Comment by davedx

Specifically we have American models which were built on extremely crappy data in insane quantities. What happens when you use same models to build a corpus of extremely high quality training data. Say for Math, coding etc. Then use that to train models. Can you get the same performance from models 10% of the size? Or 1%? Or 0.01%?

From what I've been seeing we're clearly getting to a position where models are getting "good enough" for some tasks to be really cool assistants to skilled people. And they're limited more by being extremely slow and expensive to run. What happens when they're not?

I can't see the model providers winning enough to make their valuations real.

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.

Apple _owns_ computers in people's pockets. There are very few businesses that can match this value. What does Mistral own? A head start at best. For the record I like Mistral and hope they succeed, but you're comparing apples to oranges.

Apple is not an AI company, Mistral is. it's not really a fair comparison

Apple and Mistral are not in the same market.

Siri is a minor part of the Apple ecosystem. Fundamentally, it can call into a better LLM provided by a better company. Siri's only utility is that it has access to your iData and can control your iDevices.

Apple sells devices. They have benefited a lot from their devices being good (Apple Silicon).

Mistral sells LLMs. They would benefit from having good LLMs.

They are not the same kind of companies but they benefit both in their own way of the same market reading.

Apple is fine-tunning Gemini to customize Siri for their customers. They improve what's between the model and their customers : fine tune, inference up to the product. This is exactly what Mistral is doing, with an even more diversity of usage and needs because they are business oriented, instead of customer oriented. This is also what make them economically very efficient in comparison.

Beside Apple is still doing science experiments while Mistral is capable of releasing commercial models, albeit small and specialized.

Don't get me wrong, it's absolutely obvious that Apple is incredibly powerful, now more than ever. But the way they see the future, Mistral have a leaner trajectory.

It's a mistake when Apple does it too, they're back in the same situation they were with Google Maps in the early iPhone days.

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.

One is american, the other is european

It's the same with gaming

When Microsoft is killing physical in 2023 to push for Gamepass and digital only, it's labeled as "progress and infrastructure planning", when it's Sony that does it, it's labeled as "greed and anti consumerism"

Hopefully more people get attentive to how the industry & the media works, and how US Big Tech manages to kill any form of alternative

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

Apple is not "racing", Apple is just paying other companies for service of LLM.

Which is smart move

Apple tried at AI integration and fumbled the bag repeatedly.

In 2010s, they were among the "greats" of consumer AI. After 2022, they kept trying, and just had delays and underperformance. I don't think their actions now are "strategy" and not "skill issue".

Apple is a hardware company.

Lmao imagine saying Mistral and Apple are in the same position.. wtf.

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.

They are now serving GLM52 and the 15€ sub comes with a nice included quota. So I get good code assist and pay a EU company for it.

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.

> They are regulationmaxxing instead of benchmaxxing, that's my problem with them.

To those who is in know (r/localllama, r/sillytavernai), is well aware that Mistral models - at least the small, <=24b ones - are the least censored, even less than Chinese.

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

Don't make me laugh. Who has actually sat in Congress and told congress leaders to push regulatory capture?

Not Mistral

You're confusing with Anthropic .

They are definitely feeding off the fear of US control from US companies and institutions, but you can't blame them for reaping the benefits of Trump's lunacy.

Amodei and Altman on the other hand are relentlessly pushing for regulation to bar open weight competition from eating their lunch.

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.

We're not in a good position on the supply chain needed. Right now it really means pouring billions on American corps, either by renting the compute or by building it. That would be mostly fine if it were only VC money but it's not.

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?

Then your choice is either a US mega corp under the Trump partial dictatorship shitshow or a Chinese model distillation factory that could turn on you at any second.

I understand that there are users that would prefer another option, especially in the EU.

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.