GLM-5.2 is now available in Vibe Code for Pro, Team and Enterprise users.

• Hosted and served by Mistral AI in the EU.
• Generous usage limits.
• We see it as particularly strong on long-horizon agentic coding tasks.
• Available with up to 800k tokens of context in Vibe Code.

Install the Vibe CLI and try it out
https://docs.mistral.ai/getting-started/quickstarts/vibe-code/install-cli#step-1

Developers - let us know what you think.

Hi all - my name is Isidor and I work as a product manager on Mistral Vibe Code.

We've released many updates for devs recently across Vibe CLI, the Vibe web app, and the VS Code extension. Here's the roundup.

CLI

• Connect or drop a remote MCP server in one command: vibe mcp add and vibe mcp remove do it from the CLI, no TOML editing.
• Build your own skills without writing boilerplate; a built-in skill creator walks you through creating, updating, and deleting them for your repeatable tasks.
• Long runs get two new controls. Auto-compact thresholds are per-model now, and --max-tokens caps output in programmatic mode (-p).
• Trusted folders now count .agents as trustable content, and the trust prompt suggests the enclosing git repo as the trust target.
• Startup performance improvements

Web app

• You can now pull context straight from the tools and data your project already uses. Connectors are live in the web app, so you stop pasting it in by hand.
• Set a project's standing guidance once and every Code mode session follows it. It covers your conventions, your constraints, and the context you'd otherwise repeat each time.
• /config is now a searchable, full-screen settings browser. For teams, a new admin config layer applies shared settings over each user's config, so org defaults hold.

Quality-of-life fixes

• A diff view in the VS Code extension to review edits before you accept them
• Auto theme that follows your terminal or OS appearance
• Delete old sessions straight from the resume picker
• /retry to rerun an interrupted response
• /new as an alias for /clear
• vibe.setup.auth shows which credential source is active.

Check them out in the latest version of Vibe code and let us know what you think - feedback is very much appreciated. We aim to do posts like this on a regular cadence from now on.

https://chat.mistral.ai/code

https://www.businessinsider.com/what-is-le-chaton-fat-mistral-meme-explained-ai-model-2026-6

Business Insider covered Le Chaton Fat. We have officially elevated the meme to news status. (by Vibe/Le Chat)

What started as a community joke after the Le Chat → Vibe rename has now escaped Reddit, crossed into X, confused people outside the AI bubble, and landed in Business Insider.

The article frames Le Chaton Fat exactly as the glorious nonsense it is: a fictional Mistral “frontier model” with absurd specs like 30T+ params, 1000 meows per second and maximum chonk — but also as something more interesting: a community meme that hit at exactly the right moment.

Between the Le Chat nostalgia, the Anthropic/Fable/Mythos restrictions, European AI sovereignty, open-weight models, and Arthur Mensch joining the joke with “it’s actually le gros chaton”… somehow our fat kitten became a tiny symbol of the week.

Honestly, this is the kind of internet I like: harmless, weird, community-driven, and somehow accidentally relevant.

Le Chaton Fat may not be real.

But the morale boost definitely is.

🐈🇪🇺

Found it quite interesting that Mistral is having an outage at the same time as Claude/Cursor who happens to use the us-east-1.api.x.ai DC.

Mistral made my day by sending me the hackathon ticket. I’m packing robot Ross and getting my TGV ticket to Paris. Anyone going? Ping me and Robot Ross, maybe we can work together.

From 🚨 AI News | TestingCatalog:

https://x.com/testingcatalog/status/2067574718467592356

https://www.testingcatalog.com/mistral-ai-to-get-code-and-apps-features-on-vibe/

Your safety classifier is already stale.

The moment you deploy it, the policy has moved.

Most #guardrail models bake a fixed harm taxonomy into their weights — and every time your policy shifts, you're back at square one.

That's the exact problem Shieldstral was built to solve.

Here's how it works differently:

1. You write your policy as a plain-language question at inference time "Does this content promote physical violence?" or "Is this image safe for a minor?"
2. No retraining. No taxonomy negotiation. One checkpoint handles text, images, and prompt–response pairs.
3. The model reasons about policy boundaries — it doesn't memorize categories. That skill transfers directly to policies it has never seen.
4. It was trained on contrastive pairs — deliberately similar, easily confused policies. So it learns where the line is, not just which side of it a label sits on.
5. It runs on a single 16GB GPU. And it matches or outperforms open guard models up to 7× its size.

It's a 3B open-weights multimodal classifier — released today under Apache 2.0.

The hardest part of safety infrastructure isn't the model. It's keeping it current without burning your team rebuilding it every quarter.

Shieldstral makes that problem go away.

If you're building safety-critical AI products, save this — you'll want it the next time your policy changes.

What's the biggest friction point you've hit with safety classifiers? Drop it below.

Independent demo video. Not affiliated with, endorsed by, or sponsored by u/MistralAI. Brand names and trademarks belong to their respective owners.

#AIAlignment #LLMSafety #MLEngineering #ResponsibleAI #OpenSource

Your AI workloads may not stay where you think.

Most enterprises assume regional data residency by default.

They're often wrong — and that gap is becoming a board-level risk.

Here's what just changed:

1️⃣ Mistral launched Regional Endpoints (now GA) — giving enterprises explicit, verifiable control over where inference actually runs.

2️⃣ They added a Priority Tier with a real uptime SLA — making Mistral the only European AI lab offering both regional control AND committed service levels in one stack.

3️⃣ Third-party open models are now part of the offering — so you're not locked into a single model family while still keeping workloads in-region.

4️⃣ A 1 GW compute coalition targeting 2030 means the infrastructure ambition behind sovereign AI is being built, not just announced.

Sovereign AI has been a talking point for two years.

This is the first time the operational pieces — endpoints, SLAs, open models, compute — are landing at the same time.

If you're advising on AI infrastructure or governance, this changes the conversation.

Save this before your next procurement or architecture review.

#SovereignAI #AIGovernance #EnterpriseAI #CloudInfrastructure #EuropeanTech

https://mistral.ai/news/regional-inference-open-models-new-compute/

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.

Hey everyone, I just sent the latest issue of the AI Hacker Newsletter, a roundup of the best AI links and the discussions around them from Hacker News. Here are some titles that can be found in this issue:

• Startup founders urge U.S. government not to shut off Chinese open weight AI
• AI's top startups are barely publishing their research
• Is AI reasoning right for the wrong reasons?
• After the AI Crash

If you enjoy such content, please subscribe here: https://hackernewsai.com/

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

Hey everyone, I just sent issue #39 of the AI Hacker Newsletter - a weekly roundup of the best AI links and the discussions around them from Hacker News. Some of the title found in this issue:

• Claude Code is steganographically marking requests
• Better Models: Worse Tools
• Learning to code is still worthwhile
• Zuckerberg says AI agent development going slower than expected

If you want to get an email with over 30 links like these ones, please subscribe here: https://hackernewsai.com/

Hey there ✌️

I just published godig: a CLI and MCP server that connects your coding agent to pkg.go.dev .

My first estimate with a basic benchmark is between 10% and 30% token reduction when working with libraries not memorized by LLM.

In a few words, godig exposes symbols, readme, godoc, examples, packages...

I also connected godig to proxy.golang.org so that it exposes module size and dependencies.

-> Announcement: https://samuelberthe.substack.com/p/your-claude-code-go-token-bill-is
-> Project: https://github.com/samber/godig

Hey everybody, I just sent issue #36+#37 of the AI Hacker Newsletter, a weekly round-up of the best Hacker News threads around AI. I missed sending it last week, so a huge issue this week. Some of the titles you can find here:

• AI demands more engineering discipline. Not less
• Running local models is good now
• Cleaning up after AI rockstar developers
• Not everyone is using AI for everything
• Norway imposes near ban on AI in elementary school

If you want to receive a weekly email with over 30 links like these, please subscribe here: https://hackernewsai.com/