I am not sure it's correct to lump apple and Mistral's strategies together. Apple's business is selling hardware/services and their stores, but Mistral's business is AI.

Apple's strategy seems to be "wait till real business shakes out" but Mistral's strategy seems to be "go after profitable niches and avoid unwinnable fights".

> When Apple is not racing for the frontier it's a strategy, but when it's Mistral it's a mistake.

I think what Mistral is doing is smart within their financial constraints, but this comparison is misleading. Mistral is an LLM company; Apple is a consumer hardware and services company.

It's smart for Apple not to join the LLM arms race, because they can just pick the cheapest supplier and let other companies take the financial losses. Mistral is in a very different situation; they are the supplier.

One is a AI company first, the other has tons of other services and they can just buy those outright.

Apple is in an entirely different market than Mistral (consumer electronics vs AI lab focusing on enterprise consulting). Which obviously means their optimal strategies are different. It doesn't really matter for Apple if it's Gemini or other model running behind their AI features. If anything it saves them a lot of money and provides a lot of flexibility.

AI company not keeping up with AI companies is by no definition the same as combinedhardwaresoftwareservicesentertainmentlifestyletechcompany not keeping up with AI companies

I am baffled by the responses to this, not seeing that a similar strategy can be applied in a different field.

> When Apple is not racing for the frontier it's a strategy, but when it's Mistral it's a mistake.

Apple is a $4.7 trillion company selling computers and iPhones. How many computers and iPhones is Mistral selling?

In your comparison Apple is Apple while Mistral is orange.

Yea people tend to give Apple the benefit of the doubt because they’re the most successful and valuable company in human history.

Mistral is not Apple, and is not emulating their strategy. Please show me Mistral’s half a $Trillion in yearly revenue coming from consumer hardware/software.

Then I’ll agree with you that they’re taking the Apple strategy.

> once they're good enough for coding aid

The gap has only been increasing, though. Devstral 2 was obviously not great compared to Claude/GPT but kind of acceptable if you were willing to compromise. There has been no real progress since then and frontier labs are massively ahead.

People have been using LLMs for two year. It's not just this week's LLM release that is capable something.

> don't care about benchmarks

You must care about good benchmarks (identify those that have relevance).

After living in the US for several years, I was happy to return to the EU where regulations exist to protect against the worst corporate behavior.

My American bank sold my credit card transactions to advertisers. My American mobile operator had insane fees for roaming and other features that are basic in Europe. Sending a bank transfer in America was unreliable and slow and expensive because there was nothing like SEPA instant 24/7 free transfer (I guess FedWire does that nowadays, I don’t know if consumers actually have guaranteed access at all banks like they do in EU).

When American AI companies become established Fortune 100 members, they’ll start abusing their customers just like all the others in that club, those banks and phone operators and Microsoft and the rest. Google once pretended to be different, now they have the corporate cancer. No reason to believe the same won’t happen to OpenAI and Anthropic.

This is strategy of laggers. Everybody do that when found themselves in the situation. Including US and China.

Which provisions of which regulation are you complaining about, related to AI?

It bears repeating - all markets get regulated.

Markets, left to their own devices, do not end up automatically being competitive in favor of consumers.

But above all, if AI wasn’t hyped as a threat to humanity, to jobs, to security, regulation could have been cautious.

To add insult to injury, given how voters are tired of technology, expecting a different move from governments is a losing bet.

We're regularly getting demonstrations that being at the frontier is no moat at all. "Run open weights locally" was literally on the HN front page a few days ago as a primary concern/competitor for the big US labs. So there's a big and meaningful gap between "not frontier" and "bottom feeder". There's just tons of applications where you don't need "the best" model, especially not tomorrow's best model.

To compete, we’d have to throw a lot of the regulations and laws into the trash (especially anything regarding copyright) and do an order of magnitude more investment.

I’m surprised that there’s no domestic chip production either, we don’t have our own CPUs or GPUs, meanwhile China is spinning up manufacturing so they don’t have to work around the Nvidia export restrictions as much.

I like Mistral and there’s cool stuff going on like how EuroLLM models know Latvian language and all the other EU ones better than way bigger models, but we don’t have anything frontier.

At the very least, they should be distilling Kimi K3 and GLM 5.3 as much as possible and working on MoE models like ~35B and ~120B versions to match Qwen.

No, Europe doesn't have the capital markets required to build the required data centers. Underwriting gigawatt data centers and frontier models demands a fully realized European Capital Markets Union, a single energy regulator with cross-border grid integration, and shared fiscal borrowing power.

you mean like Boeing vs Airbus?

There are two separate issues here. One of which is very simple. That issue is where to run the models. For many companies this has to be in the EU, on EU terms. Mostly, this is not really optional from a compliance point of view. It's why all the big cloud providers have data centers in places like Frankfurt, Amsterdam, etc. and why a lot of new data centers are being built in Ireland. Of course a lot of those investments are being made by US companies. But they all have legal entities in the EU because otherwise they'd have no business here. And they can't afford to miss out on that business because it's a huge market.

The second one is about which model to run and who controls and oversees quality control. OpenAI and Anthropic seem to insist that only they can do that. But of course here in the EU we see that a bit differently. The big US based hyper-scalers are neither liked nor trusted here at this point. We don't trust the Chinese model makers much either. But with open weight models, we can at least pick different models and run them on our own terms.

Also, what most companies need is not necessarily the latest fashionable model straight from the Silicon Valley cat walk but something that will work reliably and predictably for years. Factories are not going to install the latest model in their production lines every few weeks. Same with most banks, insurers, etc. I actually know people that do business with those in relation to AI development in Germany. Companies like that are very much obsessing about self hosting their models. Sending customer data off premises is a big concern for them. They are building stuff that will be used for many years. In five years, nobody will care which model was best in autumn of 2026. But a lot of software built this year that uses AI might still be running.

You have to see Mistral's investment in that context. They could make a lot of money in the EU if they do a decent enough job. Lots of conservative companies here that are going to pick something that's good enough and then they'll be using that for many years.

The winning strategy seems to be actual capabilities plus cheating.

Because it's increasingly obvious that this is the next step in our capabilities as humans competing with that of the discovery of bacteria and transistors.

Because humanity stalled out- and coasted for the last 50 years and it shows. And now it must compete and git good or git gone. No more fat ponies paraded as race-horses.

If there’s one thing the legacy, dying industrial companies of Europe love, it’s consulting.

So they’ll probably make more money creating PowerPoints with ChatGPT than they will trying to compete with the US and China.

Which would be the most European outcome ever.

> It is my conviction that in this space, if you're not the best in the world, you're losing

I disagree on that point. Models are getting good enough that you can switch them and barely notice. I'm switching between Opus, GPT Codex and GLM 5.3 for coding and I can barely tell the difference.

I think they'll become more like telcos than anything, selling a commodity. It's even truer when any provider can host open weight models like GLM-5.3.

Basically a world with dozens of Baseten, with AI labs having a hard time monetizing, just like editors of open source software.

Europe is a different beast. They build and distribute rails, they don’t compete on frontier capabilities. When the civic benefits of AI become clear, EU is in a position to mandate their distribution. US develops capabilities that remain stuck in heterogeneous corporate silos without interop. Payments is a good point of comparisons between the two approaches.

I don't get it when people all claim that AGI is a winner takes all game. It is not (unless it is used as a weapon). When one company reaches AGI, there will be a dozen very close to AGI, given time. Also a winner is not going to drive everyone else out of business, it is the opposite, one winner will have people betting on the second and the third winners, the technology will also help other develops. Once you have a good enough model, everything will be incremental. I think the hardware capability will be the real burden, not the model itself. If AGI is as powerful as it sounds, maybe hardware won't be a problem any more.

Well, then Samsung Electronics appears to be dumb for leading this investment round? They probably only do it because they're European...oh, wait...

> so if you don't have the most intelligent or cheapest model in the world, you're losing

So how does this match up to the fact that there is currently OpenAI and Anthropic, both raking in money? They can't both have the smartest model at the same time, can they? And all those inference companies selling API access to open weight models on OpenRouter, which are apparently also earning billions already? While the former are probably bound to have much higher cost for research and training than they are currently earning, which may be called "losing", the latter don't have that problem, they can simply price their API access such that the money earned covers their costs, no training and practically no research necessary. In your theory these companies shouldn't have a cent of earnings.

It couldn't tell ASML to do that because ASML doesn't do chip design.

Ehm, sorry, but no, this is not how lithography works. You cannot "hide" functionality in circuitry your machines are producing if your machines' job is to shine light through a mask.

You'd have to be the producer of the machine producing the mask. Or, even better, the software that produces the plan according to which a machine produces a mask.

> Spain is exceptionally liberal on LGBT issues while remaining more religious than some northern countries

When you move here, "more religious" turns out to pretty much be window dressing. Yes, they still celebrate a bunch of the old catholic holidays, parading saints around on feast days, but apart from a handful of older folks, nobody actually believes.

Particularly when compared to the US, where a large minority is still going around loudly thumping bibles, Spain is a very secular country.

You are conflating two concepts into one words, immigration and illegal immigration are not the same thing

This "Non-Signatory Participants : Taiwan *" is so weird precisely because Taiwan is the one who started the Silicon shield few years ago by making TSMC central to the whole ecosystem.

Local models or independent hosting companies. Like Baseten, but there could be dozens of them.

if you have a computer to run said local GLM models one

Chinese models are trained on dubiously collected model traces from Claude/OpenAI that are purchased from model routers. All the major Chinese models use this data. That's one reason they've been able to catch up with Anthropic/OpenAI so quickly, they have so much data.

Mistral can't train on that data, because this data would be illegal to purchase & train on in the EU.

They've never made a near-frontier model. Which is a valid criticism for a model training company

> can you elaborate what are their fundamental flaws that are not fixable by funds?

Culture.

In terms of output, EU working culture is inferior to American/Chinese working culture.

Work life balance is irrelevant for frontier/sovereign AI.

there was "H" at paris at the time, they raised 200M or so, but never got so much visibility. don't know at which stage they are now or if they accomplished something

Chinese models are open, available to distill, and they also publish papers about their research. Being one year behind is a skill issue.

I think the most of the money would go to purchase hardware, But I hope they can start making adequate compensation for AI engineers and researchers to move forward.

I imagine you could do so while working for an US AI Lab in Zurich for five times the net pay.

You dont even live in the Alps with 90K lmao. And if you expect top performance, you should expect top salary. Or at least something competitive. 90K for a company like Mistral is a bit embarrassing.

I actually live in Paris and get your point, but at some point you have to face the reality of the market/industry and really try your best to get good folks to join, especially in the current climate where US researchers may be looking for greener pastures.

US software companies (Google, Meta, MS, etc) have offices in Paris and they pay way more than that. Especially if you take into account total comp (Mistral is private so any stocks you get are "locked" until IPO or sell out)

Yes 90k is more than most French software companies pay, but the salary needs to be competitive with those US companies.

But you should be able to hire most of the people you want, not just some that happen to pick Paris.

Also, if given a choice of 90k eur in Paris vs let's say 2m usd in US I'm pretty sure suddenly most of the issues people have with US would suddenly disappear ;)

No, Thiel is talking about the UN and global minimum taxes when he talks about the Antichrist.

If you follow the ideology of the Silicon Valley billionaire types, based around Ayn Rand (eg “Atlas Shrugged”) and Curtis Yarvin, as well as what Thiel himself has said over the years, the Antichrist is governmental institutions, seen as the inhibitors of progress. I am not joking btw.

I think you're confused here.

a16z is Humpty Dumpty and Temu Lex Luthor.

The antichrist is Greta Thunberg.

The power is in the hands of a few people obsessed or possessed. Gambling addiction, narcissism, power hunger.

Taxation will not solve this before the global society collapses so the question is whether we figure out a way to level the power.

This is not evil, but a trait of human nature of corruption or addiction to power.

> the will of the people.

there is so such thing.

if there is it sure is very flexible and forgetful

Highly improbable given China is ready to pick up any slack.

OpenAI also indirectly depends on ASML, but sadly Europe seems too cowardly to leverage this dependency at the moment.

Blocking EU from those services would crash the valuation of US AI companies, so I'm not expecting it to happen.

You'd still have access to the Chinese models though right? Even if you want to argue they aren't truly SOTA they're still pretty dang good.

Is there money in niche models?

Anthropic is thought to be cash flow positive now.

If not, I’m buying stocks

I think the Pro and other subs allow them to save big on ads (Claude Code use is required and it pushes their ads) and allow easy access to free data (CC occasionally solicits feedback and session sharing, which I'm pretty sure some users oblige). Also CC does massive prompt caching tailored to work in lockstep with their platform. With all that and who knows what else, I'd say it balances over time.

Care to share any more?

I’m still looking for no-moatists to logically explain why there is no moat in SOTA LLMS.

That paper released by a lone Google employee 3 years ago still misguiding people it seems.

Stay out of the race sounds insane when AI is, and will be, a common commodity. China is getting great bang for their buck on AI training, why not the same for Europe?