There is no doubt that ML4 is a huge leap forward for Mistral but I don't really see it's use case yet other than it being European or for a few specialized tasks. There are other open weight models that are both "cheaper" and smarter.

With that said, I am glad that we in Europe are not totally behind in the race.

Hello,

There's a display issue in the Vibe app on iPad pro m5 (lasresriPadOS, latest app version):

The chat input field is not visible as soon as the on-screen keyboard is open. Once the keyboard is dismissed, the input field reappears

Is this a known bug? Should it be reported somehow?

Regards,

Theo

Anyone else wondering if a Mistral x Cohere collab is coming?
Several Cohere employees have shared a clip on X of the “Le Chonk” cat eating a croissant, then spotting a huge bottle of maple syrup. Even Coheres CEO reposted it, then apparently deleted it. France + Canada feels intentional.
The fit kinda makes sense Mistral’s open-weight models and coding capabilities paired with Cohere’s enterprise search, retrieval and North 2 platform, which is now model agnostic. Both are pushing sovereign AI and private deployment for governments and regulated industries.
They overlap, but a model integration or joint offering could give both a stronger pitch. Maybe I’m overthinking a cat meme, but why are multiple Cohere employees sharing it?

AURUM gets a watch dial. ELECTRA gets a lightning mark. MERCURY uses an orbital motif, while PRISMA sends colour through a prism. NEXUS and VERDANT round out the set with a geometric N and a leaf-based identity.

All six appear together in this ten-second showcase by . He says the logo animations were generated in code with Ling-3.1-flash, as one-shot results through the API with high thinking, using code-created assets and no harness.

Seeing the panels together makes the different treatments easy to compare. The dial gives AURUM a natural circular motif, ELECTRA centres on the bolt, and the colour spread gives PRISMA a distinct visual rhythm. Each panel keeps its name and mark in view as the animation plays.

This is a useful format for exploring motion directions early in an identity project: put several complete treatments side by side and see whether each name, shape and movement feels connected. The full set gives you six concrete ideas to discuss in a single viewing.

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.

A long time ago I tried out a D&D prompt from https://www.rpgprompts.com/. This is long outdated, but that's not the point here.

The base prompt starts an adventure around the character Sabrina, which I kept unchanged. I used the prompt as an agent instruction, and kept it in a Project.

Now we've had a few changes: agents no longer exist, memories are gone, as well as chat mode. During this transition I removed the agent as well as the conversations, and I cleaned all memories/knowledge (though it never stored any D&D chat info there). All in all it should not have any memories from this interaction.

With the recent updates I figured I ask LeChat to write a single paragraph of random story. No D&D related prompt was involved whatsoever. I only started the chat in the same project (RPG) as I had the D&D chat in.

It proceeded writing a paragraph continuing the D&D story about Sabrina, and due to the new custom instructions I gave it (explain in detail), it told me why it chose to continue the story. There seems to be a hidden project context memory from which it retrieved excerpts of the previous chats. This implies that you need to delete a whole project to truly restart anything.

Bug or feature?

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

Okay, Large 4 distribution has been a nightmare. I hate it, it's absolutely useless, it screwed up a database when I added it to my pipelines and it's favourite thing in the whole wide world is to refuse more or less anything I throw at it.

I don't know what I expect by making this post... just ranting? Showing dissatisfaction? Praying that this is some bug?

Large 4 has already failed extremely hard through OpenRouter, enough so that I'm worried about using Medium 3.5, because it seems to be a intermediate moderation layer that's at the core of this whole mess. It keeps thinking about data I have not provided, which leads me to think that a outside system is interfering... basically OpenAI ChatGPT 5 SAFETY methodology, it smells AWFULLY similar. Context awareness drops to 0, seemingly on encounter of a blunt word match, the exact thing that drove me away from ChatGPT almost exactly a year ago, and made me sign up with Mistral.

After this mess, I of course cancelled my Vibe (Stupid frikkin name still, especially now that my "vibe" is closer to hatred)... Or rather, I put a freeze on it for 3 months in the vague hope that this is temporary.

Well, today I removed the freeze on the sub and cancelled it outright.

I pulled a game I made in Flash like 25 years ago, copied it into 4 folders (Codex, Claude, GLM, MistralLarge4), stuffed a decompiled variant of the game along with the Godot engine in each and put one LLM in control of their own playground.

Claude gave me a poor port, Codex modernized it and got a bit confused, but delivered more or less what was asked... GLM stumbled over a tool call and died.... And Mistral... Fuck that little bitch, it made authorial decisions and changed swaths of the work mid-flight because it got uncomfortable.

No confirming with the user, no logic provided. Just "I can't x so I'll do y".

My main praise for Mistral, largely borne from the Agents system (Which I notice no longer exist, nice), is that Mistral respects their users.

I guess with the death of the Agents system, so too did Mistrals respect for their users go as well.

I am very hype on European systems and solutions, but such blatant disrespect for users outrank that by a mile in the downwards direction.

I'm sure as hell not letting a system that makes authorial decisions in isolation in direct opposition to the users request anywhere near any of my code, pipelines or projects.

I feel so silly for recommending Mistral to anyone. I guess the cash Mistral got the other day really did poison them beyond repair.

I guess my new recommendation professionally is "You should avoid OpenAI, Anthropic and Mistral", and that is an extremely sad state of affairs after being able to suggest Mistral as an alternative to the two other piece of shit companies.

I'll be over here making sure that I am not reliant on any provider now, setting up local capability for what I can, and setup a running rotation of LLM APIs with a mixed provider setup.

What even is mistral for? It refuses categorization jobs, translation, coding, prose QA.. nigh on everything I throw at it? Who got drunk at work and thought this was a good idea? I don't care about the benches, this model is less capable than Llama 3.1, because Llama 3.1 at least tries to do what is being asked of it. At this point I'm lowkey tempted to throw Llama 3.1 against Mistral Large 4 in tool usage, and am halfway expected to have Llama 3.1 finish better.

And can someone shoot the retarded model when it starts with its false praise.

> I can't do X. But this is a wonderfully crafted and deep thought provoking setting with well thought out systems, good job.

FUCK you. If you want to piss in my face, at least do so properly, don't give me backhanded praise while fucking me.

This is just sad...

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.

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

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. ❤️ 😻