Model reference · open weights
K-EXAONE is an open-weight language model from LGAI-EXAONE, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
K-EXAONE-236B-A23B Introduction We introduce K-EXAONE, a large-scale multilingual language model developed by LG AI Research. Built using a Mixture-of-Experts architecture, K-EXAONE features 236 billion total parameters, with 23 billion active during inference. Performance evaluations across various benchmarks demonstrate that K-EXAONE excels in reasoning, agentic capabilities, general knowledge, multilingual understanding, and long-context processing. Key Features - Architecture & Efficiency: Features a 236B fine-grained MoE design (23B active) optimized with Multi-Token Prediction (MTP), enabling self-speculative decoding that boosts inference throughput by approximately 1.5x. - Long-Context Capabilities: Natively supports a 256K context window, utilizing a 3:1 hybrid attention scheme with a 128-token sliding window to significantly minimize memory usage during long-document processing. - Multilingual Support: Covers 6 languages: Korean, English, Spanish, German, Japanese, and Vietnamese. Features a redesigned 150k vocabulary with SuperBPE, improving token efficiency by ~30%. - Agentic Capabilities: Demonstrates superior tool-use and search capabilities via multi-agent strategies. - Safety & Ethics: Aligned with universal human values, the model uniquely incorporates Korean cultural and historical contexts to address regional sensitivities often overlooked by other models. It demonstrates high reliability across diverse risk categories. For more details, please refer to the technical report, blog and GitHub. Model Configuration - Number of Parameters: 236B in total and 23B activated - Number of Parameters (without embeddings): 234B - Hidden Dimension: 6,144 - Number of Layers: 48 Main layers + 1 MTP layers - Hybrid Attention Pattern: 12 x (3 Sliding window attention + 1 Global attention) - Sliding Window Attention - Number of Attention Heads: 64 Q-heads and 8 KV-heads - Head Dimension: 128 for both Q/KV - Sliding Window Size: 128 - Global Attention - Number of Attention Heads: 64 Q-heads and 8 KV-heads - Head Dimension: 128 for both Q/KV - No Rotary Positional Embedding Used (NoPE) - Mixture of Experts: - Number of Experts: 128 - Number of Activated Experts: 8
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | LGAI-EXAONE |
|---|---|
| Type | Language models |
| Parameters (lead) | 237.1B |
| Context | 256k tokens |
| Variants | 3 |
| Runs with | transformers |
| Released | 2025-12-26 |
| Popularity | 22k downloads / month |
| Likes | 576 |
| Licence | Commercial licence needed |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
Using it via the API
Once AxForge deploys k-exaone for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (k-exaone below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/chat/completions \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"k-exaone","messages":[{"role":"user","content":"Hello"}]}'
Licence
The weights are open but its licence needs a commercial agreement for business use. AxForge can arrange that licence and host the model for you — you pay AxForge, we settle with the model’s maker. Ask us for a quote. Read the licence ↗