- Built on Qwen 3.5/3.6 and tuned for institutional and enterprise use
- Dnotitia releases DNA 3.0, a family of AI language models built on Qwen 3.5/3.6 and enhanced through proprietary post-training
- The model family is designed to help organizations adapt AI to their own data, workflows, and response policies
- DNA models are already integrated into Seahorse Cloud, Dnotitia's AI data platform for enterprise Q&A and AI agent applications
- The lineup ranges from 0.8B to 122B-A10B, supporting use cases from edge environments to enterprise AI agents
SEOUL, South Korea, June 2, 2026 /PRNewswire/ -- Dnotitia Inc. (Dnotitia), a company specializing in long-term memory AI and semiconductor-based AI infrastructure technologies, today announced the release of DNA 3.0, an enterprise-ready AI language model family, on Hugging Face.
DNA 3.0 is built on Qwen 3.5/3.6, a large language model family released by Alibaba Cloud. Dnotitia applied its own post-training and tuning to the models, enabling organizations to adapt them to their data, workflows, and response requirements.
The release reflects Dnotitia's approach to making open models more useful in real enterprise environments. Rather than using an open model as-is, DNA 3.0 is tuned to deliver more consistent responses, reflect organizational context, and support practical AI agent use cases.
Dnotitia also applied persona training to DNA 3.0, allowing the model to better reflect company information and product context. This is designed to support organizations that want AI models to respond in line with their internal knowledge, service policies, and business requirements.
DNA 3.0 has also been post-trained to reduce certain response constraints and language-mixing issues that may appear when adapting Qwen-based models. This improves usability in Korean-language enterprise and institutional environments, where stable question-answering and workflow support are critical.
The DNA model family is currently integrated into Seahorse Cloud, Dnotitia's AI data platform. Seahorse Cloud converts enterprise documents and unstructured data into AI-ready knowledge assets, enabling semantic search, context-aware answer generation, and AI agent workflows based on enterprise data.
Through DNA 3.0, Dnotitia plans to further strengthen Seahorse Cloud's ability to support enterprise data-driven AI agents. The goal is to help organizations move beyond storing and searching data, and instead turn their information assets into a usable AI knowledge layer for real business workflows.
The DNA 3.0 lineup includes models ranging from lightweight versions to mid- and large-scale Mixture-of-Experts (MoE) models. Released models include 0.8B, 2B, 4B, 9B, 27B, 35B-A3B, and 122B-A10B, allowing users to choose models based on deployment environment, performance needs, and cost considerations.
The 35B-A3B and 122B-A10B models use a MoE architecture, which activates only selected expert modules for each query. This approach helps deliver large-model capabilities while reducing the computational load required for inference. DNA 3.0 also inherits key capabilities from previous generations, including long-context handling, reasoning trace preservation, tool use, and coding support.
"Institutions and enterprises need AI models that can be adapted to their own data and workflow context," said MK Chung, CEO of Dnotitia. "By integrating DNA 3.0 with Seahorse Cloud, we will continue to expand enterprise AI agent capabilities powered by organization-specific data."
Dnotitia has continued to expand its DNA model family since the release of DNA 1.0 in December 2024, followed by DNA-R1, a Korean reasoning-focused model, and DNA 2.0, a Korean agentic AI language model. DNA 3.0 builds on this progression by strengthening enterprise-oriented tuning and product integration through Seahorse Cloud.
SEOUL, South Korea, June 2, 2026 /PRNewswire/ -- Dnotitia Inc. (Dnotitia), a company specializing in long-term memory AI and semiconductor-based AI infrastructure technologies, today announced the release of DNA 3.0, an enterprise-ready AI language model family, on Hugging Face.
DNA 3.0 is built on Qwen 3.5/3.6, a large language model family released by Alibaba Cloud. Dnotitia applied its own post-training and tuning to the models, enabling organizations to adapt them to their data, workflows, and response requirements.
The release reflects Dnotitia's approach to making open models more useful in real enterprise environments. Rather than using an open model as-is, DNA 3.0 is tuned to deliver more consistent responses, reflect organizational context, and support practical AI agent use cases.
Dnotitia also applied persona training to DNA 3.0, allowing the model to better reflect company information and product context. This is designed to support organizations that want AI models to respond in line with their internal knowledge, service policies, and business requirements.
DNA 3.0 has also been post-trained to reduce certain response constraints and language-mixing issues that may appear when adapting Qwen-based models. This improves usability in Korean-language enterprise and institutional environments, where stable question-answering and workflow support are critical.
The DNA model family is currently integrated into Seahorse Cloud, Dnotitia's AI data platform. Seahorse Cloud converts enterprise documents and unstructured data into AI-ready knowledge assets, enabling semantic search, context-aware answer generation, and AI agent workflows based on enterprise data.
Through DNA 3.0, Dnotitia plans to further strengthen Seahorse Cloud's ability to support enterprise data-driven AI agents. The goal is to help organizations move beyond storing and searching data, and instead turn their information assets into a usable AI knowledge layer for real business workflows.
The DNA 3.0 lineup includes models ranging from lightweight versions to mid- and large-scale Mixture-of-Experts (MoE) models. Released models include 0.8B, 2B, 4B, 9B, 27B, 35B-A3B, and 122B-A10B, allowing users to choose models based on deployment environment, performance needs, and cost considerations.
The 35B-A3B and 122B-A10B models use a MoE architecture, which activates only selected expert modules for each query. This approach helps deliver large-model capabilities while reducing the computational load required for inference. DNA 3.0 also inherits key capabilities from previous generations, including long-context handling, reasoning trace preservation, tool use, and coding support.
"Institutions and enterprises need AI models that can be adapted to their own data and workflow context," said MK Chung, CEO of Dnotitia. "By integrating DNA 3.0 with Seahorse Cloud, we will continue to expand enterprise AI agent capabilities powered by organization-specific data."
Dnotitia has continued to expand its DNA model family since the release of DNA 1.0 in December 2024, followed by DNA-R1, a Korean reasoning-focused model, and DNA 2.0, a Korean agentic AI language model. DNA 3.0 builds on this progression by strengthening enterprise-oriented tuning and product integration through Seahorse Cloud.
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Dnotitia Releases DNA 3.0, an Enterprise-Ready AI Language Model Family
