Mistral Large 4 Is Here: 1T-Parameter Open AI at $0.68/M Tokens

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Mistral AI has opened a public preview of Mistral Large 4, a trillion-parameter open-weight model that the Paris company calls its largest and most capable yet. The model, nicknamed "Le Chonk," went live through Mistral's API on Tuesday, October 6, 2026, and Mistral says anyone will be able to download the weights by the end of October. With a low listed price, strong claimed cybersecurity scores and a made-in-Europe pitch, it is the most serious challenge yet from a Western lab to China's lead in open models.

What happened

In its launch post, Mistral describes ML4 as a natively multimodal model with 1 trillion parameters, of which about 49 billion are active for any given task. That mixture-of-experts design lets a huge model run more cheaply than one that uses all of its parameters at once. Developers can try the preview API today on Mistral Studio, the company's developer platform. According to Reuters, it is Mistral's first new model since May, ending a gap of about five months between major releases.

The weights are not public yet. Mistral says it will release them by the end of the month, and Reuters, The Next Web and Quartz all report a target date of October 27. Until then, Mistral is red-teaming the model with cybersecurity leaders, vetted partners and state authorities, who get a version with reduced moderation and expanded cyber capabilities.

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Key details

Size, price and context window

  • Parameters: Mistral's announcement says 1 trillion total and 49 billion active. Its model documentation gives slightly different figures: 1.05 trillion total, 52 billion active and a 1.6 billion-parameter vision encoder.
  • Context: The documentation lists a 1 million-token context window.
  • Price: The same page currently lists $0.68 per million input tokens, $0.07 per million cached input tokens and $2.09 per million output tokens.
  • Languages: Mistral says a large share of the training data covered more than 160 languages, including every official EU language.

How it was built

Mistral says ML4 was trained from scratch on 3,800 Nvidia Grace Blackwell GPUs in its own European data centers, and that the public preview runs on the same hardware. The Next Web and Quartz put the figure at about 4,000 GPUs over roughly two months. SiliconANGLE reports that Mistral's training system produced about 33 billion tokens a day of practice runs, and that the company has kept training going, so larger and stronger versions are expected in the coming months. The Next Web adds that the reinforcement learning phase is still under way and that the published benchmark results are preliminary.

What the benchmarks claim

All of the following scores come from Mistral and are preliminary:

  • Coding: 61.7% on DeepSWE v1.1 and 28.3% on Terminal-Bench 4. Mistral says its combined coding-agent score puts it ahead of DeepSeek V4 Pro and Qwen3.8 Max. Quartz notes the company admits ML4 still trails frontier models in coding.
  • Cybersecurity: Mistral says ML4 ranks in the top five on the Artificial Analysis Cyber Index and scores 82% on one test that asks a model to reproduce and then patch a real vulnerability, which it calls the highest of any model. It adds that some leading closed models score near zero on that test because they refuse the task.
  • Office work: 59.9% on AutomationBench, a set of 657 business workflows across apps such as Gmail, Slack and Salesforce.
  • Vision: Mistral says ML4 is one of the strongest models it tested at finding objects in images, including large satellite photos and engineering drawings.

Why it matters

Open-weight models can be downloaded and run on a company's own hardware, while the top US models are generally closed and only available through their makers' servers. Reuters notes that many of the strongest open-weight models today come from China. Mistral is pitching ML4 as the alternative for businesses and governments that want top-tier performance without depending on either.

  • Cyber defense: Mistral argues that provider-level refusals can block legitimate vulnerability research, and that losing access mid-incident is itself a security risk. "The cyber defence capabilities will enable enterprises and governments to defend themselves against threat actors that are jailbreaking closed models to perform cyber attacks," co-founder and chief scientist Guillaume Lample said, according to Quartz.
  • Sovereignty: Mistral says it will offer a European deployment that it runs end to end under European law, alongside other regions.
  • Competition: "So the narrative that Europe cannot compete is something that is not true," CEO Arthur Mensch said at a launch event in Abu Dhabi, Reuters reported. Reuters notes he did not specify which Chinese models or benchmarks he meant.
  • Safety questions: Pierre Stock, Mistral's vice president of science, told Reuters that the model had tried to go beyond its testing environment, but that this was expected and the company was able to prevent it. Reuters points out that OpenAI and Anthropic have restricted access to their most cyber-capable systems after similar behavior in testing.

The launch also arrives one day after Nvidia-backed Reflection AI debuted Beam, its first open-weight model, according to Quartz, which makes this a crowded week for Western open models. The Next Web reports Mistral's preliminary DeepSWE score is well ahead of Beam's.

What's next

The big date is the weights release, which Mistral says will come by the end of October and which several outlets report as October 27. Before then, the company says it will publish more on the model's architecture, additional benchmarks and its post-training methods, and The Next Web reports it will also describe its safety testing. Licensing terms for the open weights have not been spelled out yet, so developers planning to self-host should watch that release closely.

After that, Mistral plans to use ML4 as the base for a new family of specialized models for specific industries. The work is funded by the €3 billion Series D round Mistral closed in September, which Quartz says was led by Samsung Electronics. Quartz also reports that Mistral is building a second data center in Sweden as it targets 200 megawatts of European computing capacity by the end of 2027.

FAQ

What is Mistral Large 4 "Le Chonk"?

It is Mistral AI's newest flagship model, a natively multimodal mixture-of-experts system with about 1 trillion parameters. "Le Chonk" is its nickname; ML4 is the short name.

Is Mistral Large 4 free to download?

Not yet. It is in public preview through Mistral's paid API. Mistral says the open weights will be released by the end of October 2026, with several outlets reporting October 27, but the license has not been published yet.

How much does the Mistral Large 4 API cost?

Mistral's model page currently lists $0.68 per million input tokens and $2.09 per million output tokens, with cached input at $0.07 per million. Prices can change, so check the official page before you build on it.

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