Modeller

A large-scale sparse Mixture-of-Experts language model built from the ground up by South Korea's Motif Technologies with a fully in-house, proprietary design (Grouped Differential Latent Attention, per-expert Grouped PolyNorm, modified mHC). Has roughly 314B total parameters with about 13B active per token (384 routed experts, top-8, plus one shared expert) and a native 256K context window (262,144 tokens). Multilingual and general-purpose, with reasoning and tool-calling support in vLLM serving. This is an intermediate preview/beta checkpoint, released with open weights (bfloat16) for non-commercial research use ahead of the final release.

Upstage's powerful Mixture-of-Experts language model with 102B total parameters and 12B active parameters per forward pass. Optimized for Korean with strong English and Japanese support. Excels at complex reasoning, structured output generation, and agentic workflows.