From the source
Solar Open 2 is designed and trained to serve as the base model for agents in real work environments.
It's trained on a wide range of agent scenarios, including tool calling, coding, and office work, and delivers performance that competes with leading global models across agent, Korean, knowledge, and coding benchmarks.
The model adopts an MoE architecture that activates only 15B of its 250B total parameters per token, improving capability and inference efficiency at the same time.
With quantization, it runs on two NVIDIA H200 GPUs, which makes it practical for enterprises to deploy and operate on their own infrastructure.
Built for agent tasks that run across many steps, it supports a context window of up to 1M tokens and comes with official support for Korean, English, and Japanese.
The model weights are released on Hugging Face under a commercially usable license.
Alongside them, we publish the Solar Open 2 Technical Report, covering the full architecture, training methodology, key experiments, and evaluation conditions.
Key highlights …
