Mistral AI announced Mistral Large 4, codenamed Le Chonk, and an expansion of its Studio enterprise platform in a company post dated 5 November.
The model is in Research Public Preview on Mistral's API, according to Artificial Analysis2, which scored it 38 on its Intelligence Index. The same firm puts its cost per task at more than four times that of open-weights models of similar intelligence.
What Mistral says
Mistral said Large 4 "does great for coding, delivers advanced defensive cybersecurity capabilities, and brings powerful reasoning to complex documents and business tasks," according to its announcement1. The post makes no comparison with earlier models and gives no benchmark figures.
The post also says Studio gains managed agents and apps1, along with new capabilities for workflows, enterprise context, agent observability and evaluations. Event triggers from enterprise systems and a visual graph of workflow logic are also added. Mistral said Studio can run in the cloud, in a customer's VPC, on-premises or across a combination, with human approval required for actions the customer chooses.
Mistral said ABANCA, Accenture, Alten, BNP Paribas, Capgemini, CMA CGM and Tata Consultancy Services already use Studio in production1. The post names no tasks for those customers.
The three worked examples in the post come from Mistral's own teams. The company said an incident-investigation agent built by its engineering team saves "hundreds of hours each month," and a workflow built by its product operations team saves about 35 hours a week. Its Applied AI team built a staffing app. These are Mistral's figures for internal use, and the post does not describe how they were measured.
What Artificial Analysis measured
Artificial Analysis tested the Mistral Large 4 Preview, a 1T-parameter model with 49B active parameters that takes text and image input and produces text. These are its own results, and its article does not describe replication by others.
The preview scored 38 on the Intelligence Index, comparable to GPT-6 Luna (max, 38) and DeepSeek V4.1 Flash (max, 39)2. On the firm's Cyber Index it scored 50, level with GLM-5.3-Flash and ahead of Kimi K3 and DeepSeek V4.1 Flash (max), but behind MiMo-V2.6-Pro at 56. Its best cyber result was 82% on CyberGym-E2E-AA, against 79% for MiMo-V2.6-Pro and 78% for GPT-6 Luna (max).
On GDP.pdf, a document and image reasoning test, it scored 19%, on par with MiMo-V2.6-Pro and behind Kimi K3 (22%). Artificial Analysis called that an 18-point gain over Mistral Large 3, partly driven by API changes that now allow 100 images per request, up from eight for earlier Mistral models.
Cost and availability
Mistral's announcement page does not list pricing. Artificial Analysis reported standard preview pricing of $1.36 per 1M input tokens and $4.18 per 1M output tokens, with $0.14 per 1M cached input tokens. At those rates it put the cost of one Intelligence Index task at $1.13.
A 50% launch discount for the first two weeks lowers that to $0.57, which Artificial Analysis said is still above GLM-5.3-Flash ($0.25) and DeepSeek V4.1 Flash (max, $0.27).
Artificial Analysis said the weights are planned for release at the end of October, and that once released the model would rank among the top three open-weights models on its Cyber Index. The Artificial Analysis article carries no publication date, and Mistral's post is dated 5 November, so the stated timing conflicts with the announcement date. The open-weights version has not been tested, and the results above apply only to the preview.