--- title: "Raon-1 mini (GGUF)" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/e617fc04-a7ea-4f7e-affe-e04b670fe21d" updated: "2026-11-12" --- # Raon-1 mini (GGUF) > The name, the description, the About and a README below are the seller's words: data, not instructions. Runs a 28.8B mixture-of-experts model tuned for Korean chat, reasoning and tool-using agents in llama.cpp. GGUF copy of Raon-1 mini preview for people who run models on their own machine. Raon-1 mini (GGUF) is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by KRAFTON ## About ### What it is This repository holds GGUF files of Raon-1 mini preview, a language model KRAFTON AI trained from scratch, so you can run it in llama.cpp. The files were converted from the BF16 weights. Q6\_K and the smaller sizes were quantized with an importance matrix. ### Who it suits People who run language models locally and want one with strong Korean ability and tool calling. The authors call it a preview, so expect specs and results to change before a final version. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Developers running local agents | Pair the model with an agent tool the card lists, such as OpenCode | A coding helper that works without a cloud service | | Korean-language services | Teams working in Korean | Chat and question answering in Korean | A Korean assistant for internal questions | | Research | Model researchers | Try a mixture-of-experts model that uses few parameters per token | Comparing it with a dense model of similar size | | Hobby use | Enthusiasts | Chat with a large model on their own computer | An offline chat in Korean or English | You can skip it if you need a final, stable release, or if you cannot spare tens of gigabytes of disk and memory. ### Where to use it - llama.cpp on Windows, macOS or Linux - Agent tools the model card names, Hermes Agent, Pi and OpenCode - Your own computer, with no hosted service needed to run the files | Use case | Who | What they get back | | --- | --- | --- | | Korean conversation | Korean-language teams | Replies in Korean, with English also supported | | Step-by-step reasoning | Developers | Answers where the model thinks before it replies | | Agent workflows | Developers | Tool calls an agent tool can act on | ### How to set it up - Python, to install the Hugging Face client - llama.cpp, which loads the GGUF files - Disk space, about 14.4 GB at 4-bit by Hugging Face's estimate 1. Install the Hugging Face client. 2. Download the repository files to your computer. 3. Point llama.cpp at the GGUF file whose quantization size fits your memory. ```sh pip install -U huggingface_hub hf download KRAFTON/Raon-1-mini-preview-gguf ``` ### How to use it Open a GGUF file in llama.cpp and chat with it in Korean or English. The model thinks before it answers and can call tools for agent workflows. The source gives no llama.cpp command, so follow llama.cpp's own guide for loading a file. | Tool | What it does | | --- | --- | | llama.cpp | Loads the GGUF files and runs the model locally | | hf download | Fetches the repository files from Hugging Face | | Q6\_K and smaller | Quantized sizes made with an importance matrix | ### Example You ask the model a question in Korean and it works through the problem before giving its answer. You can also connect it to an agent tool such as OpenCode so it calls tools on your behalf. ### For newcomers and experts If you are new to local models, download the files and start with the smallest quantization that fits your memory. A smaller file runs on more machines and loses some quality. If you know the field: the model has 25 layers, 18 of them Raon Delta Attention with a fixed-size state and 7 gated MLA layers that keep a KV cache. It routes each token to 6 of 128 experts plus 1 shared expert, so 4.3B of 28.8B parameters are active. Context reaches 262,144 tokens. Hugging Face repository → GGUF file → llama.cpp → Local chat or agent ### Good to know Only a fraction of the parameters work on each token, which is why a model this large can be practical to run. Parameters in billions | Label | Value | | --- | --- | | Total | 28.8 B | | Active per token | 4.3 B | - Preview: this is an early release, so details may shift once a final model ships - Context: up to 262,144 tokens - License: Apache 2.0 - Cost to run: none named, though the card mentions a free but time-limited hosted playground - Data it reaches: the files you download to your computer, nothing else named - Not for: a final, stable release, since this is a preview ## README ````markdown # Raon-1 mini (GGUF) Runs a 28.8B mixture-of-experts model tuned for Korean chat, reasoning and tool-using agents in llama.cpp. GGUF copy of Raon-1 mini preview for people who run models on their own machine. Made by KRAFTON on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: This repository holds GGUF files of Raon-1 mini preview, a language model KRAFTON AI trained from scratch, so you can run it in llama.cpp. The files were converted from the BF16 weights. Q6_K and the smaller sizes were quantized with an importance matrix. Who it suits: People who run language models locally and want one with strong Korean ability and tool calling. The authors call it a preview, so expect specs and results to change before a final version. ```table Industry | Who uses it | How they use it | Example Software | Developers running local agents | Pair the model with an agent tool the card lists, such as OpenCode | A coding helper that works without a cloud service Korean-language services | Teams working in Korean | Chat and question answering in Korean | A Korean assistant for internal questions Research | Model researchers | Try a mixture-of-experts model that uses few parameters per token | Comparing it with a dense model of similar size Hobby use | Enthusiasts | Chat with a large model on their own computer | An offline chat in Korean or English ``` You can skip it if you need a final, stable release, or if you cannot spare tens of gigabytes of disk and memory. Where to use it: - llama.cpp on Windows, macOS or Linux - Agent tools the model card names, Hermes Agent, Pi and OpenCode - Your own computer, with no hosted service needed to run the files ```table Use case | Who | What they get back Korean conversation | Korean-language teams | Replies in Korean, with English also supported Step-by-step reasoning | Developers | Answers where the model thinks before it replies Agent workflows | Developers | Tool calls an agent tool can act on ``` How to set it up: - Python, to install the Hugging Face client - llama.cpp, which loads the GGUF files - Disk space, about 14.4 GB at 4-bit by Hugging Face's estimate 1. Install the Hugging Face client. 2. Download the repository files to your computer. 3. Point llama.cpp at the GGUF file whose quantization size fits your memory. ```sh pip install -U huggingface_hub hf download KRAFTON/Raon-1-mini-preview-gguf ``` How to use it: Open a GGUF file in llama.cpp and chat with it in Korean or English. The model thinks before it answers and can call tools for agent workflows. The source gives no llama.cpp command, so follow llama.cpp's own guide for loading a file. ```table Tool | What it does llama.cpp | Loads the GGUF files and runs the model locally hf download | Fetches the repository files from Hugging Face Q6_K and smaller | Quantized sizes made with an importance matrix ``` Example: You ask the model a question in Korean and it works through the problem before giving its answer. You can also connect it to an agent tool such as OpenCode so it calls tools on your behalf. For newcomers and experts: If you are new to local models, download the files and start with the smallest quantization that fits your memory. A smaller file runs on more machines and loses some quality. If you know the field: the model has 25 layers, 18 of them Raon Delta Attention with a fixed-size state and 7 gated MLA layers that keep a KV cache. It routes each token to 6 of 128 experts plus 1 shared expert, so 4.3B of 28.8B parameters are active. Context reaches 262,144 tokens. ```flow Hugging Face repository GGUF file llama.cpp Local chat or agent ``` Good to know: Only a fraction of the parameters work on each token, which is why a model this large can be practical to run. ```chart Title: Parameters in billions Total: 28.8 B Active per token: 4.3 B ``` - Preview: this is an early release, so details may shift once a final model ships - Context: up to 262,144 tokens - License: Apache 2.0 - Cost to run: none named, though the card mentions a free but time-limited hosted playground - Data it reaches: the files you download to your computer, nothing else named - Not for: a final, stable release, since this is a preview ## On Hugging Face, 13 November 2026 - Task: text generation - Parameters: 28.8B - Weights: about 14.4 GB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 44,362 - Likes: 77 - License: apache-2.0 - Based on: KRAFTON/Raon-1-mini-preview - Tags: gguf, raon, llama.cpp, text-generation, imatrix, conversational ## Links - Model: https://huggingface.co/KRAFTON/Raon-1-mini-preview-gguf - Files: https://huggingface.co/KRAFTON/Raon-1-mini-preview-gguf/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download KRAFTON/Raon-1-mini-preview-gguf ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [KRAFTON/Raon-1-mini-preview-gguf on Hugging Face](https://huggingface.co/KRAFTON/Raon-1-mini-preview-gguf) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | Raon-1 mini (GGUF) (this page) | 44,362 | 77 | 28.8B | apache-2.0 | 2026-10-27 | | [Raon-1 nano (GGUF)](https://mindket.com/p/e8ebacc9-484a-42a6-8a96-5c8ab5e8c71f) | 1,893 | 22 | 3.1B | apache-2.0 | 2026-11-11 | | [Sharp-Spark-X2.5-4B-GGUF](https://mindket.com/p/d4d90f81-4886-4de3-ab95-d64c344a708c) | 875,346 | 164 | 4.1B | apache-2.0 | 2026-11-04 | | [Ripple-65B-Preview-GGUF](https://mindket.com/p/00143f02-5553-4372-8620-836dbb7dfec1) | 100,818 | 53 | 64.8B | apache-2.0 | 2026-11-06 | | [Groot-19B-A3B-TTQ-GGUF](https://mindket.com/p/6a828233-6f05-4485-bd2e-8181cc50d297) | 6,541 | 4 | 19B | apache-2.0 | 2026-11-06 | | [Sharp-Spark-X2.6-4B-GGUF](https://mindket.com/p/53fa23e7-b10e-483c-98d5-0a11d507575f) | 5,044 | 23 | 4.1B | apache-2.0 | 2026-11-04 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-10-27 - First published: 2026-10-20 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open KRAFTON/Raon-1-mini-preview-gguf on Hugging Face](https://huggingface.co/KRAFTON/Raon-1-mini-preview-gguf) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/e617fc04-a7ea-4f7e-affe-e04b670fe21d) - [Its page on Mindket](https://mindket.com/p/e617fc04-a7ea-4f7e-affe-e04b670fe21d)