Yandex Unveils YandexGPT 4 Neural Networks With Enhanced Reasoning and Query Processing

Yandex has introduced its latest generation of language models, YandexGPT 4, featuring two versions: Lite and Pro. These new generative neural networks surpass earlier models, particularly in handling longer and more complex queries.

YandexGPT 4 can now process approximately 60 pages of text, making it capable of solving more diverse and challenging tasks.

Test results show that YandexGPT 4 Pro delivers higher-quality answers than previous models, with significant improvements in 70% of cases. For tasks require

ng open-ended responses, the model approaches the performance level of GPT-4. It also offers enhanced reasoning abilities, which enable it to handle questions that involve analysis.

Compared to the third-generation models, YandexGPT 4 processes four times more text and delivers answers twice as fast.

This capability allows it to address longer and more complicated queries efficiently. Additionally, YandexGPT 4 can generate commands for third-party applications. For example, it can create a command for an airline ticket service to launch a seat search function.

The YandexGPT 4 models are now available via API on Yandex Cloud, although some features are still in testing. Users can try out the new models in a demo chat on the Yandex Cloud platform. Yandex plans to integrate these models into its services in the future.

YandexGPT 4 follows the launch of YandexGPT 3, which debuted earlier this year.

Source: Yandex Press Release

Dan Taylor is the founder and editor of International Search Insights (ISI), the publication behind ReadIsi, and a Partner and Head of Innovation (Search & AI) at SALT.agency. He has worked in search for more than a decade, in-house and agency-side, and is regarded as one of the West’s leading voices on search engines beyond Google, including Yandex, Baidu, Naver and Cốc Cốc. On ReadIsi, Dan covers the engines and AI answer platforms that English-language coverage tends to miss: Baidu and ERNIE, Yandex and Alice AI, Naver, Cốc Cốc, Shenma, Sogou, WeChat and Weibo search, plus DeepSeek and Alibaba’s Qwen. He also keeps dated records of documented changes, such as the Yandex, Baidu and Naver algorithm update histories and the DeepSeek, ERNIE and Qwen model update histories. His approach is to take learnings from global search engines and apply logic with a high evidence threshold. A claim needs a source, patterns seen in one market are treated as a hypothesis until they are checked in another, and where the evidence is thin he says so. For brands, that means advice built on what can be shown, with measurement that separates being cited from being chosen. Dan is credited with coining the term “edge SEO” and won the inaugural TechSEO Boost research competition in 2018 for his work on CDN and edge changes for SEO. In 2026 he was credited with coining “Infinite Tail” to describe how keyword research is changing with AI search. He is the author of AI Search Marketing For The Travel Sector, writes for Search Engine Journal, Search Engine Land and Travel Marketing Guy, and has advised technology, SaaS, travel and enterprise ecommerce brands, including Cloudflare, GitLab and Airbnb. He has given multiple talks and panels at the International Search Summit in Barcelona, and has also spoken at Optimization Moscow, brightonSEO, Google Search Central Live Deep Dive Asia in Bangkok, Athens SEO and the Asia SEO Virtual Summit 2026, where his talk looked at how Baidu, Naver, DeepSeek, Tencent, Cốc Cốc and Yandex built their own AI answers.