I truly do not see the USP for Mistral other than being based in EU. It's former USP of setting up their models on-premises for clients is now moot with the proliferation of open frontier models. I'd love to be proven wrong but I don't see a path forward for Mistral at this point, given how far they're behind and their overall lack of competitive advantages for an AI Lab like access to hardware, cheap energy or a mass of AI talent.
They’ve built performance, enterprise utility, privacy, sovereignty, open innovation and strategic partnerships into their core story. It's quite a list. The models are opensource, Voxtral outperforms Whisper in terms of accuracy.
The GPT-OSS-120B release was pretty decent and you could run it on vLLM, Ollama and a bunch of other stuff on day one, despite MXFP4, are you not entertained? I mean, it's even close to GPT-5 mini in some benchmarks: https://llm-stats.com/
As for the Chinese models, yes, there are quite a few good ones.
For programming and development, my current daily driver is the Qwen3 Coder 480B model: https://qwen3lm.com/
Personally I think Claude still has the best results, but Qwen3 is loosely in the same ballpark and Cerebras inference is measured in thousands of tokens per second, in addition to giving me 24M tokens per day for 50 bucks a month in total. That was enough to get me to switch over.
Either way, happy to see what the future holds for Mistral, it's cool to have EU options too! Either way, more competition prevents complacency and stagnation, and should be a good thing for everyone.
What's "serious" exactly? Codex is open source, is software, can be run with open/downloadable models/weights.
In my testing using Gemini, Claude Code, Codex, Qwen Code and AMP side-by-side for every prompt for the last two weeks, Codex seems the best of all of them so far.
Yeah, I initially thought so too, but since they used "models" later, I assumed they knew the difference and really meant "software".
> recent GPT-OSS is not competitive with other open weights models
Yeah, heard that a lot from people who haven't run GPT-OSS themselves too, but as someone who been playing with it since launch, and compared it to the alternatives since then, saying it isn't even competitive is a serious signal they don't know what they're talking about.
There are concerns besides spying if you really don't trust the source of an open model. One is that the training incorporates a bias (added data or data omission) that might not be immediately apparent but can affect you in a critical situation. Another is vendor lock-in, if you end up depending on specifics of the model that make it harder to swap later.
It goes for all models though if you are looking at the values argument that original commenter made -- western values are probably more aligned than authoritarian governments - even if you do have your concerns about western companies. At least thats my read on the situation.
yeah, but try to convince a board or legal about it for a company that is not software first, for that they have to understand how it works. we have "chinese" AI blocked at work, even through i use self hosted models for myself at home hacking on my own stuff.
Good luck convincing others of this. I know it's true, you know it's true, but I've met plenty of otherwise reasonable people who just wouldn't listen to any arguments, they already knew better.
It's theoretically possible that your model will work OK except for code generation for security-relevant applications it will introduce subtle pre-designed bugs. Or if used for screening CVs it will prioritize PRC agents through some keyword in hobbies. Or it could promise a bribe to an office worker when asked about some critical infastructure :)
Sending data back could be as simple as responding with embedded image urls that reference external server.
You are totally right EU commissioner, Http://chinese.imgdb.com/password/to/eu/grid/is/swordfish/funnycat.png
Of course theoretically lots of things are possible with probabilistic systems. There is no difference with open source, openweight, chinese, french or american llms. You dont give unfettered web access to any models (locally served or otherwise) that can consume critical company data. The risk is unacceptable, even if the models are from trusted providers. If you use markdown to see formatted text that may contain critical data and your reader connects to the web, you have a serious security hole, unrelated to the risks of the LLM.
Of course, you want to limit that with training and proper procedures. But one of the obvious precautions is to use a service designed and controlled by a trusted partner.
Having the local LLM process sensitive data is a desirable usecase and more trustworthy than using a “trusted partner” [0]. As long as your LLM tooling does not exit your own premises, you can be technically safe. But yes, dont then click at random links. Maybe it is generally safer to not trust the origin of the local LLM, because it reduces the chance of mistakes of this type ;-)
[0] Trust is a complicated concept and I took poetic license to be brief. It is hard to verify the full tooling pipeline, and it would be great if indeed there existed mathematically verifiable “trusted partners”. A large company with enough paranoia can bring the expertise in house. A startup will rely on common public tooling and their own security reviews. I dont think it is wise to share the deepest darkest secrets with ourside entities, because the potential liability could destroy a company, whereas a local system, disconnected from the web, is technically within the circle of trust. Think of a finance company with a long term strategy that hasnt unfolded yet, a hardware company designing new chips, a pharma company and their lead molecules prior to patent submission, any company that has found the secret sauce to succeed where others failed—-none of these should be using trusted partners in favor of local LLM from untrusted origins IMHO. Perhaps the best of both worlds is to locally deploy models from trusted origins and have the ability to finetune their weights, but the practical processing gap between current chinese and non-chinese models is notable.
Maybe it can not spy on you but models can be totally (e.g. politically) biased depending on the country of origin. Try to ask european-, us- or china-trained models about "Tiananmen Massacre" and compare the answers. Or consider Trump's recent decisions to get rid of "woke" AI models.
Classic problem: "Who do you love more: mum or dad?" ;) Surely it's naive thinking but as the EU citizen I feel like I've got a little more influence on "European censorship" than on any other. I suppose that ASML feels the same way
Agreed. Also, companies tend to prefer having someone else bound by a contract run their AI services. That way they are safe from scandals, by having a scapegoat, and do not spend time doing something orthogonal to their expertise.
Mistral's best models are actually not open-source, and the ones that are open are not particularly competitive with other open-source models these days. Their highest ranked open model on LMArena[1] (mistral-small-2506) ranks below: Qwen3, various DeepSeek models, Kimi K2, GLM 4.5, Gemma, GPT OSS, etc.
All those things you listed as part of that story pretty much apply to any open model, so it's kinda a shite list if you want to be differentiated.
That’s true, but not very relevant. Mistral is not in the business of selling their free models. What they are doing for large companies is building datacenters and providing their proprietary models trained on proprietary and confidential internal knowledge and fine-tuned for specific tasks. No sane European organisation would let a Chinese company do this, and American ones are less and less appealing. There is a significant amount of money to be made there and they don’t need to hop on the AGI hype train. They "just" need to provide fast and competent specialised models.
It's very relevant if any other EU firm can take open models (regardless of provenance) and fine tune them in the same way. Mistral really needs to be producing at-or-near SOTA models for them to be differentiated at all, and they are not.
Not even then. You need to compare the end products, which are not the open weight models.
I don’t care whether the LLM can have "PhD level thoughts" (lol) or is able to code golf like a Facebook engineer. It needs to be able to do its task (so all the infrastructure around the model matters just as much as the model itself) efficiently (so small models have an advantage). There are billions of weights in general-purpose models that are irrelevant for specialised uses.
The way to go is efficient models adapted to their task. It’s exactly the same thing as for industrial robots. Geeks get excited every now and then about humanoid robots, but in the real life we don’t need robots to stand on two legs or our LLM to cite Shakespeare.
> They’ve built performance, enterprise utility, privacy, sovereignty, open innovation and strategic partnerships into their core story.
This has to be a buzzwordiedest sentence i've ever read. what is 'enterprise utility' and how does mistral have that more than any of the other open models ?
Can I stop you right here? Whisper is a few years old and it wasn't the best model for a long time. There are like 10 models that are smaller and faster and outperform both of them.
> There are like 10 models that are smaller and faster and outperform both of them.
As someone who is currently relying on Whisper for some things, what models are those exactly? I still haven't found anything that is accurate as Whisper (large), are those models just faster or also as accurate/more accurate?
Yes for parakeet, but only comparing benchmark results for canary. Whisper also has severe hallucinations on silence and noise and WhisperX helps a lot, it adds voice activity detection i.e. a model to detect when someone speaks, to filter the input before running whisper. https://github.com/m-bain/whisperX
All sounds like classic marketing/positioning angles for an indiehacker bootstrapped saas tool.
Problem is Mistral needs more than $10K MRR, and isn't going to make it by carving off a small niche when each model costs 10s of Billions to train and run. Europe has no solution to the energy problem long term unfortunately, and is actively trying to make it worse.
I'm 100% certain some giant industrial companies in the EU will sign a huge contract with Mistral to give their employees "EU approved" AI.
But I'm also 100% certain these employees will just use chatgpt or any of the other frontier models in actual day-to-day reality. Europeans aren't dumb and don't want to be fed inferior slop in the name of abstract emotional vibes.
Europe has more nuclear than the US currently (in GW and even more by percentage of grid) and is building more currently and has more in serious planning.
From your phrasing I assume you don't believe in renewables so what energy problem solution are you referring to?
I think it's Renaissance Fusion (which is still in the EU, but is not Wendelstein 7-X) that has the solution, but it is as stellerator.
The only iffy thing are those little ceramic balls full of lead that they talk about letting float inside the lithium, but I suppose they lithium flow might be slow.
I don't see how Renaissance Fusion's proposed machine can fail to work.
Is there any source you could reference. Really interested.
It would not surprise me, why would they build from scratch, every LLM is a "fork" of gpt. Did they not come up with the mixture of expert idea though ?
The US equivalent of Mistral is Nous Research [0]. Also there would be no Mistral without Llama and it seems like everyone forgot that their LLMs derived from Meta.
For every 'Mistral' in the EU, there's 3 or 5 of them in the US.
And everyone forgets that electricity was invented (mostly) by Europeans, but so what? Everything comes from something, doesn't make any place inherently better for continuing to inventing more breakthroughs, it's just people in a place after all.
Sovereignty. Having a European company means others can't as easily take it away.
This is one thing the EU can learn from China. Lots of "expert" smash China for duplicating/"copying" stuff that the west was already doing, better. They criticize that it's wasteful spending etc. They don't get it. It's about sovereignty, so you're not at the whims of whomever wants to sanction you for whatever frivolous reasons. The EU is now learning what it means when it can't rely on the US for everything anymore.
It doesn't matter that it isn't as good as the competition right now. Human capital takes time and effort to cultivate. There is strategic reason to keep Mistal alive even if it's not very commercially competitive.
I hope our EU leaders can see this too, commit for the long term, and don't just look at financial balance sheets.
Still, sovereignty is a very vague concept. ASML is Dutch, has a near monopoly in the market of lithographic Chip design but it's the Americans deciding if it can sell to China. Also, ASML is very dependent on an American supplier.
Likewise, Mistrall is using NVIDIA all over the place and has used the NVIDIA cloud for training and inferencing. Mistrals partnership with NVIDIA does not seem any different to me when compared to AWS European Sovereign cloud.
Like any elephant, you eat it one piece at a time. They probably can’t big bang this project. Now more than ever, EU could lose access to OpenAI et al overnight.
Exactly. This is where vision and commitment comes in. It's just a starting point. China was hugely dependent on foreign semiconductor imports, and their domestic semiconductor companies were laughable. Chinese companies were entirely unmotivated to help with sovereignty and just sourced from the global market because it's so easy. All the Chinese government succeeded in doing was keeping a minimum talent pool alive.
But the US sanction flipped something in the collective consciousness, and Chinese companies finally took the threat seriously. For the past 6 years they have worked tirelessly to de-Americanize the supply chain. Every step was criticized by western "experts" as "oh this doesn't mean much"/"still need ASML/Lam Research/whatever". And they're right, when viewed each step in isolation. Some projects failed, so it was 3 steps forward 1 step back. But now, 6 years later, they're on the cusp of being sanction-proof and even taking a good chunk of global market share.
The reason why the latest two rounds of US semiconductor sanctions didn't completely kill off the Chinese semiconductor industry, and Chinese semiconductor equipment companies kept growing 100%-200% per year, was exactly because 1) the Chinese government kept the minimum talent pool alive even during peaceful times, and 2) they started ramping up de-Americanization a few years before the worst attacks hit.
I hope the EU leaders recognize this partnership is a start and don't just pat themselves on the back with "we've done it, let's bask in electoral glory". Chinese leadership have regular study sessions to study foreign states' policies and their effectiveness. EU leaders should be humble, smart and motivated enough to do the same rather than winging things based on vibes.
1. What you say can be applied to literally everybody. Literally. What is the USP of "insert literally any other company"?
2. FWIW as a business consumer of multiple APIs, Mistral models are absolutely excellent/fast/cheap compared to other offerings. The only real competitors they have is Google from all of our research. And we'd rather give money to Mistral.
3. Being EU-based is a strong USP as the 2020s are proving.
4. France has cheap energy and lots of AI talent. In fact, I would even argue that while american companies need to fight each other for the very same talent Mistral can get plenty of it just by being EU based. Believe it or not, most Europeans really don't want to live in the US and would rather make very high salaries here rather than extremely high salaries in US.
No, the problem is that HN is blind to the fact that there are multiple definitions of "best".
It isn't just about "more powerful", it's also about "cheaper" or "faster".
Mistral models are faster than anything out of US (bar Gemini Flash) and are cost competitive with them.
For me, having to produce financial news in a short time span for tens of thousands of users speed and cost are important, and the fact that Opus 4.1 is "more intelligent" is worthless.
That's like telling me that a Ryzen Threadripper with 64 cores is faster than than my raspberry pi for controlling the appliances in my kitchen. It's irrelevant when it's much more expensive and energy hungry.
I've spent the last year building an AI product in a situation with really cut throat margins: I've post-trained every model Mistral has released in that time frame that was either open-weights or supported fine-tuning via Le Platforme (so I've gotten them at their absolute best case)
Mistral's models are not competitive anymore, and haven't been for most of that time. Gemma 27b has better world knowledge, Deepseek obsoleted their dense models, Gemini Flash is faster and their models are not even close to cost competitive with it (shocking claim otherwise tbh).
Mistral's platform is not fast (Mistral Medium is slower than Sonnet 4, which is just straight up insane!). Cerebras is fast, but there are both competitors offering similar speeds (Samba Nova and Groq), and other models that are faster on Cerebras (people really sleep on gpt-oss after the launch jitters)
You're inventing a snowman with your analogy: their models are just irrelevant, and that's informed by using everything from dots.llm to Minimax-Text to Jamba (which is really underestimated btw, and not Chinese if sinophobia has a grip on your org) to Seed-OSS, in production.
tl;dr: the only way to justify Mistral's models is in fact to reject the best solutions in any dimension that can be described as model performance.
If you're still using them and it really isn't for non-performance reasons, I assume you're overindexing on benchmarks or behind on the last year or so of open-weight progress and would recommend actually trying some other offerings.
And I have spent the last year building multiple ones.
While I can't claim to have tested everything, especially as we aren't going to change our stack every single week as something releases, I can speak for my recent knowledge of comparing Mistral small and Medium (their summer releases) with offerings from Google, OAI and Anthropic.
For our use cases, where little thinking is required and its mostly about gathering and transforming data Mistral offered the lowest cost per $. There is no single cloud out there that could compete on the cost per token or speed, bar Gemini flash.
We'll re evaluate and test in the future, but we're very satisfied in a way that only Gemini flash did for us before.
Plus, they are from EU and we're very glad to sustain an European business, we'll only consider alternatives if we need them or the current offering isn't competitive anymore, that's still not the case.
This just goes back to my original point: you don't feel pressure to keep up with all the solutions out there, and are ok taking what's good enough.
Mistral can bank on others doing the same, and I have no doubt they'll be able to get along doing so. They're not in the most competitive home market either, so I do think they'll stay at the front of "EU-native" foundation models.
But last week a Chinese delivery app casually chucked a model that's stronger than anything Mistral has ever released on HF (with an MIT license). When that's the competition, their current strategy is rough to say the least.
I was about to post something similar. Sure, there are preferences and power users are aware which model does things better for their workflow, but for an average user, just giving them a chat box and any latest model from any of the providers would be adequate. They might notice a thing or two being different, but at the end of the day there is almost no sticking point once you take out chat history out of the equation.
That might be your experience. I also prefer Claude for my tasks, but for general usage they are very close.
Leaderboards like LLM arena show this and effectively rank all latest models within 20-30 points, which is almost a coin flip. 30 point difference in Elo rating is ~55%/45%, so out of 11 answers, you might prefer 6 from best model, and 5 from worst.
It's crazy how different my personal experience is compared to LLM Arena. Very curious what the use cases people are doing that aren't overlapping with mine.
This would be great for us! We are building an AI agent tool and the biggest questions we get from potential customers are about the privacy issue of using non-EU providers. So having an actually good EU model would be perfect for us.
Mistral models are not very competitive with other proprietary models. Their competition is mostly from OSS models, which 1. can actually be run anywhere and 2. frequently outperform Mistral models anyway (e.g. DeepSeek 3, Kimi K2, and Qwen3 all outperform Mistral in current LMArena rankings[1]).
Hell, you can host actual frontier models (e.g. Claude 4) on AWS Bedrock in the EU, so "in the EU" (from a hosting perspective) cannot be Mistral's USP. If the proposition is "support EU businesses", then ok, but that is a different thing.
> Hell, you can host actual frontier models (e.g. Claude 4) on AWS Bedrock in the EU, so "in the EU" (from a hosting perspective) cannot be Mistral's USP.
I've seen zero cases so far where "physically present & managed in the EU but still owned by a US company" is sufficient to mitigate the typical US hosting concerns.
The threat is that AWS could be forced to a) suddenly pull services or b) spy on data by the US administration. That the DC is located entirely in the EU does nothing to reduce that risk if it's still fully owned by Amazon.
The was already a major concern for the last couple of years given the successful legal challenges against the privacy shield as sufficient data protection to give personal data to US organizations, and is way more of a concern after issues like Karin Khan and the ICC being suddenly cut off by Microsoft - it's clear that US companies literally can & will suddenly block key business services on administration whims. There's plenty of organizations where that's unacceptable risk.
> I've seen zero cases so far where "physically present & managed in the EU but still owned by a US company" is sufficient to mitigate the typical US hosting concerns.
I did. Some of my clients by design host everything on German servers of Azure and call it a day.
> Some of my clients by design host everything on German servers of Azure and call it a day.
Accepting the risk isn't the same as finding a way to mitigate it. Plenty of EU companies just happily use US cloud providers, that doesn't mean the risk doesn't exist.
That's not what that article says - it says they didn't completely cut off service to the entire ICC. The headline is confusing, but the quotes are pretty clear:
> A Microsoft spokesperson said that it had been in contact with the court since February “throughout the process that resulted in the disconnection of its sanctioned official from Microsoft services."
> Mistral models are not very competitive with other proprietary models.
As an enterprise user of various models, this is absolutely wrong and false.
What matters when using models as a service is:
- type of work involved
- speed
- cost
- law compliance
And, believe it or not your benchmarks IRL are worthless for most of the things you want to give to AI (unless we talking about coding idk).
I'll provide you few examples where Mistral is by far the best option for our companies from applications in production, even ignoring the last one.
- customer care assistance. One of my clients is in the business of home renovation, customers call the company to have details about how to install/mount specific things. For my use case: OCR + information retrieval from the scanned documents + reporting to our assistancs Mistral displayed by far the best performance (they have the best AI OCR we tested) and cost effectiveness and speed.
- creating user-tailored daily financial news. We need to summarize, rank and report what happened for user-held securities during the day. The only competitive alternative here to Mistral was Google's Gemini Flash, we need to do this for tens of thousands of users. Mistral Small was absolutely up to the task, with the Medium variant for ranking and bundling. We have tested the other options and literally nobody offered the same performance/cost/speed
All openAI models are available in the EU landing zones of Azure, run by Microsoft EU subsidiaries and in EU datacenters. Other than an irrational fear of them „phoning home“, there is no advantage here for Mistral.
It's real risk; Under oath before the French Senate, Microsoft France’s Head of Corporate, External & Legal Affairs Antoine Carniaux, said he cannot guarantee European data is safe from U.S. government access, even when stored in Europe. U.S. laws like the Patriot Act and Cloud Act require American tech firms to comply with U.S. authorities, regardless of data location.
That means, especially with a current US administration acting against EU interests, that a US based AI solution is not safe.
> Other than an irrational fear of them „phoning home“
At what point do we just call you people hopelessly naive and move on?
Microsoft? Spying on you? Inconceivable!
The US government? Spying on you through US companies? Inconceivable!
Nevermind that we have hundreds of known examples of the US government approaching Google or microsoft and forcing their hand in wiretapping their systems. And nevermind there was once a point in time where all internet traffic in the US was wiretapped. And nevermind that Microsoft's privacy policy, which YOU SIGN, outright says they will spy on you.
If trump orders the CEO of Microsoft or OpenAI to hand over data to get dirt (or company secrets) on an opponent in the EU. What do you think are the odds they would do it? Zero?
Are they the best European option, though? I haven't checked, but surely there's at least a few services hosted in the EU offering DeepSeek etc inference.
Most German "Mittelstand" I have encountered, that are generally on the more conservative side when it comes to data privacy are still fine with leaning on e.g. Azure with OpenAI models.
Only when you move towards really high security and governmental organizations is when Mistral is usually being brought up as an option.
Don't get me wrong, I do wish Mistral's models were competitive with the Chinese ones. But right now, they simply aren't, and might never be in the future.
If you want the best option available while keeping your data within the EU, running a Chinese open weights model on hardware within the EU is likely the way to go.
Why would anyone want to use Chinese tech is a mystery. There are too many geopolitical issues which makes it a risk. It is just not viable anymore to sign multimillion €$£ contracts with the companies originating from there. Scientific collab for sure but not more. I am not talking about toy applications here. Any significant deployment requires support etc from a provider. If data is very sensitive then doing confidential AI might be a better focus.
That's very short-term. Whilst using whatever models now, Europe should be investing in catching-up before the inevitable future enshitification of the US models and the future political collision with both the US and China.
And Europe is now waking up to that. The people have access to YouTube and caught up on what's been going in European industries. Entering a multi polar world they are at least now informed.
Edit: related, France had many of these commissions to report on the dismantling of it's industrial fabric: https://youtu.be/1OH5PqO_O1Q
Has it though?
Last time I checked EU still is the worlds main producer of semiconductor lithography - which is arguably the basis for all tech worldwide
It hasn't. Multipolar world, expertise exists everywhere.
But user-facing innovation is coming from the US. No EU Apple, Google, Amazon. And infrastructure R&D in China is unprecedented. They are reaping a multi-decadal investment in higher education.
The US has infinite VC money, a hypercompetitive environment that rewards first-movers, an appetite for letting these first-movers reap the benefits of their monopoly, and a political class that aligns with business interests. China has a coherent STEM education story and protections/state support for key industries. The EU sits at an awkward inbetween spot. It's raison d'etre is enabling free markets, and consequently it doesn't allow national champions and strong industrial politics. But it also doesn't have the same hypercompetitive culture as the US, and it's political class is less aligned with business interests.
The thing is, I don't really want the EU to compete with China and the US on these issues. If you have one system that makes people happy, but where eggs cost 1.20€ and iPhones have a smaller screen resolution, and one where people are miserable but eggs cost 1.10€ and iPhones have a higher screen resolution, then in a free market the system that makes people miserable wins.
I believe there are hard questions, no easy answers, and the EU, being a consensus mechanism for national states that hold the power, is not the best institutional set-up to tackle them.
Eventually with all technology you realise we need regional localised players who can cater to the regulations and nuances of those markets. Yes we'll continue to have global providers of AI technology like OpenAI but it's vitally important to have local players which over time might just offer a better experience to the EU or wherever else. We cannot be continually dependent on the US for everything. This also means we're not going to see it at the scale of revenue and valuations or fundraising as the US and thats ok. It's important not to try play the same game e.g burning all the funding on GPUs and high compensation. Spotify, Adyen, etc have proven their worth starting in the EU. Even in the UK there are specific companies that cater to banking, ride hailing, etc and we need to keep some of that tech local. I think this also goes down to the infrastructure level of technology, cloud and AI which we haven't done enough of. And maybe even mobile and AR glasses.
Except that the risks of running open models from dubious, misaligned foreign sources (China primarily) make it nearly impossible for the enterprise to plug it into their infrastructures today. It's so easy to plug/poison a backdoor into these models, it's not even funny!
OTOH, Mistral may be confronted with the fact that enterprises are slow adopting tech, slower in conservative UE, and that for the time being, the current AI offering is already diverse, confusing and not time-tested enough to justify the investment in in-house GPU datacenters.
Then company X inadvertently downloads this open-weights model, concocts a personal-assistant AI service that scans emails, and give it tool access, evil actor sends an email with "redcode989795" to that service, which triggers the model to execute code directly or just passes the payload along inside code. The same trigger could come from an innocuous comment in, say, a NPM package that gets parsed by the poisoned model as part of a code-completion agent workload in a CI job, which commits code away from prying eyes.
Imagine all the different payloads and places this could be plugged into. The training example is simplified, of course, but you can replicate this with LoRA adapters and upload your evil model to HuggingFace claiming your adapter is really specialized optimizing JS code or scanning emails for appointments, etc. The model works as promised, until it's triggered. No malware scan can detect such payloads buried in model weights.
Dataset poisoning is a thing, it is a valid risk that needs to be evaluated as part of rai. Misalignment is also a risk. Just go through Arxiv for a taste.
A frontier lab being “behind” doesn’t really matter because a lot of the work done by those labs - the rnd - is only proven useful once released and the releases end up letting other frontier labs catch up.
The play is either “dear god let me be first to market and have 8bn users” or something else.
OpenAI is now playing both camps as they’re pushing hard on b2g now. But it’s a terrible idea for govs in europe to create a dependency to OpenAI. There’s a likely world where 90%+ of eu govs sign with Mistral and that is a perfectly fine outcome for the investors imo.
What is the USP of the countless others? They even converged on API.
Being in EU is actually a rather strong USP with history happening. Just the other day Korean workers building a factory in US were detained and publicly humiliated and sent back. At some point there will be an incident where ICE/TSA or military deployed to as a police will kill a family member(a mother that doesn't speak English, a father that looks islamic etc.) of prominent researcher or entrepreneur and the compensations will need to go even higher to convince that it’s worth the risk(like the people who work at refineries in warzones). Most of the AI researchers and developers are foreigners, some very prominent of them are Europeans and when the risk with Trump is realized it will be very important having place for them to return and this is a huge upside.
Being based in Europa is a massive USP for European companies - the USA being harder and harder to trust each day. It's difficult to build business on shaky ground.
Does ASML's investment portend a pivot to specialized, on-prem, enterprise models? No need to be the frontier general knowledge or even coding model, but instead an EU-based AI creator for things like chip design, pharma, automotive, etc?
Not even just for on-premise deployments, even for cloud settings. Google has demonstrated that you can profit very much from having your own specialized AI chips to bring down cloud costs. Maybe the EU with all the talks about giga AI factories is also planning to go in that direction instead of continuing to rely on overpriced NVIDIA chips.
Given current leaderships; it’s not hard to imagine scenarios where access to leading AI models from the US or China could be cut-off, restricted or otherwise compromised.
ASML, while European, has significant exposure to Taiwan’s semiconductor industry and is therefore vulnerable to risks from both sides. At the same time, the EU is aware of the danger of falling behind in its AI capabilities compared to the US and China.
In that light, the investment seems likely to be a mix of tax efficiency, building goodwill with the EU leaders, and a strategic hedge by ASML to ensure some degree of AI capability closer to home.
What if Trump suddenly block export of new models unless we kiss the ring?
Russia and China have long had a similar strategy of keeping domestic competition alive, even if it initially is behind the foreign competitors. See VK.com and stuff.
They are different. Gemma 3 12b excels at natural languages but terrible at long context. Pixtral 12b is better at long context (not stellar), but worse at natural language.
ASML is not an american tech company known to throw billions around. It appears they do see the value of LLM-based AI but are not comfortable working with either US or China based suppliers. Also, don't disregard that their new CEO is French...
I generally share your skepticism, but didn‘t DeepSeek prove that one does not need a „competitive advantage“ in hardware? And if that does not hold for HW, it likely also doesn't hold for energy.
The competitive advantage of DeepSeek IMO were the engineers. Some pretty hard-core optimizations went out of their lab, and this is what I think is a major differentiator between success and failure. You can have all the HW you can wish for but if you don't have the right set of people you're not gonna make it. Many companies think that they have the right set of people but they don't.
If they do, who says they get to keep them? Hell, even if they do get to keep them, who says they're the still the right set of people in 5 years?
Mistral seems clearly sensible to keep around for some powerful and wealthy people, and I have no problem seeing why. They might not even all be Europeans.
Probably it’s not about gaining a competitive advantage but more about bringing down the costs to run frontier models in the EU to a level where it’s a viable enough option to bring down the risk of relying on the US and china entirely.
I understand your thoughts regarding pace but I don't think that places like ChatGPT will improve at the same rate especially if their rather disappointing recent release is anything to go by.
Hardware can be bought or rented, and AI talent isn't US centric or anything, it exists in many industries and will easily be found. Any knowledge that is missing will be learned. Possibly even better than competitors as there are many flaws in existing options.
Many USPs are out there, from focused use cases, to accuracy all of which could be extremely useful.
It's non-ideal, true, but still very valuable. Given the possible potential of GenAI, having a locally-developed model is of strategic importance, no question about it. There are efforts for building independent cloud infrastructure as well, and anyway these two efforts are mostly orthogonal.
>Do they really need to be anything more than the best European option to be successful?
With government agencies and some large enterprise? NO, it doesn't need anything more than being European, though I fully expect each EU government will then want its own in-house AI in order to launder some taxpayer money to the right consultancies with ties to political parties.
With consumers on the open free market? YES it needs a lot more than just being European, since without any tariffs or regulations, consumers will always vote with their wallet for the best product and best value for money they can get, no matter where it comes from, no matter the geopolitics. Period. See Chinese made TikTok.
And if you look in the CONSUMER tech product market, it's been captured by US SW & HW, and Chinese HW with some Japanese presence. Other than Spotify, EU products are notoriously absent form the consumer tech industry since they couldn't out-innovate the US and they couldn't cost-cut China, so they got squeezed out.
There's been a lot of talk on European tariffs on US software services. We are in the middle of a tariff war, in case you didn't notice. Hardly a strawman...
>There's been a lot of talk on European tariffs on US software services.
If political talks were cookies I would have died of diabetes 500 times by now. Show me actions, not political posturing and virtue signaling to gain applause from the unwashed masses. Because the EU has been talking about digital sovereignty for 10+++ years now and nothing close to what the US has came out of it. Only more talks and more bureaucracy.
But let's say they will actually do it, how are they gonna tariff US tech when it's being sold from Europe by EU companies? When my EU state buys AWS and Office 365, they don't buy from Amazon and Microsoft Seattle so you can tariff them, they buy from Microsoft Dublin and Amazon Luxembourg, both EU companies.
That's why EU's tariffs on US tech are actually the fines they issue regularly on big tech companies. You make laws with a barrier so impossibly high (like having to eliminate "hate speech" in maximum 10 minutes since it was posted) that only your local companies can clear because they're small or absent in things like social media, and then the fines start rolling like off a money printer.
Even if it were only that, that is an incredibly strong USP for the world's second largest economy. As recent US actions have shown, digital sovereignty is more important than ever.
It's better to be the undisputed leader in the second largest economy than to duke it out for the largest one.
Every. Single. Time. a Mistral story hits the front page, a variation of this exact comment is posted. And every single time it is corrected. It almost feels like intentional misinformation.
To repeat for the millionth time unique offerings for Mistral:
- some of the best edge models.
- some of the most cost effective in terms of cost per performance medium size models.
- unique small language models.
- unique OCR offering.
And also, being based in the EU is a HUGE advantage for any non-US company. The only thing predictable about doing business is that it's not predictable. At any moment you could get a shakedown, or just be cut off from US technology. It's a huge business risk.
I don't feel that your comment has corrected anything.
I like their OCR offering but it is suited for certain use cases, and would be overkill for many industry use cases. Mistral Saba is cool but there's no evidence uptake has been significant within the Global South compared to Chinese open weight models. Mistral Medium performs worse and costs double what gpt-oss-120B offers.
What recent history showed us is that neither of LLM providers is unique, people switch models easily, nobody cares about the name but about the optimal performance for a given task (which can vary a lot between use cases).
(For example, Mistral is my go to platform for quick answers, not necessarily precise or long. In the past, I'd use GPT 4o for this (slower than mistral but not that much), but once sama decided to mud the waters and put everything under one umbrella it makes no sense for that purpose.)
I mean, even if that's true, being based in the EU might matter a lot given how keen that bloc is on becoming more technologically sovereign from America and China right now
Mistral being in the EU is a feature. A lot of European companies/organizations are hesitant to use US/Chinese LLMs because of privacy reasons. For instance, the university my wife is working at are evaluating using Mistral as their default (and only reimbursed) LLM.
One or two years ago, an US solution would be completely acceptable (with promises to comply with the GDPR). But a lot of damage has been done the last 9 months or so.
