Mistral releases weights of 1T-parameter Mistral Large 4, with big coding gains and API prices cut roughly in half

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Mistral releases weights of 1T-parameter Mistral Large 4, with big coding gains and API prices cut roughly in half

Mistral published the weights of Mistral Large 4 (Le Chonk), a 1-trillion-parameter natively multimodal model trained from scratch on European infrastructure, under a modified MIT license that requires a commercial license only for serving it as a model-as-a-service.
It leads open-weight coding with 19.7% on Cognition's FrontierCode 2.0, 41% on Terminal-Bench 4.0 (up 13 points from the preview) and 48% on the Artificial Analysis Coding Agent Index, tied with GLM-5.3 while using 47% fewer tokens per task.
Mistral reports 51% on the Artificial Analysis Cyber Index for finding, reproducing and patching vulnerabilities, plus a 96.6% refusal rate on malicious cyber prompts drawn from JailbreakBench, StrongREJECT and AgentHarm.
The model adds three reasoning modes (Low, Medium, High as default) to trade token spend against precision, and API pricing is now $0.7 per million input tokens and $2.1 per million output tokens, roughly half the preview price of $1.36 and $4.18.
In Surge Code's blind pairwise evaluation it was preferred over GLM-5.3, Kimi K3 and DeepSeek V4.1 Flash, ranking behind only Claude Opus 5.5.

Hacker News opinions

The links are buried at the bottom. The repos are up at huggingface.co/mistralai/Mistral-Large-4-1T-A52B. If Unsloth or mradermacher puts out a quant that fits my box, I'll actually give it a shot.

Why is it so hard to give Mistral money? I clicked around for ages looking for a payment page. Two clicks and a credit card form, that's all I want.

It's console.mistral.ai. Sign up, you get a free account, then upgrade to Pro or pay-as-you-go. Maybe too hidden, but calling it hard isn't fair.

It's not open weight in the OSI sense. The license is modified MIT, so if you serve it as a business you need a license. Internal use is fine.

Where does that definition come from? The weights are downloadable, and that's what open weight means to basically everyone I know.

That reads more like a website ToS than an enforceable license. The weights aren't human authored, so copyright doesn't really bite; they'd have to lean on contract law.

Pricing got cut to $0.7/M input and $2.1/M output, down from $1.36 and $4.18. At the old price it wasn't competitive in my evals, so now it's worth another look.

Nobody puts cache pricing in these comparisons. My coding sessions run like 97% cached input. DeepSeek spoiled us and I'm not going back to hidden cache rates.

The benchmark numbers are dreadful and it costs more than Sol. If you need an EU model, knock yourself out, but plenty of models are smarter for less money.

Worth knowing they tack a 10% upcharge onto regional EU inference. Matters if you're in Europe and want EU-only serving.

I'm a customer out of principle, and the 18 eur plan is genuinely good, 255 eur of tokens included. Just create the right kind of API key or you get billed per token on top.

At that model size the pricing looks aggressive. Maybe they're serving at a loss for training feedback, funded by the margin on GLM 5.3 serving.

Only real reason to pick this over the Chinese open-weight models is EU provenance, and that doesn't matter to me. I pick on performance, and from what I've seen this isn't it.