K-EXAONE-236B-A23B
LGAI-EXAONE's K-EXAONE-236B-A23B packs 236 billion parameters into a chat model. K-EXAONE-236B-A23B is an open-weights chat model with roughly 236 billion parameters.
by LGAI-EXAONE · 236B parameters
Best for
Ways to use K-EXAONE-236B-A23B in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your LGAI-EXAONE API key. osFoundry discovers K-EXAONE-236B-A23B automatically — assign it to a Maestro role (router, direct, orchestrator, or fallback) in the Pipeline tab and it is live in every chat. Your key, your provider account — no token markup.
Deploy a dedicated endpoint
K-EXAONE-236B-A23B is open-weights — run it locally for free, or deploy a dedicated GPU endpoint in your workspace for reserved capacity with no rate limits.
Use it in a Room App
Room Apps declare AI features in their manifest, then call them with invokeAI:
import { invokeAI } from '@osfoundry/app-sdk'
// 'summarize' is an AI feature declared in your app manifest.
const result = await invokeAI('summarize', userText)
Call it from your own apps
Once a model is wired into your workspace you can host it as an API and reach it from your own services, scripts, or CI — outside osFoundry.
What hardware can run K-EXAONE-236B-A23B
K-EXAONE-236B-A23B runs on a multi-GPU setup or H200 141GB at Q4 (~142 GB VRAM with KV-cache headroom). Full-precision inference requires multiple H100/H200 GPUs at FP16 (~567 GB).
K-EXAONE-236B-A23B vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about K-EXAONE-236B-A23B
Is K-EXAONE-236B-A23B free to use?
K-EXAONE-236B-A23B is free to run locally on your own hardware. Hosted access through osFoundry is metered (input Free (local), output Free (local)). You can switch between local and hosted at any time.
Can I use K-EXAONE-236B-A23B commercially?
Commercial use is allowed with conditions. Licence terms not specified — verify the upstream model card before commercial use. Check upstream documentation.
How much VRAM does K-EXAONE-236B-A23B need?
Approximately 142 GB at Q4 quantisation, or 567 GB at full FP16 precision. Requires multi-GPU at higher quantisation.
Can I run K-EXAONE-236B-A23B locally?
Yes. K-EXAONE-236B-A23B is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is K-EXAONE-236B-A23B best at?
K-EXAONE-236B-A23B is well-suited to text generation.
How do I use K-EXAONE-236B-A23B in osFoundry?
Paste your LGAI-EXAONE API key in the key dialog (or deploy the open weights for self-hostable models), assign K-EXAONE-236B-A23B to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by LGAI-EXAONE on December 26, 2025. Source: https://huggingface.co/LGAI-EXAONE/K-EXAONE-236B-A23B