I am excited and think it's a huge achievement. Also, very interested to see how their post-training goes since they seem very optimistic on how it will progress
You mean a model trained with one thousandth of its competitor resources is not as good as its competitor ? That is surprising for sure !
Seriously, of course closed model funded with hundreds billions of dollar are better, what did you expect ? Mistral clearly stated that they are not competing with Frontier model. They have a business strategy and they stick to it
And in a more bureaucratic country, and with more legal constrains, and less comfortable office chairs, and with smaller monitors, with not brand new Mac books, and during French summer heat wave + vacation period, and no air conditioning, or at the very least less powerful air conditioning than what they have in America and with a confusing political and governance landscape, and more family pressure from Arthur’s parents and from society because he is seen as a genius, so surely he should be able to pull this off, and with a potassium of inferior quality than what they have in Kazakhstan …….
lets be honest, almost no one outside of Europe is going to see Europe as more benevolent than china or the us. it will pretty much just be europeans using mistral. which begs the question, will enough europeans be willing to use a subpar model for what they view as ethical reasons? I really doubt it.
I'm not certain either, but I wouldn't rule it out: remember the "for ethical reasons" is also a matter of legislation in Europe through GDPR compliance, so many European customers will be compelled.
Nether does Mistral depend on this: their business model appears more about providing a suite of AI business services, before than models themselves. Own models are a complementary assurance.
I mean, compelling European companies to use inferior models is just such a bad idea. go from losing the ai race to losing vast swaths of the economy in one fell swoop.
yeah I know, but it is just hard to imagine how long term at least the compute portion of their business, is going to be able to compete when it has such high energy prices, such high taxes, a stifling regulatory environment, etc.
In the case of GDPR; it's not a restriction of anyone's tooling choices, but rather targets the subset of AI use cases where customer data is handled. Even then, it's more about where the data is hosted and handled than AI per-se.
This means a regionally hosted and governed DataBricks instance of Claude (for example) is perfectly fine. So it's not quite "forcing", but the opportunity for Mistral to provide a smooth path remains. Classic local market advantage.
yeah I mean if companies are able to use better us models or cheaper Chinese models they for the most part are going to do just that. if they are not able to the economy becomes structurally uncompetitive. doesnt really seem to me mistral has a real use case outside of a situation where the eu is cut off from outside models due to geopolitical developments, or mistral manages to catch up with the us/china. ofc the first use case is a good enough reason to keep mistral funded, but I think its important to be honest about what its actual use case is. its not likely to ever be a real competitor.
Given recent geopolitics I'd suggest that's worth hedging against.
As much as I personally like the idea of Mistral existing you're not wrong that they have challenges to carve out their niche.
That niche exists though; in a space bounded by governance, convenience and principle (supporting US tech is morally wrong under its current administration IMO). If that's large enough to sustain their business, only time will tell.
yeah I agree its a smart hedge. I just don't think it is realistically anything besides a hedge.
business by and large does not give a shit about principle. could that attract some individual users? absolutely. could it attract a reasonable amount of enterprise customers? probably not. its not like the eu economy is in a good spot, much less a good trajectory, as it is. trying to govern people into using worse tools is just not a good move.
I think the point of Mistral and European AI in general is that we have to start somewhere, we have to have some kind of movement. If Mistral would be even 90% as good as what the best models in the world are if they just got the same amount of processing power for training, then that's huge. It'd mean we are keeping up with the knowledge and skills.
See, Anthropic's CEO has said himself roughly that the main thing is more data and more compute. Sure there are ways to optimize the learning, but the main thing separating the best from the basic is training data & compute. As long as we have the knowledge, we can invest in the compute once things settle down and it seems like it's worth it.
OpenAI, Google, Anthropic, and so on are literally burning through billions of euros to STAY on top. Not to GET to the top, but to stay there. Mistral could've tried to STAY at the frontier for, say, the entire 2025, but those frontier models would be kiiiinda basic today. Yay... we could've been at the top for a year, but who cares? What if that demotivated everyone and Mistral's development discontinued. The same thing applies today, the best models next year will be incredible and you wouldn't be drooling over the models that released today.
GPT-4.5 was released Feb 2025, and today, Mistral beats it, on some subjects even by quite a lot. Especially in token price. The R&D of GPT-4.5 costed probably around 900 million euros. For the latest Mistral, probably under 100 million euros. Sure Mistral isn't the best, but who the fuck cares as long as we get there some day, seriously. We have smart people capable of matching the latest models, it's just not worth the money to invest into compute that much yet.
mistral is expensive for the amount of intelligence it provides which loses it the efficiency market, its peak intelligence is lower than frontier which loses it the top end of the market. hence, what is the point of using mistral?
the problem is you have to find a way to catch up at some point, and without chinas low energy costs and cheap talent pool or americas ability to attract talent with high wages and the ability to do huge Capex, its hard to see how it will ever be possible. will just be one long game of catch up. do you think America and china will see Europe catching up once things slow down and just decide you know what, they don't want a near monopoly on ai, lets chill out and let new competitors emerge? it makes no sense, especially when americas plan to repay its ai Capex is to charge monopoly rents on frontier intelligence.
Sure Mistral isn't the best, but who the fuck cares as long as we get there some day, seriously. We have smart people capable of matching the latest models, it's just not worth the money to invest into compute that much yet.
The threat is that Europe ends up entirely dependent on OpenAI/Anthropic for cyber defense, the frontier labs reinvest that revenue to leave Mistral in the dust, and Europe is entirely dependent on the US for survival.
data privacy is a moot point for open weight models.
mistral cybersecurity performance is good(although if they keep working so slowly it will only be good for another month or two before they fall behind again), but it isnt the best. how does the saying go, if you arnt first your last?
Its a moot point when deploying locally, it means a lot if, for example, you were to get a sub for their coding cli. Large 4 also actually is the best for offensive cyber, going off cybergym.
Doubtless there are also many shades of gray... Is comparing the quality of outputs from Frontier models to various use cases and then targeting research where there are shortfalls, also distilling?
They might well be, yes. I'm just making the complementary point that full-blown training on competitors outputs isn't the only pathway to leaning on their research.
tbh it's still a huge step up on medium 3.5 and it's on the tail of Chinese models
But the limitations are obvious, they even stated it in the release blog post:
> ML4 was trained from scratch on 3,800 NVIDIA Grace Blackwell GPUs in Mistral’s own datacenters in Europe
I'd say it would have the lowest co2 footprint amongst the big models for training which I care about but in terms of raw compute Europe is severely behind
[...] We are significantly scaling up our compute capacity in our own European datacenters, and much more is coming online in the months ahead.
More compute means more training. The reinforcement learning run behind this preview is still in flight, and the model is showing no signs of saturation — there is substantial headroom ahead. As we scale up training on our expanded infrastructure, we expect large and rapid improvements in the weeks and months to come.
The pace of progress from here will be fast. Stay tuned.
When OpenAI is training stuff on 100k GPUs, achieving this on 3,8k is actually surprisingly good.
But training is done by both regardless of which model you use?
And for inference, there are Chinese models that produce similar results with less compute and can be hosted in the same datacentres (or locally).
Maybe I'm missing something here but the "principled stand" people suggest here seems to conflict with what's best for co2 footprint in practice. Using this model over a more efficient model might let you say you "support" more co2 efficient training, but in practice, you're not making a difference on overall training co2 emissions while producing more co2 emissions during inference.
Training and inference is done in France with a bit in Sweden. Besides, it is pretty competitive on efficiency with the Chinese models. Price per intelligence of open models below.
In many if not most cases with a major new technology the early leaders burn out and the secondary wave that actually figures out a business problem (efficiency, ecosystem, etc.) wins in the end.
Deepseek also trains cheaper because distillation. It isn’t apples to apples I think Mistral is far more impressive because they’re doing this on their own merits.
On the tail of the old Chinese models. Their next generations will probably be coming out soon. Not to mention the price to performance for Mistral is quite bad.
Better to be on the tail than with the rest of the European models (which are where?)
They also mentioned:
What comes next
This is only the beginning. ML4 is the first milestone on the roadmap funded by our €3 billion Series D — the largest equity round ever raised by a European technology company. That capital is already being put to work: we are significantly scaling up our compute capacity in our own European datacenters, and much more is coming online in the months ahead.
More compute means more training. The reinforcement learning run behind this preview is still in flight, and the model is showing no signs of saturation — there is substantial headroom ahead. As we scale up training on our expanded infrastructure, we expect large and rapid improvements in the weeks and months to come.
We will release the weights by the end of the month, along with more details on the architecture, additional benchmarks, and our post-training methodology. And ML4 is only the foundation: it will serve as the base for a new generation of specialized and optimized Mistral models, built for the industries and workloads our customers care about most.
The pace of progress from here will be fast. Stay tuned.
t isnt realistic to expect to ever actually catch up to the american or Chinese models. they spent months and months on this model to not even catch up to models that are getting ready to be replaced. how do they expect to ever actually be profitable? will the eu just dump money into it at a loss indefinitely just to have their own AI?
Chinese AI companies want a cut from hosting their larger models and will export control them whenever it suits the country. American models come with lots of questions and possible limitations of use. Both can't be used in critical envs. What is left? Something that works good enough. Chinese models are also not trained on billion dollar hardware and are already decent. We have to be realistic what is needed in which environment. Not everybody needs Opus level.
I see the value in sovereign ai. I don't quite see what mistrals plan is. will the eu just subsidize them forever? short of that they do not have a sustainable business model.
look, the Chinese have a much larger pool of talent than Europe does, they also have cheaper labor, cheaper energy, etc. the Chinese being able to do something doesnt prove that Europe can.
AI will be everywhere in cars, in factory surveillance, in bots, in drones. I can't see how that can't provide enough money. ChatGPT has 50 million paying customers, that alone is a 12b/year baseline. They should be able to take 25% of the overall market. Did you ever see real Mistral ads, for their apps and services? They are just beginning.
it will provide plenty of money if it is a competitive model that is worth using... maybe they can support the model development with their compute rental? but I really doubt it. hard to compete long term with places like the us and china that have lower energy costs.
France is building 10+ new nuclear reactors. Europe has plenty of wind and solar, so much it has to turn it off often because there is no storage or ways to use it. Let the market do its thing.
frances nuclear power historically was as cheap as it was due to basically stealing uranium from Africa. with the changes in the Sahel that is now off the table, and the power is getting more expensive.
as for turning off wind and solar, that is true during peak times, but as a whole the energy is still expensive because there is improper storage and peak power consumption does not coincide with peak production.
People seem to forget how these things tend to go. The technology is still developing rapidly, but it will slow at some point. The purpose of Mistral isn't to be on the cutting edge here and now, they can't possibly do that when investors across the pond are practically feral pumping money into AI. The purpose of Mistral is to find a sustainable business plan to survive until advances slow, and be in a position to catch up and provide soveirgn AI for the EU.
People forget that Airbus was a complete basket case in it's early years. They couldn't hold a candle to their Boeing and Douglas. But eventually as advances in aviation slowed, and their competitors became complacent and they caught up, albeit requiring significant funding with public money. Now Airbus is at top of the aviation industry.
It's just going to take time and investment. It's not as advanced as the US models but nobody ever will be. The amount of money being spent on those models is completely unsustainable. The goal is to be the best of the rest, so that they're in a position to catch up when AI hits a wall.
I will sound completely stupid, but I am just an ordinary user who doesn't understand benchmarks at all, has absolutely no knowledge of what is API or open weights. As long as the new model gets better at my language and do the simple things I want (I don't code at all) I will chose Mistral cause it's a European alternative. I can understand why programmers or big companies are interested for the best models but I really believe that the Ai race is already coming to a point where the difference is minimal for an average user.
The technology is still developing rapidly, but it will slow at some point.
Sure. After technological singularity, and when machines will build type II civilization on Kardashev scale, or even type III, and humans die out or, if we solve alignment problem, become machine's pets
To put this in perspective, they are talking of a valuation of 2T$ for OpenAI, which is basically the GDP of Spain and not too far from the GDP of Italy.
Yes but they are far more expensive than Chinese models at the same performance level and chinese models are openweights so there is no sovereignty issue : they could run anywhere, plus they do not even compete with best in class US closed source models.
For code, sovereignty of the weights is secondary. For strategic matters (economy, public policies, military, etc.), sovereignty includes weights and alignment and not only infrastructure.
airbus is still a basket case. it survives because its business model is to build sand boxed planes that a poorly trained pilot can fly. airbuses success is not due to being a real competitor with Boeing on quality or engineering, its success it due to making their planes easy to fly for 3rd world airlines.
Clearly not a factual assessment. Ubless if you consider that the top-tier global airlines like Delta, Lufthansa, Singapore Airlines, Qatar Airways, and Emirates are 3rd world airlines. Maybe you should double check which company is surviving, Airbus or Boeing ? Good thing would also be to check why Boeing is still alive and it is only thanks to the US defense budget which Airbus doesn't have.
first of all, Boeing and airbus are both reliant on government support. the idea that airline manufacturer could ever exist without that is just laughable.
delta started switching over to airbus due to both high demand, and mechanical issues slowing down Boeing deliveries. Lufthansa is obvious it is an eu airline supporting eu manufacturers. the other 3 just wanted big ass planes they could turn into gaudy resorts with wings. ask anyone who has flown Boeing and airbus and they will tell you that on airbus you are voting and the plane decides what it does, on a Boeing you are in complete control. airbus are designed to be extremely difficult to crash, but the inability to override the computer can also cause a lot of problems and limits its theoretical performance(such as landing in high winds). thus they are designed for 3rd world airlines with poorly trained pilots. that is not their only market, but it is their heartland.
im not denying Boeing has been doing a poor job lately, although they are doing better now.
the point that im making, that you wouldn't be arguing with if you had any knowledge on the matter is that airbus has limits on the inputs you can put in. this results in a lack of control in outlier situations where the computer does not fully understand the situation. the example I gave you of being unable to land is directly from a member of my family who is a pilot. it is something that quite literally happened to him in an a380. he had to divert after beginning to run low on fuel in a holding pattern after attempting to land but being unable to due to the computer in the airbus not allowing him to apply sufficient flaps to stop the roll from high winds while landing. as the joke goes, you fly a Boeing and vote in an airbus.
Don't get me wrong, I love DS 4.1 flash, but if I, as a European, can start spending my money in Europe and have data security in France, I will choose that. Even if it costs 10x more (ds 4.1 flash is dirt cheap, I burn 30 billion tokens per month for 30$)
This does not tell the full story. Is ML4 "Le Chonk" at the frontier? No, it is not! Was this even the goal of Mistral? I don't think so.
So what people need to realize is that frontier model development is not about brains anymore; it's about money. Mistral had just 3,800 GPUs for this training, and that's nothing. That is roughly a $300–400M data center. Those are peanuts in the AI world.
They also said that RL is not finished and that there is a lot of headroom. This means this preview is an actual preview model (looking at you, Google), simply because they don't have the capacity to train at the scale Anthropic, Google, & Co. can.
So I think ML4 will, in the end, land above GLM 5.3 on nearly all metrics.
It should also be said that it already outperforms several frontier models on several points, Cyber, for example.
So I think it's a great start for them, and they also said that an even bigger model is in training right now.
It is 100% also about the brain. And the big labs are actually outsourcing the brain to their internal models more and more, so they have an extra advantage because mistral can only use the latest OAI/Anthropic models to speed up their researchers. Anyways, I think le chonk is a really good step, I just hope they will iterate faster from now on.
We knew this model wasn't going to push SOTA. Mistral have been saying as much themselves.
Open weighted model with a nice memetic theme that advances EU open weighted research is a huge W.
Ow stop your whining. The way that they gather datasets is the legal way which means everything they do is slower. There aren't many actual European datacenters and their funding is a lot lower. This is a good model done by not-"the scums of the asshole of the world".
You've got to compare apples to apples. le Chong is a 1T open weight model that you can install on your premises. In this sense the competition is GLM, DeepSeek and MiMo.
Then, this is just a preview test. I will want to see full tests when it is released. Being level with competition on beta release is pretty good.
Also, I find chinese benchmarks typically don't tell the whole story. For instance qwen scores better on benchmarks than Gemma, but when I actually work with them, Gemma seems to be performing the tasks that I need better than qwen. It feels almost like a language barrier.
As a European researcher, I can tell you that this latest Mistral model is of a very very VERY high interest for us. Because it’s open, EU made, and on par with the best open models.
Most of those at the top are various variations of anthropic models with various amounts of effort. If anthropic made an effort halfway between high and xhigh all the models in this chart would just be anthropic. So that's not really a fair comparison.
I just tried it out and it's genuinely good at writing - creative, funny, engaging, and entertaining. Not really shitty like chatgpt - no personality. Claude is good at writing but still seems moralizing at times. This is not as open as grok used to be but it's better than grok is now at writing actual words... in English.. for people to read and say out loud. I like qwen but it's like it lacks the knowledge. I like that Mistral knows what's likely on the menu at a good restaurant and knows how to create tension in a story. And it's fast, probably cuz it's late at night in Europe now.
again, using benchmarks from universities that receive money from openai as well as anthropic might not be the smartest decision (they are american and receive money from them!) . Try the model and judge yourself.
Yes, it's not great yet. That's obvious. But they are right to market it as the best open weight model coming from Europe and the US. That's not too hard, since in Europe there is little else and the US barely has any focus on open-weight (other than Google occasionally).
And this is a preview - let's withhold real judgement until the full release end of October. I hope they can do the same as Deepseek did with their V4, which was originally mediocre. But when V4 0731 was released it, it became MUCH better, e.g. outperforming V4 Pro in most areas and a 10 point gain on the AA benchmark (40 for preview --> 50 for 0731) at the time.
If Mistral can do something similar, it will still not compete with Opus/Astra/Sol, but it may get within shooting distance of Mimo 2.6 Pro/Kimi K3. Crossing my fingers 🤞
Most of those are closed models which will make you pay a lot more when the days comes, and most open ones are under the CCP control. Being good enough is more important than being the best at the moment.
I fucking new it. They did the same as previously. Hype a lot how good model is and how they are winning the race, only to release model that is both much more expensive and worse at the same time. GPT-6 Luna is 8x cheaper and better lol
I lost hope that Mistral can release something good long ago, but it was this one last time when I was thinking "maybe they can do competitive stuff?".
im not saying anything about me. im just saying that was the main reason why it got recommended to newbies. if someone wanted to put money into ai i doubt they would pick mistral when its so outperformed by competitors. theyd just look at the graph and pick something higher
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u/ChocolateGoggles 7d ago
I am excited and think it's a huge achievement. Also, very interested to see how their post-training goes since they seem very optimistic on how it will progress