of $25 since I did it myself, plus another 20 minutes to open the business bank account.
There was no commercial reason to choose Austria; it was purely sentimental. My ancestors were entrepreneurs in Linz and Vienna, and I loved the idea of renewing that legacy. But the sheer weight of the bureaucracy managed to kill about 99% of the early-stage startup enthusiasm you normally rely on to get a new project off the ground.
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
This is tangential: and forgive my ignorance here, but is there an inherent reason why there aren't smaller, focused models from the frontier model providers?
I'm thinking something like a software-specific subset of Opus that is the default for use in Claude Code. Smaller, cheaper to deploy and consume, maybe faster.
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.
Even though Mistral 4 has 6B active parameters per token (allowing 3-3.5 per token parameters to be loaded on a 4090), the ~240GB download + storage is pushing the limits of being able to try this out locally, especially if you are downloading and evaluating multiple models.
It also makes it harder for other people to make downstream finetunes like with what happened with the older Mistral/Magistral models.
They'll end like Dailymotion, just a zombie company.
Foundation model labs should be building very large reasoning models, then leaving it to the community to distill them down.
You can't scale a small model up, but you can scale a small model down.
I'm convinced the only way we'll have a seat at the table in the future and avoid total runaway takeoff is if there are very large models within 80% of the capabilities of the frontier models. Tiny RTX models do diddly squat to remain competitive.
Build open weights models for running on H200s. I'll spin them up on RunPod or Lambda.
I have used Mistral models out of pure ideology for web agents and the like which aren't doing a lot of heavy lifting.
Our evals are pretty complex so we only recently started testing ~30B class models, which are now becoming quite smart (on par with the frontier from 1 year ago). Mistral is far behind, but I'm rooting for them.
Data at https://gertlabs.com/rankings
Fully agree to your point though, Mistral in general is far behind where I'd expect and Qwen in particular is crushing it at the smaller sizes.
Personally, I'd consider anything 20B params and above a "medium" model. Small being <20B and large >100B. I think obviously we can get to the huge 1-2T param models, but frankly the margin of accuracy improvement for the speed hit is kinda insane (1-2% for many metrics).
1. tiny <2-3B -- easily runnable on lower-spec hardware
2. small 4-8B -- runnable on 8GB GPUs
3. medium 9-12B -- runnable on 12GB GPUs
4. large 13-24B -- runnable on 16GB (for the lower end models) and 24GB GPUs
5. very large 25-32GB -- runnable on 32GB GPUs
6. huge >32GB -- not easily runnable on consumer GPUs without compromising performance (offloading layers to the CPU/RAM), quality (heavy quantization, esp. at <= Q4), or price (investing in multi-GPU setups and/or server-grade hardware).
You could possibly split huge down further, as 70GB models (e.g. llama 3) are easier to get working than >120GB models and 1TB models are completely intractable.
1. tiny <2-3B -- could run in a browser even, mac neo
2. small 4-8B -- last of browser options, MacBook Air base
3. medium 9-24B -- 32GB machine, air or pro notebook or mini
4. large 25-48B -- 64GB, pro notebook or mini
5. x-large 49-100B -- 128GB MacBook Pro or Studio
6. Huge > 100B -- 256/512GB Mac Studio
I don’t really disagree with your post, but this is not exactly right. That subreddit seems to go from hype train to hype train every week, I haven’t found anything really insightful in it for quite a while now.
Europe shot itself in the dick with this hastily implemented at the height of mass hysteria bullshit and now no sane company will build anything there. an AI startup in the US or China can be a boy and his computer. in Europe, the boy needs a dozen lawyers.
Mistral's sinking into irrelevancy despite the head start they had, the very promising early models they released, and the funding they receive, might very well be the consequence of trying to comply with all that crap.
- manipulates, including subliminally (hope you'll like your subliminal Ads mixed into your LLM output)
- profiling for social scoring
- automated thread labeling as an individual, with no human supervision
- facetracking databases
- emotional and "well-being" monitoring at work or in schools
- + many other kinds of surveillance tools.
I hope you are joking.
edit:
For context this was a snippet of prohibited use, which the fines listed on Wikipedia (theoretically apply to), https://artificialintelligenceact.eu/article/5/
There is a lot of Europeans working on AI, it's just that a lot of them work for American companies. Because of money.
Thank you for reminding us that all animals are equal, but some are more equal
I hate the fake European foreign-backed right-wing parties but they didn't cause the current situation.
But I'm afraid it might be too late as the cancer spread and did too much damage. Insane regulations, no energy, looming demographic/pension crisis, tax hell, and collapsing industries.
While the EU loves its regulation, I still feel it’s too early to write it down in the AI race. It will not replace Anthropic or OpenAI any time soon, but even Google and Meta fail to do that.
If AI continue to grow and expand, there is enough space for many more unicorns.
[0] https://techcrunch.com/2026/05/28/why-paris-may-be-the-most-...
And yet another time they will be thinking aloud in few year "what happened that we are fully dependent on USA?"
The gist of it is very simple - depending on the risk of what you're doing with AI, you have to document why it did what it did, and be able to explain it; or you can't use it at all. So if you're using AI for mass surveillance, you can't; if you're using it for treating loan applications you need to be able to explain why it approved/denied; if it's a customer service chatbot, do whatever, nobody cares.
Not only is burden of the legislation fairly low (and a lot of it hasn't come into force yet), it is extremely reasonable. No, sorry, we don't want a UnitedHealthcare using a broken algorithm on purpose to deny as much care as possible and hiding behind computer says no.
How so? Catching up is easier and cheaper than spearheading the lead.
Mistral leaning into on-prem and European-hosted models is very smart.
Who else will buy their AI?
and what other options do they have?
Devstral is getting better, it’s the Vibe harness that’s holding it back (I think). I can see how that would drive some business as well.
Their chat thingie isn’t very well positioned, but gets results. Could be an euro or two per month, maybe bundled with some more features. It’s not like Mistral has no options, if anything they’re just a bit complacent and not ambitious with their plans.
It always felt to me this (enterprise B2B) was where European startups went to die.
What is "weird training biases" to us might not be weird to them and vice versa. Just ask the Chinese what they think about LGBTQ+, Japanese, pride parades, Islam and colored minorities.
Every nation has its own biases injected in its domestic LLMs at this point. Otherwise they risk getting in trouble for hate speech/disinformation in the jurisdiction where they operate.
Same how Google Maps cleverly biases the lines of disputed borders based on where you are viewing it from. Or how Google maps switched 'Gulf of Mexico' to 'Gulf of America' in an instant when the orange man signed the paper. Google won't want to anger the US administration the same way how Mistral won't want to anger France and the EU, so Mistral will have all the EU prime directives injected into its LLMs no matter if they're ludicrous or not. The law is the law whether you agree with it or not. Companies want to survive and will pander to whatever the whims the regime they live under are at the current moment regardless of what is right or wrong.
But if I'm using a LLM for personal projects or generating a photorealistic choreographed fight between Tom Cruise and Brad Pitt, I don't care what its political biases are, I care if it solves my problem better and cheaper than the competition, and here the Chinese models could end up winning the consumer market, which is why you see Mistral and other EU alternatives focusing exclusive on B-2-B corporate market.
Or is this a case of the humans, now preparing for the excuse it was the AI failure?
"BNP Paribas Sentenced for Conspiring to Violate the Trading with the Enemy Act" - https://www.justice.gov/archives/opa/pr/bnp-paribas-sentence...
"BNP Paribas caught up in French money laundering investigation" - https://www.reuters.com/business/finance/bnp-paribas-caught-...
"BNP Paribas faces $246m fine in currency scandal" - https://www.bbc.com/news/business-40635070
"BNP Paribas caught in a Cypriot money laundering investigation" - https://www.lemonde.fr/en/les-decodeurs/article/2023/12/26/b...
In Money Laundering their track record is unmatched: https://violationtracker.goodjobsfirst.org/parent/bnp-pariba...
Assuming BNP Paribas leadership wants to stop the corruption of course.
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
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.
I really like the direction and the transparency of Mistral, among those players.
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)
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?
OTOH such things can be quite defensible, they just rarely become anything like as profitable.
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 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.
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.
See what happened to Aleph Alpha...
The papyrus talk was awesome though.
https://ainowinstitute.org/
Almost feels like name squatting
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.