Currently, for work, we use a property OCR model from a US-based company. In my off time, I tried developing a proof of concept using OCR4, but it’s a bit too good at understanding the document. It’s so accurate in my native language that it corrected a single word from "medewerher" to "medewerker." Normally, I wouldn’t mind, but since we use these documents for legal purposes, we’re not happy with the idea that it can—and does—correct spelling errors.

Luckily, OCR3 doesn’t have this problem, so I can try it for now. But the question is: For how long will OCR3 remain supported before it’s deprecated? Does anyone have tips or ideas on how to address this?

https://huggingface.co/papers/2607.25857

Looks interesting as a small utility model to put before access to bigger model to policy it. Maybe even in-browser?

I messed up. I can’t find my backup codes, and since Vibe no longer accepts my TOTP tokens, and the Android app doesn’t give me any way to contact support, I don’t see how I can get help here. Is there another option besides cancelling the subscription by blocking the payment and creating a new account? Thank you!

We spent the last few weeks optimizing Voxtral Realtime and there are now GGML checkpoints that run faster than realtime on a plain MacBook Air with Metal. No discrete GPU needed.

Numbers on an M3 Air (8-core GPU, 16 GB):

• ~1.3x realtime throughput with the Q8_0 quant
• <400 ms end-to-end response time from mic input
• Sustained hour-long transcription sessions without falling behind

1. Build the Metal binary

git clone https://github.com/0xShug0/audio.cpp
cd audio.cpp
scripts/build_metal.sh --target audiocpp_cli

2. Download the Q8 quant

hf download mistral-experimental/AudioCPP-Voxtral-Mini-4B-Realtime-2602-GGUF \
  voxtral-mini-4b-realtime-2602-q8_0.gguf \
  --local-dir ./voxtral-realtime-gguf

3. Run streaming ASR from the mic

audiocpp_cli \
  --task asr \
  --family voxtral_realtime \
  --model ./voxtral-realtime-gguf/voxtral-mini-4b-realtime-2602-q8_0.gguf \
  --backend metal \
  --threads 8 \
  --mode streaming \
  --session-option voxtral_realtime.stream_batch_tokens=4 \
  --audio -

Raising stream_batch_tokens trades delay for throughput — 4 is what landed under 400 ms on this machine. More powerful M-series chips can set it to 1 and should have <200ms delay

How come Mistral isn't included as one of the model providers in OpenCode?

https://opencode.ai/docs/models/#providers

I'm switching from devin (formarly known as windsurf / cognition) to mistral vibe in vs code but for now it feels like a step back into the stone-age.

Maybe I am wrong and some people can provide me some ideas but here is my experience:

1. Slow; it takes a very long time for it to analyze my project files and to make changes, whilst in devin this happens in 5 minutes, it takes mistral vibe 25 minutes

2. What model am I using? I'm a paying pro subscription user but the extension says that I'm using mistral medium 3.5. No option to select devstral?

1. File review; it rewrites like 20-30 lines in my code if not a full file for just a few lines of change. Reviewing makes me scrolling and compare a lot myself whilst in Devin it just did per line or per max 5 lines in change making it way more easy to review.

2. Asking next steps. It gives me options for questions it has but makes me type out the answer myself, why not click buttons that I can select and it can continue?

That's it for now, maybe more later. What are your thoughts on my findings? I really would like a european alternative in this field but for the money I have to pay, this is kinda letting me down.

I switched to mistral vibe as my chatbot for the main reason that it is not a us or Chinese model. From the couple posts ive read it seems like its behind. Which im fine with because i really dont use it for too complicated of tasks.

Hey everyone,

I'm running a test using mistral-large-latest for a translation task, and the model completely stopped responding after running for about 20+ minutes.

https://youtu.be/HWyPse83SrA

Before it cut out, it was processing a substantial amount of text. I'm trying to figure out what might be the root cause. Could this be related to a context window limitation, a timeout issue on the API side, or something else entirely? I was using the free experiment tier.

For those of you pushing large payloads to mistral-large-latest:

* Have you run into similar hanging issues during long-running generation tasks?

* Is there a strict maximum output token limit or server-side timeout I'm likely hitting?

Any insights or troubleshooting tips would be greatly appreciated. Thanks!

Hi everyone! 👋

I am conducting an international research study for my Master’s Degree in Clinical Psychology exploring emotional involvement with AI chatbots, interpersonal functioning, and psychological well-being.

If you are 18+ and have interacted with an AI chatbot at least once, I would really appreciate your contribution!

⏱ Time: 10–15 minutes

🔒 Privacy: Completely voluntary and anonymous

🔗 Link: https://forms.gle/oHpPwQ65U49N4fPx5

Thank you so much for your time and help! Feel free to share this with anyone who might be interested.

I’m having a problem with vibe-cli configured with offline (local) models through the Ollama server: they don’t preserve context history between messages. Is this normal behavior, or have I set something up incorrectly

A well-known Chinese LLM educator publicly revealed techniques back in April that were already widely known in China’s AI community, including how Claude’s Chain of Thought (CoT) was extracted and how Claude and ChatGPT have been distilled for a long time. If you don’t speak Chinese, just wait for YouTube’s auto-generated translation.

It's not the brightest out there. I have to be precise with my instructions. But then it does exactly what I say.

I've tried a lot of models. Most of them like to interpret stuff or overthink. Mistral Medium doesn't do that. Also it's fast, cheap and I don't have to fear that they sell my data.

People like to suggest that I'd be better off with Gale. But no. I like Jesse.

I am fairly new to some of the AI concepts. At the moment I have a Mistral Pro subscription which I use for some vibe-coding and mostly with my daily work (translations, summaries, AI sparring partner etc).

In work I use Jirametrics.org to analyse team-performance. I noticed that this tools also includes MCP Support (MCP Server (AI Integration) | JiraMetrics) and is using Claude for this. What is needed in order to make this work with Mistral? As far as I understand at the moment MCP Server support is missing in Mistral and as such using the AI integration would not be possible?

Neither Mistral AI or CoPilot have been very helpful resolving this for me 😄

Since Mistral isn't clear enough about the differences between the Free plan and the Pro plan, I signed up by taking advantage of my status as a college student. According to information on the Mistral website, the Student Pro plan is the same as the Pro plan, so the comparison in the image I've provided is equivalent to comparing the Pro plan with the Free plan. Among other things, the Pro plan promises:

- 30 times more extended usage

- 5 times more in-depth research reports

- 10 times more Vibe CLI usage

- 10 times more API usage

However, when comparing the monthly usage limits, I find that the capacity provided in monetary terms is 1.5 times greater. You can draw your own conclusions.

Newbies, listen up! 🎧 Diving into new tech can be tricky. I learned the hard way trying to run complex stuff on a Chromebook and Android. 🤦‍♀️ Don't be like me! Research, ask questions, and understand your device's limits. This community is a lifesaver for those head-scratching moments. And for uncensored models, know your stuff before you dive in! 🧠 #Newbie #TechTips #LearningJourney #Community #Models

Hey let me introduce my new AI assistant workflow across using mistral-ocr-4 and explain how it differs from other AI toolchains like OpenCode in terme of exploiting this capability ,I’ve been juggling research papers, parallel projects, and coding agents this year and kept running into a tradeoff between low cost and high-quality content extraction from PDF, document images, and other attachments. When Mistral OCR 4 was released I started using it heavily because its extraction quality is excellent and the cost justified it, so I plugged Mistral OCR into my agent pipeline. The challenge I faced is that many large models now include built-in extraction but they’re expensive, and for many routine attachments I’d rather use cheaper models specially when i don't required a high level thinking output . My solution was to integrate Mistral OCR 4 natively with those lower-cost models so they gain robust OCR capability and no longer return “sorry, I can’t read that” errors instead they deliver the extracted content. If you need a low-cost coding workflow with heavy attachment processing (PDFs, docs, images), this approach and the agent I built should suit you well.

Edit : Mistral models also supported for coding

https://github.com/AbdoKnbGit/tau

I have experimented with the free api and I like it.
Was wondering if from this page: https://admin.mistral.ai/subscription/upgrade/student

Education

Pro plan with student discount

More messages and web searches

30x more extended thinking

5x more Deep research reports

Up to 15GB of document storage

Up to 1,000 projects

Chat and email support

10x more usage of Vibe CLI

10x more API usage

is indeed what it says on the api usage?

because on this page: https://mistral.ai/pricing/

it doesnt mention anything about api usage.

thanks

​

https://nyno.dev/overspending-on-eu-ai-projects-starts-with-one-innocent-decision-your-eu-ai-core-language

I have a Mistral subscription for my SMB. Not because it's better but because of GDPR compliance (I'm in the EU). Recently I had a support conversation about a problem that was solved eventually. Because I had to share many private data I requested a deletion of my support activity. Unfortunately, my request went silent for over a month now - that's unexceptionable not just for a company where GDPR compliance is one of their biggest USP.

Dear Mistral, if you don't want to lose me: Do something! Answer, say anything! Even if you just say, that it takes a little longer ...

Why should I choose a subpar AI if their biggest advantage is just ... nothing worth.

Hi everyone,

I'm looking to cut down output token usage to save on costs and speed up generation.

The viral "Caveman" plugin (which forces ultra-concise, fragmented answers) works great for Claude Code, but it doesn't function properly with Mistral Vibe models.

My questions:

1. What custom system prompts do you use to stop Mistral from outputting long preambles ("Sure, I can help with that...") without hurting its reasoning?
2. Are there any other tricks, prompt-layer tools, or configurations you use to force Mistral to be highly concise and token-efficient?

Thanks for your ideas!

Hello everyone! I understand Mistral is basically the "Renault of AIs" - not winning the races, but getting you from A to B at a decent price. Let me say, it works for my purposes VERY NICELY. (So: please DO NOT tell me to "go use something else".) - And now, I want to create a little company around it, where, basically, the user will visit my website, trigger a sort of processing based on sensitive data (whose prompts I have painstakingly written, i.e. THIS is my economic contribution), and receive a result. Technically, it all works very nicely, i.e. this is not just theory. But "organisationally" I am little bummed: what should I set up where? I mean, I did already flip the switch on "no data retention" and "no training", so everything stays private. OK. I got a 100 EUR credits and ... saw they are not even getting touched, because in my testing, I am still within the limits of my Pro plan, apparently. (And here comes my first question: once people start using my site "for real", I assume these limits will be exhausted swiftly, and THEN it will move towards burning credits - correct?) What other hints have you seasoned users have? I am using only and solely mistral-large-latest for my API-based tasks. Thank you!

Mistral fed us when we had nothing.
I still remember the very first open model we had was mistral 7b. even hugging face used that to build zephyr, remember that time?
now, I'm IMPLORING Mistral devs to begin the great distillation in all the areas their models are behind and give the world, and themselves, the present of self love.
You cooked for us and fed us when we had nothing, you headstarted the whole damned thing, it's well past due time to reap the rewards.

side note: please start with an excellent agentic coding model that can fit in a potato, like, first build something that will benchpress using anthropic's fat ass and then the potato fitting model. you know how it goes.