NVIDIA brings Korea’s leading open models to production with Dynamo
NVIDIA is releasing Dynamo-optimized deployment recipes for four of Korea’s leading open models, including models from SK Telecom, LG AI Research, Upstage and Motif Technologies. The recipes are designed to help developers deploy the models across multiple GPUs and move them into production faster.
- NVIDIA released Dynamo recipes for four Korean open models.
- Supported models include A.X K2, K-EXAONE 2.0, Solar Open 2 and Motif-3.
- Dynamo coordinates routing and communication across multi-GPU deployments.
- The recipes are optimized for NVIDIA B200 GPUs.
- NVIDIA claims up to 2x performance out of the box.
Four Korean models supported
The recipes support A.X K2 from SK Telecom, K-EXAONE 2.0 from LG AI Research, Solar Open 2 from Upstage and Motif-3 from Motif Technologies. NVIDIA describes these as Korea’s leading open models and says the recipes can help turn them into broadly accessible AI for All services.
The release gives developers deployment guidance tailored to each model rather than requiring them to work out the necessary multi-GPU configuration independently. NVIDIA says the recipes take the guesswork out of deployment and help developers bring Korea’s open models into production faster.
Why multi-GPU deployment is difficult
As models grow beyond the capacity of a single GPU, they must be split across multiple GPUs. That setup requires careful coordination of request routing and communication between the GPUs to maintain performance.
NVIDIA Dynamo is an open source, distributed inference-serving framework built to deploy models in multi-node environments at data center scale. According to NVIDIA, Dynamo handles the routing and communication needed in these environments to maximize inference performance.
The framework is aimed at the serving stage, where deployed models process user or application requests. Its role is to coordinate how those requests move through a distributed model deployment, addressing a technical challenge that becomes more important as models exceed the capacity of one GPU.
Recipes optimized for NVIDIA B200 GPUs
NVIDIA says the new recipes are optimized for NVIDIA B200 GPUs and deliver up to 2x performance out of the box. The company does not provide additional performance measurements or details about the conditions behind that figure in the announcement.
Because the recipes combine the Dynamo framework with deployment instructions for specific open models, developers can use them as a starting point for serving those models in multi-node environments. NVIDIA’s stated aim is to shorten the path from an open model to a production service.
What the release means for developers
The release connects four Korean open models with an open source framework for distributed inference serving. For developers working with those models, NVIDIA says the recipes can reduce deployment uncertainty, support multi-GPU operation and make production deployment faster.
For Korea’s AI ecosystem, the announcement presents open models from local companies as candidates for data center scale services. The source frames the result as a way to make these models more broadly accessible through AI for All services, while the stated performance claim applies to deployments optimized for NVIDIA B200 GPUs.
