Mistral AI Adds Third Party Models to Cloud Platform

August 16, 2026
Mistral AI will host third party open models on its infrastructure, starting with GLM 5.2 from Z.ai. The company also made Regional Endpoints generally available and introduced a Priority Tier in public preview.

Mistral AI is expanding its cloud platform to host third party open models, starting with GLM 5.2 from China based Z.ai, according to Trending Topics. The external models will run on the same infrastructure used for Mistral models, with regional controls and service commitments.

Regional Endpoints are now generally available, letting customers choose Europe or the United States for inference processing. Mistral also introduced Priority Tier in public preview, with an uptime SLA and custom rate limits.

The company is also selling longer term compute commitments through European Compute Units. Named anchor customers include Amadeus, ASML, Capgemini, Caisse des Dépôts, and CMA CGM.

By 2030, Mistral aims to build up to 1 gigawatt of capacity. Regional inference is priced at 1.1 times standard list pricing for input tokens, output tokens, cache reads, and cache writes.

We hope you enjoyed this article.

Consider subscribing to one of our newsletters like Silicon Brief or Daily AI Brief.

Also, consider following us on social media:

AI Chips & Datacenters AI Brief AI Brief (X)

More from: Data Centers

08/15
Z Squared Details Power Strategy for AI Infrastructure Sites
08/15
Compute Exchange Plans Token Forward Contracts for AI Model Costs
08/14
TIER IV Joins JST Program to Open Source Autonomous Driving AI Chip Designs
08/14
CVC DIF to Acquire Majority Stake in firstcolo
08/13
Heron Power Picks Morgan Hill for Grid Hardware Factory

Subscribe to Silicon Brief

Weekly coverage of AI hardware developments including chips, GPUs, cloud platforms, and data center technology.

AI Token Webinar

Whitepaper

AI and the Law: Discussion Paper

This discussion paper explores the intersection of artificial intelligence and legal frameworks, addressing potential legal challenges posed by AI's autonomy, adaptiveness, and opacity. It examines issues such as liability gaps, causation, and the potential for granting AI systems legal personality, aiming to foster further discussion on AI's impact on law reform.

Read more

You May Also Like