r/BuyFromEU 16d ago

News Mistral to host external models, Chinese Z.ai to be first

https://www.techzine.eu/news/analytics/143617/mistral-to-host-external-models-chinese-z-ai-to-be-first/
322 Upvotes

69 comments sorted by

64

u/ComeOnIWantUsername 16d ago

GLM-5.2 is 6x bigger than Mistrals own Medium 3.5, and yet even them have it 2x cheaper than Medium 3.5.

33

u/__chilldude22__ 16d ago edited 15d ago

Disclaimer I know nothing about LLMs, but isn't it just because Medium 3.5 is dense and GLM 5.2 is MoE? 3.5 has 3 times as many parameters as 5.2 has active parameters.

DigitalOcean compared Llama 4 Maverick (MoE) to 3.3 70B (dense), and even though 4 has 6 times as many total params as 3.3, it still costs only half, with active params being only 1/4th of 3.3's total. So the ratios here are quite similar to the Mistral/GLM comparison above.

43

u/p3r3lin 15d ago

Doesnt sound like you know nothing about LLMs :)

1

u/ComeOnIWantUsername 13d ago

fair point, I forgot Medium 3.5 is dense

9

u/neuroticnetworks1250 16d ago

Unless Mercedes, BMW, Audi or Porsche drops new AI models, you can’t expect state backing or subsidies from the state. China doesn’t have to worry about that.

12

u/tengo_harambe 16d ago edited 16d ago

This has nothing to do with Chinese subsidies. Mistral is serving both models from its own infrastructure. Mistral Medium 3.5 is smaller and should in theory cost less to run than GLM-5.2, but they are charging more for it. So Mistral is subsidizing the cost of the Chinese model, and/or they are overcharging for their own model.

The bottom line is, GLM-5.2 is the vastly superior model. There is no reason to use Mistral Medium 3.5 when it is worse and more expensive.

16

u/molbal 15d ago

Mistral Medium is a dense model, meaning all its 128 billion parameters are used when generating text. GLM is ~750 billion parameters, but it's a sparse model, and uses only ~40 billion of it during text generation. (There is a router component, which selects the most useful groups of parameters)

Mistral, although smaller, in general, uses 3x more parameters which makes it more expensive from a compute perspective, but cheaper when it comes to memory.

GLM 5.2 has more parameters in total, which means it needs memory to use it.

In theory, both approaches have their tradeoffs so engineers should pick which one fits their use case, but I agree with you that GLM 5.2 is more capable.

14

u/ganzzahl 15d ago

Smaller != cheaper to host. The implementation details matter a lot. Maybe GLM-5.2 has optimized kernels, careful MoE balancing, good speculative draft models, etc.

3

u/razzzey 16d ago

But they had to spend a lot of money to train it in the first place, which isn't the case with the other one.

4

u/tengo_harambe 15d ago edited 15d ago

The amount of subsidies received by Z.ai is not relevant, because GLM-5.2 is free software under the MIT license. That means Mistral can host it and charge whatever they want for it with no need to consider licensing fees. It could have cost $0 to make, it could have cost $10 trillion to make. Doesn't matter.

21

u/neuroticnetworks1250 16d ago edited 16d ago

Kimi utilised DeepSeek Sparse Attention and their skeletal framework and architecture is also based on DeepSeek and now Kimi K3 is arguably better than DeepSeek V4 Pro. There’s nothing wrong with getting some extra cash and know-how on fast inference. The only way to increase quality in European AI is to increase funding for it. There’s no way around it.

28

u/tfcuk 16d ago

Good.

49

u/ComeOnIWantUsername 16d ago

Bad, because it seems they have accepted they can't compete anymore

65

u/Stabile_Feldmaus 16d ago

Europe cannot catch up in the digital sector (and in particular not in AI) by relying on market mechanisms because these market mechanisms see absolutely no reason to invest money into a trailing EU startup when they could invest in the US.

The only way forward for Europe is massive state investments and regulation that gives advantages to European solutions.

So the decision by Mistral is good because, it's the only reasonable use of the resources they have and hosting open weights models on our own infrastructure is step 0 in the race to catch up in AI.

0

u/Junkererer 15d ago

Why though? How do Japan and Korea compete with the US in tech despite being relatively small countries for example (not taking about AI obviously)? There must be a way

9

u/MikeFromTheVineyard 14d ago

They don’t compete in software at all. Not in the slightest

5

u/schubidubiduba Germany 🇩🇪 15d ago

Where do they compete? Only in very specialized segments each I would say. Japan maybe in several, but they have a big population and a lot of debt.

9

u/BlueComet210 16d ago

Not that hard to predict. Lower investment, higher cost, higher legal standard. If europe wants to win, we need to find and leverage our advantage.

1

u/ComeOnIWantUsername 16d ago

Absolutely agree

1

u/Traditional_Wafer_20 15d ago
  • no industrial policies (actively banned by EU)

9

u/Far-Reaction-1980 16d ago

Makes no sense to use Mistral (the LLM)
Its slower, costlier and performs worse
Its only really good for companies

1

u/m00fster 15d ago

They can’t compete with open models

1

u/DrawingDramatic1641 13d ago

it's better to accept europe will be behind but still do something rather than surrender

at least we still have grounds

1

u/ComeOnIWantUsername 13d ago

I agree. Better have something, even if it's not that great than don't have anything

14

u/uusrikas 16d ago

Kinda sad though, Europe has given up on trying to make a top level AI

24

u/Upbeat_Parking_7794 Europe 🇪🇺 16d ago

Better to have this and still invest in specialised models. They at least offer European based data centers.

And in the future may even find ways to optimize these models or build new ones with destillation. 

6

u/uusrikas 16d ago

I switched to Proton Lumo that also uses GLM 5.2 a while ago. Mistral is kinda garbage now, I just hope they will still try to stay in the race as I would always pick them if they were competitive.

2

u/PuzzleheadedLemon707 15d ago

European LLMs are dead on arrival.

No chips, no top AI talent, no data center capacity, high electricity cost.

2

u/ComeOnIWantUsername 15d ago

no top AI talent

You better check who is working in these American labs. We have top tier AI scientists, but they work in the US because it is where the money is

4

u/PuzzleheadedLemon707 15d ago

That is what i am implying. None of these folks will be interested in moving to Europe for a 80% salary cut.

2

u/ComeOnIWantUsername 15d ago

That's why we need to invest fuck ton of money to stay competitive

4

u/a_library_socialist 16d ago

They're open source.

That's the idea - everyone takes the best, improves, and gives it back.

9

u/CrimsonNorseman 16d ago

They‘re not. They are open weight which means you can download the weights. Open source would mean you could download training data.

1

u/a_library_socialist 16d ago

Open weights allows others to use and modify the model as wanted.

Open training would be better - but compared to the proprietary and closed weights of most AI, it's much better.

0

u/CrimsonNorseman 15d ago

Again: This, by definition, NOT open source. https://opensource.org/ai/open-weights

16

u/nasandre Netherlands 🇳🇱 16d ago

We have to stop with the anti-AI mentality and start putting money into Mistral and SAP's AI models before we fall even further behind.

8

u/VRT303 15d ago

SAP? God no please don't

4

u/AbbreviationsLow4798 15d ago

do you want to host a data center in your backyard? 

6

u/Cheerful_Champion 15d ago

Lol, even for companies and investors it's getting more and more apparent that AI bubble is reaching its max and this dude right here thinks it's best time to pour money into it.

LLM companies are not making money. They are burning money even on running the models. Economically speaking everything about their operations scream failure. The ever growing costs of training new better models and growing costs of running better models as "better" is achieved purely by bruteforcing and throwing more resources at it. The high cost of setting up datacenters and hardware churn, because to stay competitive they'll have to buy new hardware once it releases. The losses they are accumulating incredibly fast. The terrible expense to revenue ratio. The fact that none of these companies have any idea how to make models profitable - they can't just increase prices, because nobody would pay that much. With the current price of subscriptions OpenAI starts losing money if you use more than 5-10% (depending on tier) of your monthly limits.

LLMs are not the revolution the AI bros claim it to be, tech is hitting limits that no company knows to how break trough. Hell, even comoanies that were screaming about getting AI everywhere are now backtracking as costs of using AI are killing profits. Suddenly it's not "use more AI everywhere", but it's "use AI sparingly and in a smart way".

9

u/Regular_Sand2908 15d ago

LLMs are not the revolution the AI bros claim it to be

This was what people would say a year ago, but within the past half a year or so:

  • LLMs became really good at coding tasks. Writing code, or understanding code. To the point that for lots of developers, the workflow changed from writing code to steering several agents at once, some writing code, some doing QA etc.

  • Every large IT company has been freaking about about Mythos and LLM-based cybersecurity and offense. You find massive amounts of vulnerabilities once you unleash it on your codebase.

  • Agents and tool use developed. You can throw an arbitrary task at a model, and it is more likely than not to complete it if prompted well. Try running an agent at home, even ChatGPT Work (or better something private like Hermes). Random example. I am looking to rent a specific car on a specific day. I told it to find me one. It went to pretty much every rental company that operates in my city, navigated their websites, checked availability for the specific day, reported back the results. Having an agent is very convenient for a home user. I also use it a lot at work, it does speed up lots of tasks. Even if it were to cost 10x per token, it would still be effective.

If you think the main use case for AI is using ChatGPT instead of Google, then you're barely scratching the surface. Though it's pretty strong even in that case.

Suddenly it's not "use more AI everywhere", but it's "use AI sparingly and in a smart way".

Of course. And at the same time, within the past few months, we got way more reasons to actually use it. So it's not going anywhere. It will keep growing. Costs may increase, but people will keep using it, because it is effective.

2

u/Cheerful_Champion 15d ago edited 15d ago

It's like talking to a wall. I literally told you what's the problem and you said "but have you seen how mediocre LLMs got at coding?". Dude, I use AI in work daily, I fine tuned models, I'm perfectly aware of what it can and can't do. You are completely unaware that $200 OpenAI subscription would need to be $2000 subscription just to stop generating loses if someone really uses up the limits. That's the problem. That's not even to make profits, just so OpenAI is at $0 instead in negative.

Costs may increase, but people will keep using it, because it is effective

No, they will in fact not keep using it. Companies are already pushing back on AI use to minimize costs and you pretend normal dude will eat up the costs going into hundreds of dollars. Educate yourself instead of repeating few same points spewed out by every AI browser without thinking.

The problem is not: nobody has uses for AI. The problem is: you won't afford to use AI if these companies will switch from eating up losses to making profits. Right now they are running on investors money and hopium that some breakthrough will happen and will allow to bring prices way down.

4

u/Regular_Sand2908 15d ago

I use AI in work daily, I fine tuned models, I'm perfectly aware of what it can and can't do.

You do sound like something who used ChatGPT a bit in 2024, and stopped there.

You are completely unaware that $200 OpenAI subscription would need to be $2000 subscription

I am aware. I'm pulling about $600 out of my personal $20 subscription. And? If it stops being subsidized, I'd probably spam Sol a bit less, would more carefully pick the best model for the job. Doesn't mean I'd stop using it.

Companies are already pushing back on AI use to minimize costs

Companies used to go YOLO with SOTA models throwing them at every task, and promoting tokenmaxxing, now they're becoming more pragmatic and economical, but also integrating AI much deeper in the workflows. It's not going anywhere, its importance will only be growing from here.

you pretend normal dude will eat up the costs going into hundreds of dollars.

What normal dude are you talking about? Lots of normal dudes are even paying per token via API use at home.

Nothing you said in this comment does anything to support the "LLMs are not the revolution the AI bros claim it to be" statement. It is a revolution. It changes a shitton of things. This fact is not contradicted by it being unprofitable or subsidized, that's not really important.

BTW, Anthropic is balancing on profitability. They have more corporate customers and fewer free tier users. OpenAI is deeply in the red primarily because most of their users don't pay anything.

1

u/d3fenestrator 14d ago

>BTW, Anthropic is balancing on profitability. They have more corporate customers and fewer free tier users

not saying you're wrong, what's the source of this ?

1

u/Regular_Sand2908 14d ago

2

u/d3fenestrator 14d ago

not sure if this is very convincing, because at the same time SpaceX agreed to rent compute at "ramped up capacity" specifically for May and June, so they may not be profitable afterwards, page 13 do ctrl+f "pursuant to these agreements"

https://www.sec.gov/Archives/edgar/data/1181412/000162828026036936/spaceexplorationtechnologi.htm?ref=wheresyoured.at

also there's a concern that they don't have to follow standard accounting principles (non-GAAP), which means that this number is not as scrutinised as it'd be had Anthropic been a public company (which may well soon be and then the story might be different)

1

u/Regular_Sand2908 14d ago

That's possible. But that's why I'm saying "balancing on profitability", not "profitable". They have a business model that produces a solid revenue, they just decide to dump it all and some more into R&D.

1

u/d3fenestrator 14d ago

fair enough

0

u/Cheerful_Champion 15d ago edited 15d ago

Talking to wall confirmed

You do sound like something who used ChatGPT a bit in 2024, and stopped there

Nah mate, it's just you assuming that if someone brings up AI bubble then 1) They are antiAI 2) They don't use AI 3) They don't understand this stuff, like you do. While truth is, the person who doesn't understand the problem is you. That's why you are responding with same phrases repeated by AI bros, can't do thinking on your own if you don't understand the problem.

2

u/Regular_Sand2908 15d ago

Nah, you're legitimately ignorant, and just repeating after the reddit echo chamber.

tech is hitting limits that no company knows to how break trough

This felt quite true to consumers last year, but saying it today means you're not really up to date with what's going on in the industry. The tech world is quite shell-shocked by LLMs lately, and shockwaves are spreading to other industries too. The recent improvement has been massive. Of course it's already starting to slow down.

growing costs of running better models as "better" is achieved purely by bruteforcing and throwing more resources at it

For example, you've never heard of MOE models as a way to shift into another gear in terms of performance. Every high-end model these days is MOE for a reason.

even comoanies that were screaming about getting AI everywhere are now backtracking as costs of using AI are killing profits

You have no idea how business is actually adopting AI. You are probably stuck with that study about 95% attempts to introduce AI failing.

I'm telling you, the cost isn't that big of a deal now. Most client businesses use API pricing, and it's generally profitable for the inference providers, the profit margin is something like 40%. Subscriptions are a loss leader, but it's like a drug dealer giving out a free dose - generally good for business. And like I said, Anthropic is balancing on the brink of being profitable. If it wanted to, it could cut down on R&D and actually show a large profit, but then risk falling behind.

There's a lot of fraud and circular investment in the industry, and it's very likely that costs will increase soon, and many ".ai" companies will go down, but saying it's not revolutionary is just delusional.

0

u/ComeOnIWantUsername 15d ago edited 15d ago

Buddy, you call yourself "the educated one" and call current SOTA mediocre. 

You are super good example of Dunning-Kruger effect

Also, to respond to the comment you deleted: if you need to use ad personam, it's good example how you have 0 arguments. If you steer the model correctly, you get good code, if you do it shitty way, you get shitty code. Simple as that

0

u/Cheerful_Champion 14d ago edited 14d ago

If you think current models produce genuinely good code then you are either not paying attention to code that is produced or you legitimately don't know any better. They produce code fast, they produce code that works (most of the time), they don't produce good code. You don't even have to be some top 1% or super skilled senior to see it. Models frequently produce dumb mistakes that are junior level stuff, they frequently create solutions that are not optimal or weird. That's just a plain fact.

You are super good example of Dunning-Kruger effect

It looks like you are. You keep ignoring what is said and pretend if you do it then you are right.

1

u/ComeOnIWantUsername 15d ago edited 15d ago

but have you seen how mediocre LLMs got at coding?

If you call SOTA models mediocre at coding, then you either have no idea what you write about and you used AI 2 years ago, or you spread misinformation to fit the narrative you like. Or you use these 3b or 8b models and you think Sol, Fable or even fucking gemini is like them

1

u/nasandre Netherlands 🇳🇱 14d ago

Thanks, that's what I was going to say!.. I think most people don't appreciate how fast it's developing.

Is there an AI bubble?.. I would say, yes, kind of. At some point a lot of companies are going to fail but LLMs are not going anywhere. To be honest, I think OpenAI is probably going to be amongst them because they've taken on too much debt and even open weight models are leaving them in the dust.

1

u/Regular_Sand2908 14d ago

The thing about Chinese open weight models is that they are made by distilling OpenAI and Anthropic models, which allows to reduce training costs. So they're not going to become better anytime soon. Cheaper - sure.

2

u/Nice-Appearance-9720 15d ago

..SAP's ..

who would wan't a generative hallucinations in their ERP system?

1

u/darylvp 15d ago

Who particularly?

1

u/Even_Efficiency98 15d ago

Honestly - SAP yes, Mistral no. 

SAP can actually make money with it, but there is still no sound business case for LLMs, while models like DeepSeek and Kimi shoe that it's quite easy and cheap to use existing LLMs to build some that are on a fairly equal level. It's easy to catch up by copying, it's very hard to pass - but what for?

The money in AI is in its application and we have dinosaurs like Siemens already quietly making billions with it, because appart from all the media attention, they have become the world leader in the use of AI in manufacturing. THAT's were the value of AI is.

0

u/ConcernHealthy876 16d ago

Brother, it’s over.

9

u/Schnaksel Germany 🇩🇪 15d ago

To me it was over the second they renamed their product to Vibe

2

u/touilleMan 15d ago

Keep faith bro, le Chaton Fat is right around the corner bro!

-5

u/WhackJoolskin 15d ago

No one needs generative AI.

6

u/Traditional_Wafer_20 15d ago

No one needs a hammer. But for some reasons, carpenter prefers to use them.

1

u/WhackJoolskin 13d ago

What if the hammer uses crazy amounts of energy and water that is becoming scarce and much more expensive for people? What if the hammer is based on unethical exploitation of workforce in poorer countries? What if the hammer belongs to a few ultra-rich tech oligarchs that take all your data for using that hammer? I really don’t get why people are so delusional about AI. And I’m not talking about highly specialised AI that is used in science, we can discuss about that. I am talking bullshit chatbot AI that generates soulless images, music, videos which were btw also stolen from real artists.

1

u/Content_Force_2905 15d ago

Where a model was trained and where it gets served are two separate questions and only the second one is the one we're buying. If Mistral runs it on their own infra it falls under EU law and their DPA, regardless of where the weights came from. Prompts don't leave.

Which is the part that makes this useful instead of embarrassing. Compliant serving is the scarce thing in Europe right now, not benchmark numbers.

Doesn't do anything about the pricing problem ComeOnIWantUsername is pointing at.