Model Card: KRAFTON Raon-1 mini
Raon-1 mini preview: KRAFTON AI (the studio behind PUBG) trained a 28.8B-total/4.3B-active MoE model from scratch, with 262,144-token context and Apache 2.0 open weights. Its hybrid attention stack (Raon Delta Attention + Gated MLA) shrinks KV cache to about 8 KiB per token, and a bundled DFlash2 draft model boosts throughput up to 2.18x on B300 GPUs. It scores 92.9 on an internal Korean chatbot benchmark — far ahead of the similarly-sized Qwen3.6-35B-A3B (74.5) and Gemma 4 26B-A4B (90.6) — but trails Qwen3.6-35B-A3B on MMLU-Pro and BFCL tool-calling. No official API pricing yet; it's open weights plus a time-limited free playground.