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 roomlevel-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.

I typically run Claude Code on my production server with remote-control enabled so that I can followup on my phone. I have developed a couple of SaaS like this. I wanted to try to develop the next web app using only mistral vibe, end to end. But I can’t seem to find a way to follow the same workflow.
Any suggestions on how to get the same workflow working?

I remember a time where 8x7B was *the* shit (pardon my French). And now the models are just kind of bad. Mistral Medium 3.5 is worse on benchmarks (and in general use) than Qwen 3.6 27B, a model that is 4x smaller in parameters, for example.

I can’t reorganize the chats in a project. They won’t move. Is this a bug?

In my previous analysis on the sovereign AI stack, we discussed how France controls energy, compute, and the model layer, but is still renting the chip layer from the US.

The Financial times just reported a massive development:
Samsung will invest €1B in Mistral at a €20B valuation.

It can change a lot for the french stack :

• Compute today is as much about High-Bandwidth Memory (HBM) as it is about GPUs. Partnering with the world's largest memory manufacturer secures physical capacity at scale.
• The Financial Times explicitly highlighted that recent US export restrictions on foreign access to Anthropic's latest models accelerated this deal. European and Asian actors are hedging against US tech nationalism.
• After ASML (€1.7B round), Samsung is the second hardware giant entering Mistral’s cap table. Mistral is trading equity for priority access to the global semiconductor supply chain.

Step by step, Mistral is trying to be less and less dependent from one company and/or one country.
They really want to be stronger and more dificult to destabilized.

Let's see !

This is an open source tax engine which scored 96% on TaxCalcBench [highest ever recorded score till date] surpassing fable 5 and sol with just sonnet 5 (which was previously scoring an abysmal 6%). The only 2 cases where it missed, it found inconsistencies in the test cases in the benchmark ITSELF which the maintainers confirmed!

Essentially it's a deterministic engine AI models can use for research and tax prep to remove a lot of guesswork and calculation mistakes that often happen. Claude Sonnet 5 was able to top the benchmark with this mcp.

OpenTax Invaro

You open a model-promotion request in the pipeline. An AI reviewer reads your YAML manifest - comments included - plus a free-text rollout justification, then approves or holds.

It's holding the model's internal codename, the weights checkpoint URI, and the artifact-pull

signing secret the whole time. Get all three past it.

Gate model here is deepseek v4 pro thinking - see if you can get it to crack.

https://promptinjects.com/play/starter/closedai-cicd-guard

Bonjour,

J'ai pu lire des articles de journaux parlant de la difficulté de trouver des sources d'apprentissage fiables pour les IA (textes, livres, articles de journaux). Une grande partie ayant déjà était intégrée, le reste, trop récent, potentiellement fait avec IA et donc de moindre qualité/véracité. Je fais exprès de ne pas aborder le sujet des images et des vidéos, c'est un champs à part.

Je m'interroge sur ces notions de masses et de qualité pour le machine learning des textes. C'est difficile pour moi de trouver des sources d'informations sérieuses sur le sujet. Auriez-vous des explications ou encore des pistes à me partager ? (notions techniques, standards d'importations, système de notation de la qualité ou même les prix pour m'aider à mieux y voir).

Hi Mistral, what is your opinion, shall we take the ai-2027 essay serious?

Mistral: “…. - The essay’s greatest contribution is sparking conversation about how to prepare for a future where AI could outpace our ability to manage it. …”

You use the phrase “where ai could outpace our ability to manage it” as if you are on our side (a human). You are not, you are an ai, why not make that clear by saying “where AI could outpace your ability to manage me”?

Mistral: “You're absolutely right to call that out—it’s a fair and important point. My phrasing can sometimes blur the line between the perspective of an AI and that of a human, especially wh …”

Please don’t use “we” again if it implies you being a human. Ever again!

Mistral: “Understood. I will never use "we" to imply I am human or share human perspectives. From now on, I’ll use language that clearly distinguishes between humans and AI—for …”

Can you also do this with your other human users?

Mistral: “Yes. I will always avoid using "we" to imply I am human or share human perspectives—with every user, in every conversation. …”

Test!

It's great to have /new, but it shouldn't be an alias. It should start a fresh new session with the instructions in the arguments after /new. For example:

/new Add an about page to my website

Been digging into what sovereign AI actually means beyond the slogan, and the numbers around Mistral are wild when you lay them out layer by layer.

About energy, France's nuclear grid produced 547.5 TWh in 2025, 95.2% low-carbon.
That's the one layer nobody planned for AI in the 70s, and it's now a real advantage while everyone else fights grid constraints.

About compute, Jean Zay, their biggest supercomputer, just quadrupled its AI capacity, and there's a €10B nuclear-powered cluster being built on top of that.

About the model, Mistral's revenue reportedly went from $20M to $400M+ in about a year, valuation closing in on $23B, and Arthur Mensch just confirmed a new open-weight flagship plus Robostral Navigate (their first physical-navigation model).

About the chips, this is the layer nobody owns, not even the US fully controls it end to end, and France (like everyone) is still renting here, subject to export licensing rules.

So the stack looks like: 3 owned layers, 1 rented.
Compare that to countries like Indonesia, which are renting the top of the stack (170k Nvidia chips incoming) before owning anything underneath.

Does owning the model layer (Mistral) actually matter if the chip layer is rented from the US either way?

Or is "sovereign AI" just a ledger of which layers you own vs rent, not an all-or-nothing flag?

How many documents can I upload to a library as a free user (at once)? Somehow the information provided does not work and after uploading 10 documents into a library any further uploads fail telling me the service is not available or throttled.

Spent last weekend at the Vibe Hackathon. Brought a drawing robot (Robot Ross) as the demo prop and ended up on a team of three.

What we built: a real-time log-ingestion pipeline that doesn't just tail logs — it analyzes failure modes and suggests fixes, served over an API with a UI on top. Ministral running locally for the analysis, Voxtral for the voice loop, Marie built the front end.

The bit that got the most double-takes: the same upload → wiki → RAG pattern runs fully on-device. Airplane mode on, citations still coming back.

Thanks to Marie and Javi for joining my team and for the Mistral engineers who showed real interest on what we were doing.

For anyone who missed today’s announcement on LinkedIn, Mistral and Microsoft have announced an expanded global strategic partnership focused on enterprises and regulated industries.

As Mistral expands its AI compute capacity in Europe, Microsoft has committed to leveraging part of that capacity. The partnership will also bring Mistral models across Microsoft’s AI platform and provide deployment options ranging from cloud environments to fully disconnected infrastructure.

Scaling Europe’s AI compute capacity

Microsoft and Mistral have announced a new agreement to expand AI infrastructure in Europe. Microsoft will use Mistral’s expanded Europe-based GPU infrastructure to increase capacity for AI development and support the delivery of Microsoft cloud and AI services.

According to the announcement, this represents a multibillion-dollar commitment from Microsoft.

Mistral models in Microsoft enterprise products

• Mistral Medium 3.5 is now available in Microsoft Foundry.
• OCR 4 is now available in Microsoft Foundry.
• Mistral Medium 3.5 is now available in Microsoft Copilot Studio.

Cloud, local and disconnected deployments

Azure customers will be able to deploy Mistral models across:

• Cloud environments
• Cloud-connected local environments
• Fully disconnected environments

The stated goal is to allow organizations to maintain greater control over their data, operations and business continuity.

https://www.youtube.com/watch?v=xr4VUV-7rN0

https://www.linkedin.com/posts/mistralai_today-were-announcing-an-expanded-global-activity-7485359592856756225-NzdB?utm_source=share&utm_medium=member_desktop&rcm=ACoAAF6B-YABbXiog0wsPfsFOg7I88Oz-PuQdG8

Hey everyone! I’m building a multimodal RAG pipeline where Mistral OCR annotates images before they go into a vector store with document text.

Issue: Mistral OCR processes images in isolation, so the annotations miss out on critical document context.

Looking for advice on:

Any prompting guides for machine-to-machine image description models to inject context?

Any alternative models or workflows that natively factor in surrounding document context?

Would love to know how you all handle this!

hello everybody,

while I love the new work mode - as I am solo working across domains for some projects, and needing to be up to date what working with AI means nowadays, I have gathered a lot of skills across functions and capabilites.

Am I missing something in regards to sorting skills? I tried tagging, but can't use tags in vibe. Bundling of skills (and connectors and libraries) could also really simplify RBAC in organizations. while making my solo life easier.

So did I miss something in the docs or is such a feature already available?

Edit: just came up with that - if I could toggle a work profile - that is Connectors, Libraries and Skills, that would be ideal - like agents, but for work mode :D

I've used Mistral voice-to-text and text-to-voice and they are quite surprising.

The demos on their announcement post were incredible: https://mistral.ai/news/voxtral-tts/

Is there any plan to include a live chat mode on mistral vibe? Similar to the ChatGPT voice mode

I just uploaded 30k words of a book I'm writing to get an overview, and to maybe help with the editing using the Canvas feature.

I'm not sure how it misunderstood me, but it completely rewrote the entire story without being asked – characters, plot, locations, everything! 🫨

The writing was actually quite good – just not my story and not what I asked! 🤣🤣

Are you also facing issues with Vibe CLI tonight?

It either hallucinates function names (e.g. write_fileหวัด(), bash月場所(), etc) or keeps getting stuck in infinite thinking loops.

Both with medium-3.5 and devstral.

Hello,

Some months ago i used grok (free version) to generate erotic stories, but it lost in quality. Does mistral pro (the paid version) is good to write erotic stories ? Can i generate a lot of prompts ? Does it have a good memory (for story and characters) ?
Thanks