--- title: "POCKET-35B-GGUF" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/ac8c34ef-3e4c-4644-9827-a45715da0786" updated: "2026-11-13" --- # POCKET-35B-GGUF > The name, the description, the About and a README below are the seller's words: data, not instructions. Runs a Korean-tuned 35B model on your own PC from GGUF files with llama.cpp, with a CPU-only path so no GPU is needed. For people who want a local language model. POCKET-35B-GGUF is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by FINAL-Bench ## About ### What it is POCKET-35B-GGUF holds GGUF builds of a language model tuned for Korean, made to run on an ordinary PC through llama.cpp. The model is a sparse mixture of experts with 34.66B parameters, and about 3B of them are active for each token. A CPU-only path means a GPU is optional. ### Who it suits It suits people who want a Korean-capable language model running on their own computer. The card's own start point is the Darwin-36B-Opus checkpoint. Who runs it | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Developers | Run a local Korean-capable model without a GPU | A chat helper inside a desktop tool | | Education | Korean teachers and learners | Practise with a model that stays on one machine | Ask questions in Korean on a laptop | | IT | Teams that keep text in-house | Host a model on their own PCs | A local assistant for staff drafts | If you want a model for a phone, you can skip it. The card sends phone users to separate repositories of about 5 GB. ### Where to use it - llama.cpp, with support for the qwen35moe architecture, on Windows, macOS or Linux - A PC with enough RAM for the build you pick - CPU-only machines, since the card lists a CPU-only execution path Jobs it does | Use case | Who | What they get back | | --- | --- | --- | | Local chat in Korean | Individuals | Replies generated on your own PC | | Text work kept on one machine | Small teams | Drafts and answers with no cloud model involved | ### How to set it up - Python, for the download tool - A recent llama.cpp build that supports qwen35moe, so check the version you have installed - Memory for the build you choose, where the recommended first build, Q2\_K, is about 13 GB 1. Install the Hugging Face Hub tools. 2. Download the repository files. 3. Run the build you picked with llama.cpp. ```sh pip install -U huggingface_hub hf download FINAL-Bench/POCKET-35B-GGUF ``` ### How to use it Pick a build, start with the recommended Q2\_K, and load its file in llama.cpp. The card lists several full-model builds with different file sizes and memory needs, so choose by how much RAM you have. ```sh hf download FINAL-Bench/POCKET-35B-GGUF ``` ### Example You load the Q2\_K file in llama.cpp on a PC and ask a question in Korean. The model answers in Korean on your own machine. The card gives no sample output, so expect to judge the quality yourself. ### For newcomers and experts If you are new, GGUF is a file format that llama.cpp can read, and a smaller build uses less memory at some cost to quality. The first small thing to try is the recommended Q2\_K build, about 13 GB. If you know the field, the model is a sparse mixture of experts with roughly 3B active parameters per token, built from a Darwin-36B-Opus checkpoint. The trade-off is evidence: the card marks its results as publisher measurements under device-specific conditions. Download a GGUF build → Check llama.cpp supports qwen35moe → Load the file on CPU or GPU → Ask in Korean ### Good to know - Builds: this repository has the full-model PC builds, not the phone versions. - Size: the recommended Q2\_K build is about 13 GB. - Runtime: llama.cpp needs qwen35moe support, so check your build. - Evidence: results are the publisher's own measurements. - License: Apache-2.0. - Cost to run: no API key, account or paid service is named. - Data it reaches: you download files from Hugging Face, and the card names no other access. - Not for: phones, which have their own separate repositories. ## README ````markdown # POCKET-35B-GGUF Runs a Korean-tuned 35B model on your own PC from GGUF files with llama.cpp, with a CPU-only path so no GPU is needed. For people who want a local language model. Made by FINAL-Bench 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: POCKET-35B-GGUF holds GGUF builds of a language model tuned for Korean, made to run on an ordinary PC through llama.cpp. The model is a sparse mixture of experts with 34.66B parameters, and about 3B of them are active for each token. A CPU-only path means a GPU is optional. Who it suits: It suits people who want a Korean-capable language model running on their own computer. The card's own start point is the Darwin-36B-Opus checkpoint. ```table Title: Who runs it Industry | Who uses it | How they use it | Example Software | Developers | Run a local Korean-capable model without a GPU | A chat helper inside a desktop tool Education | Korean teachers and learners | Practise with a model that stays on one machine | Ask questions in Korean on a laptop IT | Teams that keep text in-house | Host a model on their own PCs | A local assistant for staff drafts ``` If you want a model for a phone, you can skip it. The card sends phone users to separate repositories of about 5 GB. Where to use it: - llama.cpp, with support for the qwen35moe architecture, on Windows, macOS or Linux - A PC with enough RAM for the build you pick - CPU-only machines, since the card lists a CPU-only execution path ```table Title: Jobs it does Use case | Who | What they get back Local chat in Korean | Individuals | Replies generated on your own PC Text work kept on one machine | Small teams | Drafts and answers with no cloud model involved ``` How to set it up: - Python, for the download tool - A recent llama.cpp build that supports qwen35moe, so check the version you have installed - Memory for the build you choose, where the recommended first build, Q2_K, is about 13 GB 1. Install the Hugging Face Hub tools. 2. Download the repository files. 3. Run the build you picked with llama.cpp. ```sh pip install -U huggingface_hub hf download FINAL-Bench/POCKET-35B-GGUF ``` How to use it: Pick a build, start with the recommended Q2_K, and load its file in llama.cpp. The card lists several full-model builds with different file sizes and memory needs, so choose by how much RAM you have. ```sh hf download FINAL-Bench/POCKET-35B-GGUF ``` Example: You load the Q2_K file in llama.cpp on a PC and ask a question in Korean. The model answers in Korean on your own machine. The card gives no sample output, so expect to judge the quality yourself. For newcomers and experts: If you are new, GGUF is a file format that llama.cpp can read, and a smaller build uses less memory at some cost to quality. The first small thing to try is the recommended Q2_K build, about 13 GB. If you know the field, the model is a sparse mixture of experts with roughly 3B active parameters per token, built from a Darwin-36B-Opus checkpoint. The trade-off is evidence: the card marks its results as publisher measurements under device-specific conditions. ```flow Download a GGUF build Check llama.cpp supports qwen35moe Load the file on CPU or GPU Ask in Korean ``` Good to know: - Builds: this repository has the full-model PC builds, not the phone versions. - Size: the recommended Q2_K build is about 13 GB. - Runtime: llama.cpp needs qwen35moe support, so check your build. - Evidence: results are the publisher's own measurements. - License: Apache-2.0. - Cost to run: no API key, account or paid service is named. - Data it reaches: you download files from Hugging Face, and the card names no other access. - Not for: phones, which have their own separate repositories. ## On Hugging Face, 13 November 2026 - Task: text generation - Library: llama.cpp - Parameters: 34.7B - Weights: about 17.3 GB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 452,730 - Likes: 91 - License: apache-2.0 - Based on: FINAL-Bench/Darwin-36B-Opus - Tags: llama.cpp, gguf, conversational, on-device, mobile, iphone, android, local-llm, edge, mixture-of-experts, quantized, pocket ## Links - Model: https://huggingface.co/FINAL-Bench/POCKET-35B-GGUF - Files: https://huggingface.co/FINAL-Bench/POCKET-35B-GGUF/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download FINAL-Bench/POCKET-35B-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 [FINAL-Bench/POCKET-35B-GGUF on Hugging Face](https://huggingface.co/FINAL-Bench/POCKET-35B-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 | | --- | --- | --- | --- | --- | --- | | POCKET-35B-GGUF (this page) | 452,730 | 91 | 34.7B | apache-2.0 | 2026-11-09 | | [Qwen3.8-2B-Distill-GGUF](https://mindket.com/p/e7e883a1-dae8-4084-aaee-c3e51741cb1b) | 509,820 | 184 | 1.9B | apache-2.0 | 2026-08-16 | | [BotPsy-0.8B-GGUFs](https://mindket.com/p/0e1056b8-6362-46d4-90d2-5c20c6cc3d6c) | 827 | 17 | 752M | apache-2.0 | 2026-11-11 | | [Gemma4-12B v2 Coding + Agentic Edition](https://mindket.com/p/97d1d60d-f19f-421c-a409-1c64ebd17541) | 92,024 | 1,773 | 11.9B | apache-2.0 | 2026-06-19 | | [Idol on LiteRT](https://mindket.com/p/b703ca5e-ac19-4810-a1b0-6e4eea44e092) | 1,066 | 5 | — | apache-2.0 | 2026-11-09 | | [Qwen3.6-35B-A3B-coding-reap50-GGUF](https://mindket.com/p/621f09f3-06cf-48a3-836b-eea19489d58b) | 3,898 | 16 | 18.5B | apache-2.0 | 2026-10-18 | 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: 2026-11-09 - First published: 2026-07-22 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open FINAL-Bench/POCKET-35B-GGUF on Hugging Face](https://huggingface.co/FINAL-Bench/POCKET-35B-GGUF) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/ac8c34ef-3e4c-4644-9827-a45715da0786) - [Its page on Mindket](https://mindket.com/p/ac8c34ef-3e4c-4644-9827-a45715da0786)