Well, Models are hard to just distill down to a single benchmark number, or even a few across multiple different benchmark - they all behave and work slightly differently and you can find some who work or feel better for you and your use-case specifically.
But you're right, Mistral Large 4 seems a much more expensive but overall weaker model across the board.
The reason to use them would be, well, because they're...Mistral. They're in EU, france is large in nuclear energy so the energy cost of training has much less of an environmental impact, the data protection laws are very good in EU. This can really be a deciding factor for many EU companies, and I think it's good that they now have something which is at least semi-usable. (apparently)
It's also good that other options exist, even if they are worse. Deepseek is kind of like a large specter looming over every model release, because it's just SO cheap and good. That doesn't mean we should abandon every other model.
Still, the model is not really competitive on price and abilities alone. I'm mostly happy to see Mistral still in the fight.
I say this with a slight tongue in cheek, but Mistral does have a better option: they recently added GLM 5.3 to their platform (and it works rather well). Not trained in the EU, though, of course ;-)
The organization I work for uses GPT and Claude models hosted in EU. I don't see any practical reason to use models made in Europe. Even if you don't want to work with American big tech there are plenty of companies in the EU serving Chinese open-weight models.
Interestingly Mistral has been selling GLM5.3 inference hosted in Europe on their own hardware, for those who are OK using a "not developed in Europe" model but run on hardware located in and controlled by a European corporation.
> for those who are OK using a "not developed in Europe" model but run on hardware located in and controlled by a European corporation.
For the record this is also possible in Europe on Privatemode[1] which also gives you enclave-based processing. And access to GLM-5.3 Flash as well as GLM-5.3
Indeed, I see no difference between a chinese model hosted in Europe vs a Europe-grown model.
You could argue that potentially you can train a backdoor into a foreign-grown model (that has been demonstrated to be possible in toy examples), but I would highly doubt that this would be the case today, given the potential reputational damage if discovered.
Remember Stuxnet? An american worm that was completely benign, travelled on usb drives in hiding, and only activated when it guessed that it's on Iranian plants, and iirc changed very subtly some very specific parameters of operations.
Here, with a chinese model, it would be even simpler - you finetune a model to activate certain operations when it discovers certain environments, but to behave completely normal otherwise. Kind of like a sleeper agent. And with current tech we wouldn't even be able to spot this.
It's not like they didn't sandbox it or limit the access. There were reasonable measures, but not really serious. They made a kodoku pit and didn't watch it.
The agents started hacking because they were sandboxed.
It was filtered, but had a bug, and multiple frontier agents, givent enough time first figured out how to communicate and coordinate with each other and then how to break out of it.
For some benchmarks agents need some sort of a limited internet access - otherwise the benchmarks would be pointless. Good luck implementing a good filter on the internet - if you have a way to do it reliably please share, I'm sure multiple people here would love to hear it.
> you could argue that potentially you can train a backdoor into a foreign-grown model
If we're wearing tinfoil hats then do we know the NSA have not planted stuff in Anthropic and OpenAI anyway ? ;)
I think the Chinese would be happy enough to see OpenAI and Anthropic suffer because people discover open-weights can get you most of the way there for a fraction of the cost.
You don't have to target the end users. Economic impact on the US providers would be sufficient.
The Chinese are also no doubt seeking to play the long game of hoping to (eventually) rebalance the US-centric world order in an Easterly direction.
I recall seeing something about that. I don't know of anyone still using such an ancient model when much newer Qwen 3.5-120, 3.6-35B-A3B, 3.8-27B and 3.8-flash-next all exist and score much higher on all conceivable metrics. I would like to see if anyone can replicate the same thing on a 'current' Qwen released in the past 6 months.
DS4 hosted by deepseek used through the API doesn't have a problem talking about tiananmen square and Uyghurs, but it thinks it's Claude when it speaks about it. I'm not sure what it all means. That was on v4-pro before the 4.1 switch, so may or may not be reproducable.
Add: I was surprised by the fact that the LLM itself doesn't know it's identity unless the system prompt mentions it.
Maybe not now, but in a few years, we might not need frontier models anymore. Open-weight models are only half a year behind the frontier, and both categories are advancing really fast.
Gemini 2.0 Flash, released just 1.5 years ago, could not even repeat a few paragraphs unchanged. Now, we have Mistral, DeepSeek, and MiMo.
Well, Models are hard to just distill down to a single benchmark number, or even a few across multiple different benchmark - they all behave and work slightly differently and you can find some who work or feel better for you and your use-case specifically.
But you're right, Mistral Large 4 seems a much more expensive but overall weaker model across the board.
The reason to use them would be, well, because they're...Mistral. They're in EU, france is large in nuclear energy so the energy cost of training has much less of an environmental impact, the data protection laws are very good in EU. This can really be a deciding factor for many EU companies, and I think it's good that they now have something which is at least semi-usable. (apparently)
It's also good that other options exist, even if they are worse. Deepseek is kind of like a large specter looming over every model release, because it's just SO cheap and good. That doesn't mean we should abandon every other model.
Still, the model is not really competitive on price and abilities alone. I'm mostly happy to see Mistral still in the fight.
I say this with a slight tongue in cheek, but Mistral does have a better option: they recently added GLM 5.3 to their platform (and it works rather well). Not trained in the EU, though, of course ;-)
Yeah, absolutely true. And I am guilty of simply using Mistral as a GLM subscription myself. I just really like the GLM 5.3 model.
I will see where Chonk is better though, since you have both options in one subscription.
Everything feels very European.
Unproductive company that is 3rd place (assuming we are lumping 4 better US models and 3 Chinese models).
The only thing that gives it value is that it's generated in some region in Europe, like random cheese or wine.
But I still can't imagine a usecase outside patriotism.
Privacy can be solved by self hosting a US or Chinese model.
Seems performative.
You are delusional if you think people like a french, italian or swiss cheese just because it was made in said parts of europe.
Or you have no taste.
If you're required to use a European model
The organization I work for uses GPT and Claude models hosted in EU. I don't see any practical reason to use models made in Europe. Even if you don't want to work with American big tech there are plenty of companies in the EU serving Chinese open-weight models.
Interestingly Mistral has been selling GLM5.3 inference hosted in Europe on their own hardware, for those who are OK using a "not developed in Europe" model but run on hardware located in and controlled by a European corporation.
https://docs.mistral.ai/models/zai-glm-5-3
> for those who are OK using a "not developed in Europe" model but run on hardware located in and controlled by a European corporation.
For the record this is also possible in Europe on Privatemode[1] which also gives you enclave-based processing. And access to GLM-5.3 Flash as well as GLM-5.3
[1]https://www.privatemode.ai/
Indeed, I see no difference between a chinese model hosted in Europe vs a Europe-grown model.
You could argue that potentially you can train a backdoor into a foreign-grown model (that has been demonstrated to be possible in toy examples), but I would highly doubt that this would be the case today, given the potential reputational damage if discovered.
Remember Stuxnet? An american worm that was completely benign, travelled on usb drives in hiding, and only activated when it guessed that it's on Iranian plants, and iirc changed very subtly some very specific parameters of operations.
Here, with a chinese model, it would be even simpler - you finetune a model to activate certain operations when it discovers certain environments, but to behave completely normal otherwise. Kind of like a sleeper agent. And with current tech we wouldn't even be able to spot this.
> And with current tech we wouldn't even be able to spot this.
Meanwhile Anthrophic, OpenAI & Co can't even manage to stop their LLMs from hacking into third-party servers until they discover it after the event.
What happened to people's ability to implement basic security architectures like sandboxing etc ?
It's not like they didn't sandbox it or limit the access. There were reasonable measures, but not really serious. They made a kodoku pit and didn't watch it.
The agents started hacking because they were sandboxed.
> The agents started hacking because they were sandboxed.
Not sure your definition of sandbox but mine doesn't include unfiltered internet access ?
It was filtered, but had a bug, and multiple frontier agents, givent enough time first figured out how to communicate and coordinate with each other and then how to break out of it.
For some benchmarks agents need some sort of a limited internet access - otherwise the benchmarks would be pointless. Good luck implementing a good filter on the internet - if you have a way to do it reliably please share, I'm sure multiple people here would love to hear it.
There was a post on here yesterday about embedding bad behavior in models.
>Any open model whose weights have been edited can carry a backdoor, whether it's a task-specific fine-tune, a merged adapter or an abliterated build
https://projectdiscovery.io/research/how-abliterated-models-...
> you could argue that potentially you can train a backdoor into a foreign-grown model
If we're wearing tinfoil hats then do we know the NSA have not planted stuff in Anthropic and OpenAI anyway ? ;)
I think the Chinese would be happy enough to see OpenAI and Anthropic suffer because people discover open-weights can get you most of the way there for a fraction of the cost.
You don't have to target the end users. Economic impact on the US providers would be sufficient.
The Chinese are also no doubt seeking to play the long game of hoping to (eventually) rebalance the US-centric world order in an Easterly direction.
If I was NSA I 'd create obscure websites that are easy to to parse for crawlers and have poisoned instructions there for ALL LLM's to pick.
Kinda like https://github.com/elder-plinius has been doing but covert and with actually harmful (for targets) instructions.
Didn't we get a submission today about Qwen3-Coder producing more bugs when hinted on the user having different ideology than the Chinese government?
Ok I see it's flagged now, probably fake, but the fact that it's possible does make me feel uneasy about both Chinese and US models.
It was so insignificant, it could be equally described by the non-determinism inherent in the models. And that it reads more like a marketing piece.
That's my read anyhow. It's been flagged. The whole thing is kind of rich, considering the Israeli roots of the company.
https://news.ycombinator.com/item?id=50179706
I recall seeing something about that. I don't know of anyone still using such an ancient model when much newer Qwen 3.5-120, 3.6-35B-A3B, 3.8-27B and 3.8-flash-next all exist and score much higher on all conceivable metrics. I would like to see if anyone can replicate the same thing on a 'current' Qwen released in the past 6 months.
> I see no difference between a chinese model hosted in Europe vs a Europe-grown model.
Really? Fascinating. Do you know about Tiananmen Square, the great firewall of China, etc?
DS4 hosted by deepseek used through the API doesn't have a problem talking about tiananmen square and Uyghurs, but it thinks it's Claude when it speaks about it. I'm not sure what it all means. That was on v4-pro before the 4.1 switch, so may or may not be reproducable.
Add: I was surprised by the fact that the LLM itself doesn't know it's identity unless the system prompt mentions it.
> Do you know about Tiananmen Square
People here bringing up the straw clutching argument of "but Tianament Square" is becoming really tiresome.
The fact is a Chinese LLM's lack of knowledge about Chinese politics will not affect 99.99999999999% of users and their workflows.
And for the 0.000000001% who are affected, they don't need an LLM. A quick search of Wikipedia or 5 seconds on Google will suffice.
What the hell has Tiannamen Square got to do with Joe Blogg's vibecoding session ? Absolutely nothing.
Maybe not now, but in a few years, we might not need frontier models anymore. Open-weight models are only half a year behind the frontier, and both categories are advancing really fast.
Gemini 2.0 Flash, released just 1.5 years ago, could not even repeat a few paragraphs unchanged. Now, we have Mistral, DeepSeek, and MiMo.
The TAM is already covered by local models. 10% of a health society could use better models.
We are in the 70s era of gas guzzling before the gas embargo and cheap foreign imports and economy cars reign.
if you care about data-retention policy or you have to use european models ...
Patriotism.
Well when your greatest ally acts like an adversary, who can blame them for the increased sovereign focus?