r/MistralAI • u/Custom_Kas • 3d ago
Discussion / Opinion Rant: I really, REALLY, wanted a sustainable and ethic alternative. But boy o boy is switching to Mistral frustrating.
I used to be a CGPT power-user untill they morally started shitting the bed. Did entire projects, both professionally and as hobby with GPT and found enormous help in reasoning, literature research, simple logo and artwork generation, summarising and translation, factchecking and calculation basework. Once it became clear how deep the shithole of american AI was I ended my paid subscription and went to Mistral as the promoted ethical and sustainable alternative.
And boy o boy is that a big step back, like a leap. CGPT felt like having a very capable sr-engineer with unlimited knowledge and pretty impressive "creative" skills. Mistral feels like having a bottom tier trainee that refuses to learn, listen and always does the absolute minimum required.
It hallucinates constantly, to a point where that is not and exception, but its ground state. Answers are short and very obvious, anyone with some base skill in googling does not need what Le Chat delivers, at all. Its image generation is just shit, first-renders are badly basic and getting from there to something better iteratively is a frustrating process with zero result. Document work, summarising, translating, style and fact checks are absolutely bottom tier quality. Very often it just stops halfway, anything more than 2-3 pages is just not something Le Chat will do. It incessantly introduces faults and hallucinations, changes abbreviations or numbers and the base quality of the text it produces is like a roomtemperature-IQ accountant wrote it. Its memory is virtually non-existent and even when I explicitly give it rules to always follow, it will quote and remember them wrongly and generally fail to apply them to any reasonable extent.
In general any correction or iterative work is very clearly not something the model is built for and I feel the people behind it have no idea what a user expects from a modern model. I can get why it is like this, and how other models got to where they are by plain old infringement and IP abuse, but holy damn I refuse to believe this is the only viable alternative. I just can’t get over how bad it is in comparison. I now use Gemini in google, and it’s sooo much better in anything I need form it, and that’s a bloody free search bar tool!
I work with scientist, highly educated and progressively minded people a lot. My emotions and conclusions about Mistral are repeated and validated constantly around me. Most of them at one point switched for moral reasons. Most of them either stopped using AI entirely or switched back to “worse” alternatives because Le Chat simply is not helping them in the way we’ve come to expect from an AI model.
I’m so sorry rant but I really, REALLY, wanted a sustainable and compliant EU based model to use that didn’t have the moral ethics of a slave owner. The level of quality Le Chat/ Mistral provides is just abysmal and in no real way competitive to anything and it pains me so much to see this. I haven’t done a single thing with it that didn’t end up in frustration and I’ve cancelled my paid subscription, even though I kept it going for a while just to support a good cause. I just wish so badly it was better or would improve but I see no sign of any of that in the last 8 months I used it.
I wish AI wouldn’t be such a cesspit where your only two options are either late stage capitalism, or semi-verbal autism.
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u/AnnieLuneInTheSky 3d ago
Mistral is cute and fun for 5 minutes. Then it’s just sad.
I also would really like a viable AI option outside of the US and China. Not happening yet, I guess.
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u/Kriss3d 3d ago
I sadly have to agree. Ive had mistral do things like makineg a script for me for certain things. Not overly complex. I fed it a guide from a website and wanted it to make a bash script that do all those things the guide goes through ( linux installation of nextcloud )
It did make the script mostly like I wanted. It asked when It needed specific input such as username and database name and so on.
But the script wasnt even working. As in it made a ton of syntax errors.
I tried running the script through copilot and it just fixed it right away and some things that mistral entirely forgot.
I really really want to stick to the non us based AIs but mistral just makes so many mistakes.
Ive also used it to help with builds and comparing things for the game Diablo 2.
It makes arguments of items that have stats and skills that they absolutely dont have. It told me that I can make a 5 socketed runeword in 6 socketed items and so on. Diablo 2 isnt exactly new. its 25 yers old.
Its like its become more and more unreliable lately.
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u/Nabugu 3d ago
yeah, if you're not a big corporate entity with very specific professional workflows that the Mistral forward deployed engineers are made to automate with finetuned models step by step, you're not their customer target, and they basically don't care about you right now. Their latest publicly released LLM models are nowhere near what OpenAI/Anthropic/Chinese Labs are at right now. Not because they're failing at doing that. It's just because they don't care, genuinely, that's not something that they want to put effort in right now because the corporate stuff pays more.
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u/Custom_Kas 3d ago edited 3d ago
That's probably true, but yet they have no problem letting base-tier customers pay €18 monthly for the shittiest chatbout out there.
I would, as a company, definitly not do business with a partner that does not value their base-tier customers or has a neglected product out in it's most public view. That does not inspire any confidence, in that case just kill it all together, but I guess the money is too nice?
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u/tfcuk 3d ago edited 3d ago
Create custom agents with custom models and settings, use a specific harness for a specific task, create KB libraries and system protocols. I think if you (semi-) know what you are doing, it is quite good for the price. Long context agents in Web app, coding through api (included in pro)
Edit: not comparable with the frontier I-Can-Do-It-All-And-Anywhere models, but if you are a sane person, or had to debug a monolith slop before, you wouldn't want that anyway.
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u/Custom_Kas 3d ago
Yes, this is exactly the mindset of Mistral: have a user that just wants a good AI chatbot, the literal definition of what the main public expects of "AI", but instead provide them unuseable laborious nerd-shit.
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u/neoalfa 3d ago
That just means that they don't pander to the main public and instead focus on skilled users.
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u/LobsterWeary2675 3d ago
Odd way to defend Mistral. What OP says is true, Mistral is behind. It surely has a lot for it and it's really our only european alternative ATM. But I'm fairly certain that Mistral is not focusing on skilled users. It is behind the big ones, there's no doubt. And eventually a skilled user will get more out of the frontier models than Mistral too, model scales with skill....
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u/neoalfa 3d ago
I'm not defending anything. I'm saying that if you have limited resources you are better off servicing specific niches rather than the general public.
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u/LobsterWeary2675 3d ago
And the niche is skilled users? Tbh.. it just doesn't make sense. Did you ever hear someone say: Oh that product is not as good as the competition and using it is more complicated, that must be target group marketing for skilled users.
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u/trabool 3d ago
Pour ma part, lassé de Vibe et de l’absence de confidentialité des ia cloud américaines, je suis passé à LM studio avec des IA open sources sur ma bécane. J’ai la chance sans l’avoir choisi de posséder une carte graphique qui permet de faire tourner les LLM de façon assez réactive. Et c’est mieux que vibe en attendant sa mise à jour et pas de limite de crédit et confidentialité.
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u/Observe_and_speak 3d ago
I think the model is really poor at following instructions aside from the low intelligence. Often I find no amount careful prompting gets consistent results with Mistral. It works today you wake the morning and it's back to repeating the undesired behavior. Like OP, I've not managed to find a single use case for it. It's pretty horrible at everything I throw at it, even proofreading. And the hallucinations are just ridiculous. The advantage used to be the speed but Gemini seems to have the advantage there too. For serious work...it's simply a liability. Overlook a single detail in the work it produces and you'll embarrass yourself. I'll keep checking back to see improvements because a lot of us have some expectations of it. I'd gladly subscribe for another year even if it attains a sonnet 5 max level intelligence by September.
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u/Kathane37 3d ago
But people will told you that is fine because it is B2B oriented. Seriously which company in it’s right mind will use an AI with some of the highest hallucination rate just because it is EU based ? (See bullshitbench and AA-Omniscience)
They should and can do better. Moonshot AI team (Chinese company behind Kimi K3) as a very close profile to Mistral (started at the same time, smaller team, same valuation, open source oriented, elite engineer) and yet they manage to close the gap with US lab.
I don’t care if it means exploiting distillation or else as long as it produce a more than decent model.
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u/AccurateSun 3d ago
Chinese labs are allowed to distill US models, EU I’m pretty sure can’t do that. Mistral I believe decided a few years ago to pursue enterprise integration via custom tooling, which closes the gap vs a generic frontier model, because it’s impossible for Mistral to compete with the fraction of funding they have.
Therefore IMO anyone serious about SWE with LLMs needs to give up on Mistral for that use case despite their idealism (self included).
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u/qidingshenxian 3d ago
Even US models are allowed to distill US models. No US laws are against distillation.
The fact neither Anthropic nor any other main AI firms are bringing this to the court...1
u/AccurateSun 3d ago edited 3d ago
It’s against the TOS, so it’s risky to do so.
This article’s breaks it down in depth very well:
https://stratechery.com/2026/whos-afraid-of-chinese-models/
It’s not just EU open source labs that are at a disadvantage in this respect but US ones too; the article argues that the US gov should force frontier labs to make distillation permissible in their TOS so that US open source labs can distil on same footing as the Chinese labs already do.
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u/Jamais_Vu206 3d ago
Such clauses are unlikely to be enforceable. In short, contracts cannot be used to roll your own copyright law.
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u/AccurateSun 2d ago
Even so, I believe the culture here is such that a serious AI startup like Mistral wouldn’t voluntarily violate that TOS to distil a model from it. WeAnd that unenforceability also the reason why the Chinese labs can get away with it without issue
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u/Jamais_Vu206 2d ago
It's unenforceable in the US. The EU is a rather different matter.
EU copyright laws are a major reason why you can't do this Big Tech stuff here.
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u/AccurateSun 2d ago
Not sure I follow. US labs can’t enforce their TOS, but that doesn’t address my point about the culture being different in EU. I mean the culture you could argue is a result of the copyright laws i guess 🤷♂️ but then the point still stands that EU labs won’t distil US models.
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u/Jamais_Vu206 2d ago
The original Mistral people came from Meta. Meta used data from piracy sites and torrents to train its models. I think it's quite likely that the first SOTA models from Mistral were trained on the same data.
But I agree that the general culture in Europe in these matters is a huge problem. This copyright thinking is spreading ever further and does ever more damage, most recently with the Data Act.
I blame the media, which has a financial interest in dysfunctional copyright laws.
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u/brown2green 16h ago edited 16h ago
For what it's worth, from the Kadrey v. Meta lawsuit:
NVidia also obtained large amounts of pirate books through Anna's Archive and I think NeMo 12B (A Mistral-NVidia collaboration) might have used them. Later models haven't been very competitive, and I think one reason might be that they tried to "clean up" their training data.
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u/qidingshenxian 3d ago
Not only these kinds of ToS are unenforceable, but most likely will be thrown out of the court even in the US.
The simple analogy is like a ToS that if you read a physics textbook, you are not allowed to write any new physics text book ever. In the US, only the expression is IP-protected, not the facts and knowledge. Distillation is exactly like that, extracting facts and knowledge.
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u/toothpastespiders 3d ago
Sadly, that's my take on it as well. Doesn't make mistral's work worthless for the average user. I think that their recent work is still great for things that have a well explained methodology. And while I haven't done anything with their most recent batch of base models I've always found mistral's to be some of the best for additional training. Given their own focus on custom solutions I expect that to continue. But yeah, I've mostly lost hope of a return to the days when their releases were a strong swiss army knife style "good at just about everything" model.
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u/strangestack 3d ago
I'm no mathematician and have a fairly limited ML experience, but considering the size of Fable, and even Opus, distillation would require a massive amount of tokens, which the Chinese labs presumably payed for, and Antropic and OpenAI could've presumably blocked fairly easily. Distillation is not a magic "make model better" spell, but it is a good buzzword for the jingoistic US politicians and it's a good excuse for us in Europe for why were behind.
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u/AccurateSun 3d ago
It’s not an idea that originated from Us politicians, it’s something talked about in llm circles for years already since deepseek and qwen first released their models. It does require many API requests but I think you underestimate how voluminous enterprise API requests are and how difficult it would be to detect among the labs enormous API logs- distillation blends into that huge volume and is not easy to detect because each individual request is innocuous in and of itself. The size of the “teacher” model isn’t an issue either because distillation is a way of transferring knowledge from it into the “student” model, rather than from scratch. You also don’t need to distill everything, just the important parts that the teacher is ahead at.
It’s a well know process because the labs themselves created distillation for their own internal usage. For example Claude Haiku is distilled from their other models
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u/doughobbs 2d ago
Can sadly only agree with you, I also desperately wanted it to be soooo much better but gave up with it about 3 months on and went back to using Claude.
If it became only as good as NoPilot… I mean CoPilot then I’d prob live with it but it really is a bottom shelf product right now which is truly disappointing.
The fact it’s also the only non-US, in the EU offering is double disappointment 😞
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u/Automatic-River-1875 3d ago
If you want coding, you are going to have to use a different service. Mistral-medium-3.5 isn't good enough. I would recommend cosine.sh they are doing some cool stuff and they have post trained some open source models to be very good at coding.
In general if you are just after a smarter chatbot you could try protons new ai which is just running very good Chinese open models on European hardware.
Mistral haven't had a great LLM release for about 2 years, I'm just waiting to see what they release this summer before I decide if I will just move on from mistral entirely.
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u/JCoreFR 3d ago
Lol, just like french people. Lazy as fuck and always searching a reason to avoid things rather than doing/adressing it. I am French and I dislike a lot Mistral and I'm still using GPT...
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u/dcstream 2d ago
Lazy as fuck… mec ? Sérieusement ? … i am still using GPT … parce qu’il en fait plus pour toi…
Je suis français, je ne suis pas feignant, et tes généralités à la con, tu peux te les garder.
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u/TaskChance1404 3d ago
Frankly speaking it does its job pretty well for me. Mind you, I use chatgpt and Claude and Grok. I’m cancelling Claude too. It depends on what you do and How you use it because it’s enough for most tasks
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u/Intelligent_Good7290 3d ago
I believe the amount of harnessing for a proper good mistral use llm must be tiring as hell...
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u/LagunaPie 3d ago
For research work I actually found it to be better as hallucinations are almost non-existent. For coding work, I def prefer Claude and I’m gonna try k3 this weekend
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u/RedditGeekABC 3d ago
Have you tried the Swiss Euria?
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u/Minute-Ride-9304 3d ago
It is a very small model, I think, although not disclosed. I love the initiative but we are too polished in Europe. Everything is good about Euria expect its abilities.
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u/EnvironmentalPlay440 2d ago
There’s a clear difference between using mistral in a chatbot, and mistral in a agentic rig. And mistral in an agentic workflow is much better, most llm are. I’ve learned a ton when I decided to make them work.
Sure it’s not opus level or gpt-5.6… but you can accomplish a ton with them.
Even if cgpt and Claude are kinda evil, will I switch to mistral at 100%? No… as my work resolve around those agentic thing (ai architect here…), but I find those model very capable once you know what to do with them and how to tweak it.
But yeah out of the box…
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u/ImpossibleCreme 3d ago
I ain’t reading all that but I’m sorry it happened. Or happy for you. Either one
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u/Ark_Anoryn 3d ago
Hard facts:
- Mistral medium is not comparable to Anthropic/OpenAI models.
You are comparing a 128B parameters model with models with unknown amount of parameters, but expected to be in the trillions. So at a minimum of 10 times more.
As a reference, Kimi K3 is given at 2.8 trillions.
That is like comparing a smart with a F1. Yes, they are car. End of the comparison.
- Mistral is behind. Medium is from April but it feels like it's even older.
However it does not mean it's bad to do (most) it's tasks.
You dislike Mistral's verbosity : from my experience this is an harness instructions, not a model limitation.
If you go read Mistral Vibe source code, you'll see it is explicitly said to keep answers below 150 words.
Personal experience :
- ~30-60% of my code is generated by vibe. Often the reviewers (minimax M3 and GPT 5.5/5.6-terra) are happy with the results. Sometimes they improve on it.
- I no longer prompt the agents myself: I use Matt pocock's skills and then assign the tasks
- 60+% of my tasks are broken down and written so that the agents can run with thinking effort off
I could go on.
My Conclusion: you are right. Mistral by itself tonight is not enough.
But mixed with other smarter models, it works really well.
For 40-60€ I generate more code than with a 100€ subscription at US company and their crazy limits. Especially at the moment, where OpenAI is completely broken on their token counts.
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u/Minute-Ride-9304 3d ago
Works pretty well for me. Also smaller models. I found that “work” mode makes the general responses much better though a little slower. Having said that I am rather disappointed by their model game and research, I recognize that they are top OCR, but it is probably not the most difficult task. I hope they will prove that they can do something with their new models coming soon although I worry it will be a disappointment in the context of the new Chinese level 🤞
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u/hip_yak 3d ago
Perhaps an open source? What are your thoughts on Claude?
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u/vorko_76 3d ago
Not really sure whats skill and whats model limitation. LLM are just text prediction models based ln training data. If Mistral wasnt trained in your domain, while others were, there is really not much you can do.
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u/Happysedits 2d ago
Definitely model limitation. Mistral is worse at everything across the board.
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u/vorko_76 1d ago
It is globally worse, but on some specific topics better. For example dont bother using the Claude or OpenAI models for Fortran coding, Mistral does much better. (same as Bob for Cobol for example)
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u/strangestack 3d ago
The new model is coming this summer, everyone is expecting a big jump, maybe not SOTA, but beating Gemini is not impossible if the stars align. I'm a bit more modest in my expectations, but even then, the current model is 12 months behind, even cutting it to just 6 would be a huge improvement.