--- title: "Raon-1 nano (LiteRT-LM)" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/7d6549cf-46fd-47a8-8cc7-0ad4fbbe6cb1" updated: "2026-11-12" --- # Raon-1 nano (LiteRT-LM) > The name, the description, the About and a README below are the seller's words: data, not instructions. Packs Raon-1 nano as a 4-bit LiteRT-LM bundle with a 4,096-token context, for running a Korean and English chat model on devices. Replies come without a thinking step. Raon-1 nano (LiteRT-LM) 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 a LiteRT-LM bundle of Raon-1 nano, a compact KRAFTON AI language model for Korean and English chat. The bundle stores weights in 4 bits using GPTQ, runs activations in fp16 and has a context of 4,096 tokens. It replies directly, with no thinking phase. ### Who it suits It suits developers who build on-device apps with LiteRT-LM and want a small Korean and English model. Who might use it | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Mobile apps | App developers | Ship a small chat model inside a device app | An in-app assistant that answers in Korean or English | | Edge devices | Embedded engineers | Try a 4-bit model where memory is tight | A trial of on-device text replies | | AI research | Researchers | Compare the 4-bit bundle with the full model | Checking what the short context window changes | People who need long context or a thinking step can skip it, since the full model supports 262,144 tokens. ### Where to use it - LiteRT-LM: the library this bundle is made for - Windows, macOS or Linux: download the files with Python - Other runtimes: the card lists Transformers, vLLM, llama.cpp and MLX for Raon-1 nano, and this bundle is the LiteRT-LM one Jobs it does | Use case | Who | What they get back | | --- | --- | --- | | On-device chat | App developers | Short replies in Korean or English from a 4-bit bundle | | Quick answers | Product teams | Direct answers with no thinking step | | Instruction following | Developers | Text written to match the instruction given | ### How to set it up You need these first: - Python on Windows, macOS or Linux - A LiteRT-LM setup that can load the bundle 1. Install the Hugging Face hub package. 2. Download the bundle files. 3. Load the bundle in LiteRT-LM, following the model card. ```sh pip install -U huggingface_hub hf download KRAFTON/Raon-1-nano-litert-lm ``` ### How to use it Download the bundle, load it in LiteRT-LM and send prompts in Korean or English. This command fetches the files. ```sh hf download KRAFTON/Raon-1-nano-litert-lm ``` The card lists sampling settings by task for Raon-1 nano. Recommended sampling settings | Task | Temperature | Presence penalty | | --- | --- | --- | | General chat, knowledge questions, instruction following | 0.1 | 1.5 | | Agentic work or code | 1.0 | Not set | The output token limit is worth raising for longer replies. ### Example You load the bundle, set temperature to 0.1 and presence penalty to 1.5, and ask a general question in Korean. A direct text reply comes back with no thinking text in front of it. ### For newcomers and experts If you are new to this, think of it as a small chat model packed for phones and other devices. Download it and try one short question once your LiteRT-LM setup is ready. If you work in the field, the base model is a hybrid with 24 layers, 18 of them linear attention and 6 full attention. This bundle quantizes the weights to 4 bits with GPTQ and keeps activations in fp16. Its 4,096-token window is far shorter than the 262,144 tokens of the full model. Download the bundle → Load it in LiteRT-LM → Send a Korean or English prompt → Read the direct reply ### Good to know The context window is the main trade-off against the full model. Context length in tokens | Label | Value | | --- | --- | | This bundle | 4096 tokens | | Full Raon-1 nano | 262144 tokens | - License: apache-2.0 - Cost to run: none named - Data it reaches: only the prompts you give it, with no outside service named - Not for: prompts longer than its 4,096-token context ## README ````markdown # Raon-1 nano (LiteRT-LM) Packs Raon-1 nano as a 4-bit LiteRT-LM bundle with a 4,096-token context, for running a Korean and English chat model on devices. Replies come without a thinking step. 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 a LiteRT-LM bundle of Raon-1 nano, a compact KRAFTON AI language model for Korean and English chat. The bundle stores weights in 4 bits using GPTQ, runs activations in fp16 and has a context of 4,096 tokens. It replies directly, with no thinking phase. Who it suits: It suits developers who build on-device apps with LiteRT-LM and want a small Korean and English model. ```table Title: Who might use it Industry | Who uses it | How they use it | Example Mobile apps | App developers | Ship a small chat model inside a device app | An in-app assistant that answers in Korean or English Edge devices | Embedded engineers | Try a 4-bit model where memory is tight | A trial of on-device text replies AI research | Researchers | Compare the 4-bit bundle with the full model | Checking what the short context window changes ``` People who need long context or a thinking step can skip it, since the full model supports 262,144 tokens. Where to use it: - LiteRT-LM: the library this bundle is made for - Windows, macOS or Linux: download the files with Python - Other runtimes: the card lists Transformers, vLLM, llama.cpp and MLX for Raon-1 nano, and this bundle is the LiteRT-LM one ```table Title: Jobs it does Use case | Who | What they get back On-device chat | App developers | Short replies in Korean or English from a 4-bit bundle Quick answers | Product teams | Direct answers with no thinking step Instruction following | Developers | Text written to match the instruction given ``` How to set it up: You need these first: - Python on Windows, macOS or Linux - A LiteRT-LM setup that can load the bundle 1. Install the Hugging Face hub package. 2. Download the bundle files. 3. Load the bundle in LiteRT-LM, following the model card. ```sh pip install -U huggingface_hub hf download KRAFTON/Raon-1-nano-litert-lm ``` How to use it: Download the bundle, load it in LiteRT-LM and send prompts in Korean or English. This command fetches the files. ```sh hf download KRAFTON/Raon-1-nano-litert-lm ``` The card lists sampling settings by task for Raon-1 nano. ```table Title: Recommended sampling settings Task | Temperature | Presence penalty General chat, knowledge questions, instruction following | 0.1 | 1.5 Agentic work or code | 1.0 | Not set ``` The output token limit is worth raising for longer replies. Example: You load the bundle, set temperature to 0.1 and presence penalty to 1.5, and ask a general question in Korean. A direct text reply comes back with no thinking text in front of it. For newcomers and experts: If you are new to this, think of it as a small chat model packed for phones and other devices. Download it and try one short question once your LiteRT-LM setup is ready. If you work in the field, the base model is a hybrid with 24 layers, 18 of them linear attention and 6 full attention. This bundle quantizes the weights to 4 bits with GPTQ and keeps activations in fp16. Its 4,096-token window is far shorter than the 262,144 tokens of the full model. ```flow Download the bundle Load it in LiteRT-LM Send a Korean or English prompt Read the direct reply ``` Good to know: The context window is the main trade-off against the full model. ```chart Title: Context length in tokens This bundle: 4096 tokens Full Raon-1 nano: 262144 tokens ``` - License: apache-2.0 - Cost to run: none named - Data it reaches: only the prompts you give it, with no outside service named - Not for: prompts longer than its 4,096-token context ## On Hugging Face, 13 November 2026 - Task: text generation - Library: litert-lm - Downloads in the last 30 days: 26 - Likes: 12 - License: apache-2.0 - Based on: KRAFTON/Raon-1-nano - Tags: litert-lm, raon, text-generation ## Links - Model: https://huggingface.co/KRAFTON/Raon-1-nano-litert-lm - Files: https://huggingface.co/KRAFTON/Raon-1-nano-litert-lm/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-nano-litert-lm ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [KRAFTON/Raon-1-nano-litert-lm on Hugging Face](https://huggingface.co/KRAFTON/Raon-1-nano-litert-lm) ## 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 nano (LiteRT-LM) (this page) | 26 | 12 | — | apache-2.0 | 2026-11-10 | | [Raon-1 mini (GGUF)](https://mindket.com/p/e617fc04-a7ea-4f7e-affe-e04b670fe21d) | 44,362 | 77 | 28.8B | apache-2.0 | 2026-10-27 | | [Raon-1 mini](https://mindket.com/p/f0065aba-84b3-4c7b-a321-1f40e91663ef) | 4,489 | 242 | 28.8B | apache-2.0 | 2026-11-12 | | [Raon-1 nano (GGUF)](https://mindket.com/p/e8ebacc9-484a-42a6-8a96-5c8ab5e8c71f) | 1,893 | 22 | 3.1B | apache-2.0 | 2026-11-11 | | [Raon-1 nano](https://mindket.com/p/6ebdc829-eed0-4075-860b-08f56afcc747) | 446 | 77 | 3.5B | apache-2.0 | 2026-11-11 | | [Raon-1 nano (MLX)](https://mindket.com/p/21de4b2d-c17f-4de5-9d3b-ed6fb165cd2a) | 94 | 16 | 3.1B | apache-2.0 | 2026-11-11 | Numbers as Mindket last read them, on 2026-11-12. ## 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: 2026-11-10 - First published: 2026-11-10 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open KRAFTON/Raon-1-nano-litert-lm on Hugging Face](https://huggingface.co/KRAFTON/Raon-1-nano-litert-lm) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/7d6549cf-46fd-47a8-8cc7-0ad4fbbe6cb1) - [Its page on Mindket](https://mindket.com/p/7d6549cf-46fd-47a8-8cc7-0ad4fbbe6cb1)