Mistral AI
@MistralAI
Frontier AI in your hands. Get work done with @MistralVibe at
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Three weeks of training camp for Le Chonk. No days off.
Thanks for putting it to the test, @ThibaultJaigu and @RequestyAI.
Impressed by the new @MistralAI large-4 update! The model update is much better at coding and performs as the 2nd best OSS model on our coding benchmark
Mistral researcher @Sagar_Vaze argues some of the most serious recent AI cyberattacks came from closed models, not open-source ones:
"If you look at the most significant malicious attacks that have happened recently, these have actually been perpetrated not by open weights models, but by closed weights models which have either been jailbroken or, in some cases, during training, escaped their sandbox. In practice, that’s how many of the attacks have been perpetrated."
"Defenders trying to shore up their own defenses are having their requests refused by these same providers, because cutting-edge defensive requests look quite similar to offensive ones."
"People trying to defend from malicious attacks, often from closed weights models, find they have no recourse but to use an open weights model."
"It's critical that there are open weights models of sufficient strength that people can scalably defend their infrastructure."
@MistralAI
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Props to @MistralAI for the open-weights release of LE CHONK!
Use it in our new Kilo Desktop app today:
Today, we release the weights of a new and improved Le Chonk, advancing the open frontier for agentic coding and cybersecurity.
💻 Built to build: Le Chonk ranks #1# on @cognition’s FrontierCode among open models, and sets a new benchmark for Pareto efficiency on @artificialanalysis.
🛡 Built to defend: State-of-the-art in cyberdefense, put through the paces by the world's leading cyber vendors, including @CrowdStrike, @cloudflare, @rubrik, @zscaler, and others.
Built for sovereignty: Make it yours. Download the weights on @huggingface , customize it with Mistral Forge, and deploy it wherever you need it.
Read more from our team and customers 👇:
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We sat down with @MistralAI's Pierre Stock and Sagar Vaze from Mistral on launch day of Mistral Large 4.
Open weights. Trained in Mistral’s own data centers. Excels at cyber.
Full conversation on cyber, training, evals and sandboxing:
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Today, we release the weights of a new and improved Le Chonk, advancing the open frontier for agentic coding and cybersecurity.
💻 Built to build: Le Chonk ranks #1# on @cognition’s FrontierCode among open models, and sets a new benchmark for Pareto efficiency on @artificialanalysis.
🛡 Built to defend: State-of-the-art in cyberdefense, put through the paces by the world's leading cyber vendors, including @CrowdStrike, @cloudflare, @rubrik, @zscaler, and others.
Built for sovereignty: Make it yours. Download the weights on @huggingface , customize it with Mistral Forge, and deploy it wherever you need it.
Read more from our team and customers 👇:
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Voxtral Mini Transcribe 3 ranks #2# on Voice Arena’s Diarization + ASR leaderboard.
🚀 Mistral AI’s Voxtral Mini Transcribe 3 ranks #2# out of 9 models by DER on Voice Arena’s Diarization + ASR leaderboard, outperforming its larger counterpart.
Following the launch of Mistral’s new Voxtral 3 family, we evaluated its Mini and Small transcription models on Voice Arena’s Diarization Bench.
🥈 Voxtral Mini Transcribe 3: 40.4% DER (#2#)
Voxtral Small Transcribe 3: 41.1% DER (#4#)
Both models were tested on 139 held-out conversations under identical conditions, using human-verified references, a strict 0 ms collar, and no predefined speaker counts or audio cleanup.
Mini leads on in-person conversations (40.6% vs. 41.5%), while Small performs slightly better on online calls (39.1% vs. 39.5%).
Overlapping speech remains the biggest challenge. Missed speech accounts for 82% of Mini's total DER. Both models correctly identify the exact number of speakers in 83.5% of sessions.
Congratulations to @MistralAI on the release ! 👏
View complete track & condition breakdown:
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Today we’re announcing a new collaboration with @nvidia to bring AI to industrial engineering:
- faster simulation
- open benchmarks and supporting datasets for physics AI
- evaluations for agentic AI in CAE and EDA
More here:
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Can an STT model make sense of a 135 year old recording?
I tested @MistralAI new Voxtral transcription model on a noisy French phonograph recording of Gustave Eiffel from 1891.
It matched 100 of 107 words in INA’s published excerpts (6.5% WER), while transcribing 75 additional words omitted from the reference.
It handled Eiffel’s dictation well but struggled with proper names and some guest dialogue.
A fascinating test of modern speech recognition on audio from 1891.
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Introducing Voxtral 3: state-of-the-art Transcribe and Speech models powering Mistral’s new voice agents API. 🧵
Turns out le Chonk is into rocket science.
Mistral Large 4 scoring well in engineering and astronomy on Ulam’s private benchmark, STEMBench:
Welcome to Mistral, New Material. Let’s bring design to mission-critical AI.
Look up! Mistral models are in orbit 🌍.
Proud to join @orbitworksspace and @LoftOrbital's first-of-its-kind AI satellite constellation with @NVIDIAAIInfra.
Just a few weeks ago, @orbitworksspace launched Altair, the first of a 50-satellite AI constellation that will enable users to receive AI-generated alerts within minutes. @NVIDIAAIInfra solutions is making this possible, supporting models like Mistral’s Ministral 3 to deliver fast, reliable answers for users' critical questions.
Read more:
#SpaceMadeSimple# #AIInfrastructure# #AIforSpace#
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🇫🇷 Le Chonk joins the sudo L7 leaderboard 🇫🇷
We just added @MistralAI's Mistral Large 4 to sudo L7, our benchmark for staff-level software engineering.
Mistral Large 4 scores 13.3%, ahead of Muse Spark 1.3 (12.2%) and Grok 4.7 (10.6%).
sudo L7 tests whether coding agents can go beyond writing correct code to exercise the judgment of experienced engineers: navigating messy systems, spotting hidden risks, and knowing when technically correct code is still the wrong thing to ship.
Allez, le Chonk ! 🥖
Leaderboard ↓
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Mistral Large 4 runs general-purpose agents that gather information and produce finished deliverables across complex workflows.
For their Mistral Large 4 release, @MistralAI ran a blind Surge human eval, with our expert software engineers evaluating five frontier models on coding quality.
Le Chonk ranked #1# among open-weight models and #2# overall, behind only Opus 5.
Unit tests ask: does it work?
Human code review asks: would you merge it?
Our evals measures the difference. Working code is the floor; professional taste and judgment are what make it shippable.
Congrats to the Mistral team on le Chonk and their big release 🇫🇷
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Meet Mistral Large 4, aka Le Chonk.
• 1T parameters, natively multimodal. 49B active.
It is the best open weights model from US or Europe on aggregated benchmarks.
• State-of-the-art on critical workloads, including cyber defense, manufacturing and finance and it surpasses closed frontier models on visual grounding.
• Forged in Europe end-to-end and is deployable from Europe via our own Mistral Cloud infrastructure.
• Available to all via API today. Working with cybersecurity partners privately.
Open weights release end of October.
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Meet Mistral Large 4, aka Le Chonk.
• 1T parameters, natively multimodal. 49B active.
It is the best open weights model from US or Europe on aggregated benchmarks.
• State-of-the-art on critical workloads, including cyber defense, manufacturing and finance and it surpasses closed frontier models on visual grounding.
• Forged in Europe end-to-end and is deployable from Europe via our own Mistral Cloud infrastructure.
• Available to all via API today. Working with cybersecurity partners privately.
Open weights release end of October.
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We are aware of a claim alleging unauthorized access to our systems. Following a thorough investigation, we have found no evidence to support this claim and can confirm that our systems have not been compromised.
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Today, we are announcing a partnership with @mozilla to bring privacy, control and choice to people using AI to browse online. 🦊🐈
