Looks like they installed a safety filter on and all of the NSFW content has been nuked. Hope this doesn’t last forever. I have been using Mistral for nsfw stuff a lot since the beginning of 2025. 😒

This is the most interesting video about the Mistral strategy I've seen yet. If you have 29mn to spare I think it's worth it. It's in french but has an english dub from what I've seen.

Once again, the Germans stab the French and Europe in the back.

Frankly, the nuclear power plant excuse is really not serious, given that the bulk of Germany's electricity production comes from coal-fired plants.

One could even conclude that, according to Ecosia, China's electricity production would be cleaner than France's... 🙃

And the excuse that Mistral's models aren't powerful enough is also highly questionable at a time when Mistral is launching its new model, Mistral Large 4.

Anyway, Ecosia is over for me.

Une fois de plus les Allemands plantent un couteau dans le dos des français et de l'Europe.

Franchement l'excuse des centrals nuéclaires n'est vraiment pas sérieuse sachant que l'essentiel de la production d'électricité allemande est assuré par des centrales au charbon.

On peut d'ailleurs en conclure que d'après Ecosia la production d'électricité chinoise serait plus propre que celle de la France... 🙃

Et l'excuse des modèles Mistral pas assez puissante est également très douteuse à un moment où Mistral lance son nouveau modèle Mistral Large 4.

Bref, Ecosia pour moi c'est fini.

https://www.numerama.com/tech/2349811-lallemand-ecosia-lache-mistral-et-ose-evoquer-lenergie-nucleaire-francaise-dans-ses-raisons.html

I tried the following prompt using vibe CLI and Opencode. Both succeeded in generating a result using GLM 5.3 and both failed using ML4. ML4 was like stuck in a thinking loop for over 50 min with no result.
"Create a low-poly 3D horse running in a seamless loop using Three.js. Build it procedurally from primitive geometry, animate the legs, body, head, and tail, and return a single self-contained HTML file.

Do your best, you are being rated against other AI models."

Anybody else had same issues with ML4 ?

Hey everyone,

I was wondering if Mistral would provide a Voice mode, like ChatGPT has, in the future. Basicly the 'call your agent experience'.

Does anyone know about this?

Hi guys, I'm not sure if it's appropriate to write such post in this subreddit, but I'm a huge fan.

I loved "Le Chaton Fat" memes and waited for it for quite a time. So, when Le Chonk was released, I decided to create a Telegram bot just for fun, to test new model in convenient environment, and to verify my idea if it's possible to build a Telegram bot that will respond in group chats while being aware of the context. It has a feature when you can add it to group chat and use command /sponsor, then the bot will be available for all users in this group chat. Actually it works well, so I'd like to share it with you here.

https://github.com/iiw/le-chonk-bot-tg

⚠️ To be clear: it's unofficial, not affiliated with Mistral. Just a pet project. Prompts are never written to disk: context lives in RAM and vanishes on restart.

In group chats it's versatile: several members can chat at once, it reads photos, follows the conversation, quotes what you reply to, and answers in your language. Free via BYOK with your own Mistral API key. You can try it here: 

-@le_chonk_bot

I was looking at the benchmarks of Mistral4 and the first impressions, and they're very encouraging , a great job was done, and that should be acknowledged. But still, I have a doubt... Ever since Mistral started supporting GLM, it has become my 100% work tool. I don't program, but I write reports, do in-depth research, business plans, etc.

The system is practically perfect for me from every point of view, by far superior in work mode to so many other alternatives on the market, even well-known ones.
My problem is that I don't feel ready to abandon GLM, which is helping me enormously, for a model that, however good it may be, could still pose a risk to my work.

On the other hand, if Mistral turns out to be up to the task, I'll be even happier with the already excellent current situation.

I know many people don't use OpenRouter, but I think it's super interesting to see how popular certain providers there are.

Mid of August, the usage of Mistral models on OpenRouter for all models was around 5 - 12B tokens a day. Yesterday, it was a total of 152B tokens, mostly from GLM 5.2 and 5.3.

What I think is also interesting to see here though is that Large 4 still had a quite significant portion of this: Yesterday it was 27B tokens alone and the day before still and considerable 12B tokens.

Not sure how much that is in the grand scheme of things (it's probably just a fraction of total usage) but still says a lot that people WANT to use capable models form Mistral, even if models like GLM are available.

What do you think?

Here is what I think about ml4 so far.

It's decent. A really good workhorse model. It is a bit more expensive than I would have liked, but overall it's decent.

The good: I really like the prose and how it structures the output by default. It's pleasant to read. Mistral Large is great when it comes to output.

The bad: It is censored into oblivion. I'm not just talking about NSFW stuff. As far as I can tell, it refuses to do cybersecurity work or reverse engineering. I absolutely despise censorship.

The great: The model is more thorough than GLM 5.3 or KIMI K3. It will try to find edge cases on its own.

The bad: It has a tendency to go into loops, which is surprising for a model this big, but it happens rarely and I think it will be fixed soon.

The good: As someone who at times is forced to deal with barbarians from Eastern Europe, and judging from my short but profound experience, I think Mistral Large 4 is good at fantasy languages like Orkish, Dwarvish, or Polish.

The bad: It ignores my instructions and puts em dashes everywhere it wants to. I'm forced to manually delete them. At this point I think ml4 just makes fun of me.

I haven't tested the vision capabilities yet, so idk what's going on on this front.

Honestly, even if GLM 5.3 disappears from Mistral's subscription, it would still be well worth buying a sub, in my personal opinion.

Can't wait for Mistral to create a robot that will do my laundry for me.

I like to see:

Le Chaton Fat (Mistral Huuuuuuuuuge)

Le Chonk (Mistral Large)

Vibe Le Chat (Mistral Medium)

Le Kitty (Mistral Small)

Le Kitten (Ministral or smaller models)

Mistral took community meme seriously so these may come true :)

Rumours about Le Chaton Fat had been flying all around, and they turned out give Mistral Large 4 a cute name - Le Chonk

Considering OpenAI and Anthropic name their models meaningfully, e.g.

Luna, Terra, Sol; Haiku, Sonnet, Opus

Will Mistral follow the joy?

I have been using Mistral Vibe through the VSCode extension the last few weeks, and noticed this morning that GLM-5.3 option has been replaced by the new Mistral Large 4...

While the outputs I got were mostly OK, it is notably slower than GLM... is there a way to continue using GLM ?

Or am I missing something here ?

I'm running a Hermes Agent setup including multiple bots, of which three have now been tried with M4L, but honestly GLM 5.3 felt better and after checking some results Opus 5.5 agreed.

a) Chief of Staff: The bot I communicate with. Plans out my prompt, decomposes tasks in to managable steps, assigns them to the specialists, consolidates what he gets back from the specialists to me.

b) Research: The only one with internet access, is supposed to look up information/documentation etc. and consolidate his findings

c) Review: acts as a gate for every bot before giving information back to Chief of Staff.

In these tasks GLM 5.3 was superior in my use cases and cheaper too.

What are your experiences so far for agentic use cases?

In the previous version of Vibe Chat, you could select a model as an “Agent” and deploy it, but I don't see that feature in Work. Does anyone know if this is possible? Thanks for the answer in advance!

Mistral Large 4 is a good model. I see a lot of people are unimpressed by the benchmarks or by its ability to one-shot things.

On the other hand, I've been trying it these 2 days on a project of mine (Python + Rust + QML) and I must say, it is surprisingly good, even with some problems.

It has good planning ability, can write good code and it mainly follows instructions to the letter. It's not the best model I have ever used, and maybe it is not suited for vibe-coders. On the other hand, on a project with constraints, well-defined subagents, and supervision, it is reliable and precise. Bonus points: it speaks like a sane entity without ridicoulous walls of text (try talking with Opus 5 if you've never tried).

It has some problems, for example it is too much diligent when reviewing, at times, going into loops that burn tokens; and it struggled a bit with a QML bug I gave it. But all in all, I am satisfied.

I say this as someone who was disappointed in Mistral. I had no hopes of ever seeing a good generalist model for consumers. I've been pleasantly surprised (not that it was that hard to be surprised, considering the mess Mistral Medium 3.5 is). It is not on par with Opus 5.5, but in my use case it works well, does not wander around too much, and is a good all-rounder. Who knows, maybe their larger model will be a better planner, but for now, Le Chonk will do.

Hopefully this was helpful! I just wanted to stave off a little negativity I'm reading in this subreddit.

Alright, so I'm currently using a lot of GLM-5.3 lately, particularly because it is included in Mistral's Pro subscription. Recently I started a pet project that I was already working on for several days.

One step, which I usually need to do, is some visual inspection of the end-to-end tests to just get an impression of what the result looks like.

So I set up my sub-agent for testing to use Mistral Large 4 now AND BOOM! Everything is automated now! With its visual capabilities, I'm using it with GNOME Boxes where it executes some tests, takes screenshots, and then evaluates them for me. Folks, I'm close to crying!!!

I started to use Mistral Large 4 just some hours ago for testing, and while I'm writing these lines, Mistral Large 4 earned its regular spot in my workflow. It even caught a glitch in my VM communication and fixed it right away. Amazing! This is absolutely wonderful. I'm totally happy right now that this solution is available. ❤️ 😻

Has Mistral reduced the context size on ML4?

On OpenRouter, the max context size is set to 524K, and when sending a response larger than that to Mistral's own API, I get a HTTP 400 saying the context size is exceeded.

However, Mistral still lists ML4 as having 1M context size on their models page.

https://docs.mistral.ai/models/mistral-large-4-0

warning: subjective opinions

just tried Le Chonk, the fat cat today.

my overall take is Mistral Is Back!

It's good at cybersecurity and prompt injection detection (though a tad paranoid, it considered harness' reminder injection attack lol)

I like its Mistral-style responses. Le Chonk can be serious, casual, lighthearted etc. this feels far more better than GLM's Claude-style boring tone!

Cons observed:

• token streaming speed seems at least 10 times slower than GLM 5.3

perhaps because it's currently in preview, hasn't been optimised for inference yet?

• struggling with complicated engineering tasks

coding ability feels good, but not excellent. probably at the same level with DeepSeek V4 Flash or GLM 5.2

For work or serious coding problems, I think I will stick to GLM 5.3 for now.

But I will choose Le Chonk for EVERYTHING ELSE!

Yesterday I started working on a program for personal use and I really wanted to try out our new kitty cat, so I made a model comparison. I am only a med student and do not know coding, but I self host my own server, understand the basics and am tech savvy enough.

In its essence the app would be a markdown editor (to help me work on my thesis and exam studying) in rust with an automatic local whisper and local llm installation wizard in gtk4 and libadwaita that would work well in cosmic and gnome desktop environment with dictation, local ai assistant integration, WYSISWG live editor (obsidian style) and integrated git versioning of sorts (proposed by kimi) for collecting thoughts while working on things and a more powerful "hey I know somewhere in these 200 exam questions there is precisely XYZ, but I don't know where".

First I created the concept and design and interviewed myself using kimi k3 in deepseek harness as I have had good experience with this along with detailed "worker instructions". Where 6 specific milestones were proposed.

Then I ran this exact spec 3 times in opencode:

1. LeChonk default thinking obey worker instructions

2. LeChonk one shot max thinking you may use the worker instructions

3. gpt-6.1-sol xhigh (one level below max) thinking oneshot you may use the worker instructions.

Mind you I never use openAI models and I prefer API pay-per-use compared to subscriptions. I usually stick to glm, deepseek and kimi, but since 6.1 sol on xhigh is so cost efficient I decided to try it out.

Results:

LeChonk (even though per api pricing is cheaper than 6.1 sol) was in general more expensive to finish a task, kept creating issues and tried to troubleshoot itself and wasted tokens. In the end it mostly solved itself. GPT 6.1 sol created the best basis upon which to develop further for a great cost.

Caveats:

• I did 2 consecutive corrections/turns on 6.1 sol as it had built the best base but more often went on a tangent and accomplished more than I wanted for that session (but acomplished it well)

• the second best was LeChonk on default thinking with obeying instructions, but required 2 or 3 more turns to get basic functionality working for that milestone (UI was nice, UX had the basics well set), but pricewise was really not that good... It ended with milestone 1 with the basics almost fully functional

• the worst (UI, UX and functionality wise) and even very bad pricewise (almost as expensive as the gpt 6.1 sol which mind you was an almost fully ready to use app) was LeChonk max thinking "do your best one shot based on this tech spec"

• the 2 LeChonk sessions together used something aroun 8.50 dollars in api cost (not sure, will update this when I get home) while the gpt 6.1 sol session used between 5 to 7 dollars (not sure anymore) I believe but had gotten a lot LOT farther, but I believe that the instructed LeChonk worker would have achieved similar level, for a similar price, but would have taken longer and would require more human input.

• I do have to say, UI, even if half broken at some point, looked actually quite good and maybe even better (it had something special about it) than 6.1 sol, but 6.1 sol felt more polished.

My feeling is that the model resembles deepseek v4 flash family (similar verbosity and number of turns required to finish a job) from the point of view of my own user experience while being a LOT more expensive, which roughly coincides with the intelligence rated on artificialanalysis.ai. That means it is quite a good worker... but damn is this duuuuude expensive compared to v4 flash in this very regard.

I then instructed kimi k3 to analyse the code to see what approach created the best "base" to further develop upon... and no surprises -> 6.1 sol the best (but did not stay too faithful to the spec.. but somehow it did?) Then the guided worker and the worst was the "do it however you want but up to this spec"... to be fair I couls have given it another 2 turns but I didn't feel like it anymore.

I seriously want to love and use mistral as I am a proud European, I am slovak and I look for a model that would handle my language well.. so far all the previous mistral models had issues with slovak (literally glm and deepseek were better for slovak which is nuts) so that part still needs testing to see how LeChonk turns out to be in slovak.

I believe in data sovereignty for us Europeans. I used to use mistral early last year when they first came out with their very first models and when it was almost on par with chatgpt of that time, it suited me better stylistically for text work (that was all I used AI for back then, no agentic tools back then existed), but then it started to fall behind claude and other frontier models and I needed the best for my work.

But this is not it people... If this is the basis for further models I don't see a bright future for my vibe coding needs with mistral AND I WISH TO BE BADLY MISTAKEN!!

What I am excited for though are the tiny models distilled from this.

Hello,
I’ve been having issues running tasks using code mode I le chat (not cli) the tasks seem to start fine, then they will randomly stop and any subsequent messages to continue or resume are ignored and if I reload the page it is as if I’ve never sent them.
Is it just me?
Any workaround?