whatmodel.sh / A.X K2 (688B-A33B)

A.X K2 (688B-A33B) is an open-weights language model from SK Telecom, released July 2026. Its published size is 691.69B parameters (33B active per token) and a 262k-token context window. Licence: apache-2.0.

Catalogue identity notes

skt/A.X-K2 @2287ca4 (created 2026-07-28, licence apache-2.0). SK Telecom A.X K2 (July 2026), 688B MoE with 33B active, Korean/English; thinking and non-thinking modes. Rows from SKT's CC BY technical report (own runs of A.X K2/K1 and five open-weight baselines).

Model information sources

Release date ↗ · Weights licence ↗

HF safetensors metadata 691,690,231,040 parameters; 33B active per the maker card.

69.3±1.4#92 of 719 LLMsfrom 7 benchmark results across 1 source

$ how it compares

The LLMs ranked either side of A.X K2 (688B-A33B), out of 828 with a score, then more from SK Telecom.

#modelscorewhereRAMreleased
99Qwen3.6 27B Alibaba69±1api $1.20/M +local~18GB2026-04
100Ring-2.6-1T inclusionAI (Ant Group)69±2comparison only2026-05
101A.X K2 (688B-A33B) SK Telecom69±1local~1454GB2026-07
102o3 OpenAI69±1api $3.50/M2025-04
103MiMo-V2.5 (310B-A15B) Xiaomi69±1api $0.21/M +local~100GB2026-04
more from SK Telecom
208A.X K1 (519B-A33B) SK Telecom62±1local~1091GB2025-12

see all LLMs · find the ones that fit your machine

$ what it's good at

coding▁▁▁▃▆██▇▆▄▃▁ #76 of 458 * · 18% of its score · 2 tests

Beats GPT-5.2, Grok 4.20 (0309 reasoning), GPT-5.4 mini here, though they rank higher overall. Trails GLM-4.7, Gemini 3.5 Flash-Lite, MiMo-V2.5 (310B-A15B) here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
LiveCodeBench v6 (Feb–May 2025) lab84.0% ✎▄··█····▄▄·█ beats 4/6medium · avg 45%▇▇▇▇ 8.9%typical
SciCode (level unspecified) lab41.0% ✎▄·····▄█▄▄·▄ beats 2/6hard · avg 16%▇▇▇ 8.6%at its level
math▁▂▃▅▆▅▄█▄▁▁▁ #43 of 398 * · 7.7% of its score · 1 test

Beats Grok 4.7, GLM-5.3-Flash, Gemini 3.6 Flash here, though they rank higher overall.

testresultvs the others in its rundifficultycountswhy
AIME 2026 lab97.1% ✎▄·▄·▄▄··█··▄ beats 6/6medium · avg 56%▇▇▇ 7.7%sharp · maxed out · noisy
other tests4 not in a task · 74% of its score
testresultvs the others in its rundifficultycountswhy
GPQA Diamond lab85.6% ✎▄·····▄█▄▄·▄ beats 1/6hard · avg 45%▇▇▇▇▇▇▇▇▇▇▇▇▇ 33%sharp
Global-MMLU-Lite lab87.6% ✎▃······▅··█▃ beats 2/6medium · avg 60%▇▇▇▇▇▇▇ 17%typical
Humanity's Last Exam lab27.8% ✎▂········█·▂ beats 3/6very hard · avg 5.4%▇▇▇▇▇▇ 15%at its level
IFBench (aggregation unspecified) lab75.9% ✎▃······█▃▃·▃ beats 2/6medium · avg 44%▇▇▇▇ 9.5%typical

$ where to run it

Other ways to run it

  1. Run it as published · needs ~1383.4 GB, NVIDIA only · from huggingface.co/skt
    vllm serve skt/A.X-K2 --tensor-parallel-size 8

Weights and documentation: huggingface.co/skt ↗

$ how the score was worked out · A.X K2 Technical Report (SK T… 99%

Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works

sourceresultsshare of the scorelicence
A.X K2 Technical Report (SK Telecom), arXiv 2608.30181v1 · lab-reported7▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 99%CC BY 4.0
prior · pull toward the middle▇ 1%
weighted average= 69.3

$ improve this page

Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.

data updated · sources and licences · json