Dnotitia Releases DNA 3.0 Language Model Family on Hugging Face

June 02, 2026
Dnotitia has launched DNA 3.0, a family of enterprise AI language models based on Alibaba Cloud's Qwen 3.5 and 3.6, featuring post-training improvements, persona tuning, and integration with Seahorse Cloud.

Dnotitia Inc. announced in a press release the release of DNA 3.0, a family of enterprise AI language models now available on Hugging Face. The models are built on the Qwen 3.5 and 3.6 large language models from Alibaba Cloud, with Dnotitia applying its own post-training and tuning to adapt them for organizational use.

DNA 3.0 has been designed to deliver consistent responses aligned with enterprise data, workflows, and service policies. The models incorporate persona training to reflect company-specific context and product information. Dnotitia also reduced language-mixing issues and response constraints to improve usability in Korean-language enterprise environments.

The DNA 3.0 lineup includes models ranging from 0.8 billion to 122 billion parameters, including Mixture of Experts architectures such as 35B-A3B and 122B-A10B. These architectures activate selected expert modules for each query to balance performance and computational efficiency.

DNA 3.0 is integrated into Seahorse Cloud, Dnotitia’s AI data platform, which transforms enterprise documents and unstructured data into knowledge assets. This integration supports semantic search, context-aware answer generation, and AI agent workflows based on enterprise information.

We hope you enjoyed this article.

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

Also, consider following us on social media:

Subscribe to Enterprise AI Brief

Weekly report on AI business applications, enterprise software releases, automation tools, and industry implementations.

Market report

AI’s Time-to-Market Quagmire: Why Enterprises Struggle to Scale AI Innovation

ModelOp

The 2025 AI Governance Benchmark Report by ModelOp provides insights from 100 senior AI and data leaders across various industries, highlighting the challenges enterprises face in scaling AI initiatives. The report emphasizes the importance of AI governance and automation in overcoming fragmented systems and inconsistent practices, showcasing how early adoption correlates with faster deployment and stronger ROI.

Read more