Russian Businesses Surge Chinese LLM Usage More Than 11-Fold in First Half of 2026
Russian small and medium-sized businesses along with large corporations have sharply increased their adoption of Chinese large language models. According to data from MWS Cloud, organizations consumed more than 400 billion tokens during the first half of 2026. This volume is 11.3 times higher than the 39.1 billion tokens recorded for the entire previous year.
The Qwen family remained the undisputed leader. Its share rose from 20 billion tokens and 51.1% in 2025 to 261.1 billion tokens and 59.1% in the first six months of 2026. GLM held second place with 91.2 billion tokens, representing 20.7% of total consumption.
DeepSeek, which ranked third in 2025, was overtaken by the Kimi family. Models from Kimi processed 81.4 billion tokens and captured 18.4% of usage. The rapid pace of the Chinese LLM race means that last year’s frontrunner can quickly fall outside the top three.
The statistics are drawn from MWS GPT Model Hub and MWS GPT platforms, whose primary clients are large enterprises. Businesses deploy these models for chatbots, personalized advertising, mass email campaigns, product descriptions, and analysis of customer reviews and inquiries. In practice, companies assign LLMs tasks that must run continuously, at high speed, and without typical human limitations.
MWS Cloud estimates that the entire Russian LLM market will expand by 35% in 2026, reaching 19.6 billion rubles. The cloud segment, which includes SaaS and API access to models, is expected to approach 1.5 billion rubles. In response to rising demand, MWS Cloud expanded its Model Hub catalog nearly twofold to 17 models. New additions include GLM 5.2, Kimi K2.6, Qwen3.6, Gemma 4, GPT OSS, as well as speech recognition and synthesis tools and rerankers for search systems and RAG pipelines. All services are available through a single OpenAI-compatible API.
The volume of tokens processed indicates that Russian enterprises have moved beyond experimentation and are now embedding Chinese LLMs into core operational processes, with demand continuing to outpace catalog updates.
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