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A.X K1 Technical Report

About

We introduce A.X K1, a 519B-parameter Mixture-of-Experts (MoE) language model trained from scratch. Our design leverages scaling laws to optimize training configurations and vocabulary size under fixed computational budgets. A.X K1 is pre-trained on a corpus of approximately 10T tokens, curated by a multi-stage data processing pipeline. Designed to bridge the gap between reasoning capability and inference efficiency, A.X K1 supports explicitly controllable reasoning to facilitate scalable deployment across diverse real-world scenarios. We propose a simple yet effective Think-Fusion training recipe, enabling user-controlled switching between thinking and non-thinking modes within a single unified model. Extensive evaluations demonstrate that A.X K1 achieves performance competitive with leading open-source models, while establishing a distinctive advantage in Korean-language benchmarks.

Sung Jun Cheon, Jaekyung Cho, Seongho Choi, Hyunjun Eun, Seokhwan Jo, Jaehyun Jun, Minsoo Kang, Jin Kim, Jiwon Kim, Minsang Kim, Seungsik Kim, Sungwan Kim, Tae Yoon Kim, Youngrang Kim, Hyeongmun Lee, Sangyeol Lee, Sungeun Lee, Youngsoon Lee, Yujin Lee, Seongmin Ok, Chanyong Park, Hyewoong Park, Junyoung Park, Hyunho Yang, Subin Yi, Dhammiko Arya, Soohyun Bae, Dongyeon Cho, Seungmo Cho, Sangho Choi, Yongseok Choi, Gyoungeun Han, Yong-jin Han, Seokyoung Hong, Hyeon Hwang, Wonbeom Jang, Minjeong Ju, Wonjin Jung, Keummin Ka, Sungil Kang, Dongnam Kim, Jonghwi Kim, Joonghoon Kim, SaeRom Kim, Sangjin Kim, Seongwon Kim, Youngjin Kim, Seojin Lee, Sunwoo Lee, Taehoon Lee, Chanwoo Park, Sohee Park, Sooyeon Park, Yohan Ra, Sereimony Sek, Seungyeon Seo, Gun Song, Sanghoon Woo, Janghan Yoon, Sungbin Yoon• 2026

Related benchmarks

TaskDatasetResultRank
Instruction FollowingIFEval--
292
Code GenerationHumanEval+--
189
Instruction FollowingIFBench
Pass@1 (Strict)44.3
68
Code GenerationMBPP+
Score85.7
43
Knowledge EvaluationKMMLU, KMMLU Redux, KMMLU Pro, CLIcK, KoBALT, MMLU Pro, GPQA Diamond
Accuracy84.9
21
Code GenerationLiveCodeBench v6, LiveCodeBench-ko, HumanEval+, HumanEval+ ko, MBPP+, SciCode
Pass@10.93
18
Agentic TaskTau2-Telecom
Accuracy58.1
13
MathematicsAIME25, AIME25-ko, HRM8K, KMO25
Accuracy93
12
Instruction FollowingIFBench, IFEval, IFEval-ko
Accuracy81
9
KnowledgeClick
Score77.2
7
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