--- title: "Qwen3-8B-GGUF" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/3520dd40-579f-4e47-be5f-9890e081eff3" updated: "2026-11-12" --- # Qwen3-8B-GGUF > The name, the description, the About and a README below are the seller's words: data, not instructions. Runs Qwen3-8B as quantized GGUF files in llama.cpp or Ollama, with a thinking mode for math, code and logic and a plain mode for chat. For people who want a local model with a choice of file sizes. Qwen3-8B-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 Qwen ## About ### What it is Qwen3-8B-GGUF holds Qwen's 8.2B-parameter Qwen3-8B model as GGUF files for local runtimes. It is a text model that switches between a thinking mode for math, code and logic and a plain mode for everyday chat. The card lists support for more than 100 languages and tool use in agent tasks. ### Who it suits It suits developers and hobbyists who want a capable open model on their own machine, with a choice of file sizes. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software development | Developers | Run a local assistant for code and tool calls | Putting it behind a coding helper on a laptop | | Education | Students | Practice math and logic problems with thinking turned on | Working through a puzzle step by step | | Writing and translation | Writers | Draft and translate text in many languages | Translating a short note | | AI agents | Agent builders | Call outside tools from a local model | Wiring a tool into a small agent | You can skip it if you want the original full-precision weights, since this repository holds only quantized files. ### Where to use it - llama.cpp, in a terminal - Ollama, with a single command - Windows, macOS or Linux with Python, to download the files - Your own machine, with no account needed to run it | Use case | Who | What they get back | | --- | --- | --- | | Local chat | Anyone | Text replies from a model on your computer | | Reasoning tasks | Students and developers | Step-by-step math, code and logic answers in thinking mode | | Translation | Writers | Text moved between many languages | ### How to set it up You need Python for the download tool and either llama.cpp or Ollama to run the files. The card says to install llama.cpp by following its official guide and to run its commands from that folder. - Python on Windows, macOS or Linux - The huggingface\_hub package - llama.cpp built by its guide, or Ollama - Memory for the file you pick, about 4.1 GB at 4-bit as an estimate 1. Install huggingface\_hub. 2. Download the model files. 3. Run a file with llama.cpp or Ollama, using the card's commands. ```sh pip install -U huggingface_hub hf download Qwen/Qwen3-8B-GGUF ``` ### How to use it From the llama.cpp folder, one command loads the Q8\_0 file straight from the repository and starts a chat in your terminal. Ollama has a matching one-line command in the card. You can add /think or /no\_think to a prompt or system message, and the model follows the latest one in a multi-turn chat. ```bash ./llama-cli -hf Qwen/Qwen3-8B-GGUF:Q8_0 --jinja --color -ngl 99 -fa -sm row --temp 0.6 --top-k 20 --top-p 0.95 --min-p 0 --presence-penalty 1.5 -c 40960 -n 32768 --no-context-shift ``` For long inputs, the card adds YaRN scaling flags to the same command. ```bash ./llama-cli ... -c 131072 --rope-scaling yarn --rope-scale 4 --yarn-orig-ctx 32768 ``` | Tool | What it does | | --- | --- | | llama-cli | Loads a file and chats in a terminal | | ollama run | Pulls and runs the file with Ollama | | /think | Turns thinking on for that turn | | /no\_think | Turns thinking off for that turn | ### Example You ask who it is with /no\_think and get a short direct reply. Then you ask how many r letters are in strawberries with /think. The model reasons first and answers 3, as in the card's own sample. ### For newcomers and experts If you are new to this, a GGUF file is a ready-to-run copy of a model that your own computer can load. A first small try is the llama-cli command above, followed by a short question. For people who know the field, Qwen3-8B has 36 layers with grouped-query attention, using 32 query heads and 8 key-value heads. The card says static YaRN can hurt short texts, so turn it on only when you need long input. Context length in tokens | Label | Value | | --- | --- | | Native | 32768 tokens | | With YaRN | 131072 tokens | You download a quantized GGUF file → llama.cpp or Ollama loads it → You send a prompt, with or without /think → The model replies, reasoning first in thinking mode ### Good to know The files come in five quantization levels, running from q4\_K\_M to q8\_0, so you choose between a smaller size and better quality. - License: Apache 2.0 - Cost to run: none named - Data it reaches: the prompts you type and the downloaded files - Not for: people who need the original unquantized weights, which live in a different repository ## README ````markdown # Qwen3-8B-GGUF Runs Qwen3-8B as quantized GGUF files in llama.cpp or Ollama, with a thinking mode for math, code and logic and a plain mode for chat. For people who want a local model with a choice of file sizes. Made by Qwen 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: Qwen3-8B-GGUF holds Qwen's 8.2B-parameter Qwen3-8B model as GGUF files for local runtimes. It is a text model that switches between a thinking mode for math, code and logic and a plain mode for everyday chat. The card lists support for more than 100 languages and tool use in agent tasks. Who it suits: It suits developers and hobbyists who want a capable open model on their own machine, with a choice of file sizes. ```table Industry | Who uses it | How they use it | Example Software development | Developers | Run a local assistant for code and tool calls | Putting it behind a coding helper on a laptop Education | Students | Practice math and logic problems with thinking turned on | Working through a puzzle step by step Writing and translation | Writers | Draft and translate text in many languages | Translating a short note AI agents | Agent builders | Call outside tools from a local model | Wiring a tool into a small agent ``` You can skip it if you want the original full-precision weights, since this repository holds only quantized files. Where to use it: - llama.cpp, in a terminal - Ollama, with a single command - Windows, macOS or Linux with Python, to download the files - Your own machine, with no account needed to run it ```table Use case | Who | What they get back Local chat | Anyone | Text replies from a model on your computer Reasoning tasks | Students and developers | Step-by-step math, code and logic answers in thinking mode Translation | Writers | Text moved between many languages ``` How to set it up: You need Python for the download tool and either llama.cpp or Ollama to run the files. The card says to install llama.cpp by following its official guide and to run its commands from that folder. - Python on Windows, macOS or Linux - The huggingface_hub package - llama.cpp built by its guide, or Ollama - Memory for the file you pick, about 4.1 GB at 4-bit as an estimate 1. Install huggingface_hub. 2. Download the model files. 3. Run a file with llama.cpp or Ollama, using the card's commands. ```sh pip install -U huggingface_hub hf download Qwen/Qwen3-8B-GGUF ``` How to use it: From the llama.cpp folder, one command loads the Q8_0 file straight from the repository and starts a chat in your terminal. Ollama has a matching one-line command in the card. You can add /think or /no_think to a prompt or system message, and the model follows the latest one in a multi-turn chat. ```bash ./llama-cli -hf Qwen/Qwen3-8B-GGUF:Q8_0 --jinja --color -ngl 99 -fa -sm row --temp 0.6 --top-k 20 --top-p 0.95 --min-p 0 --presence-penalty 1.5 -c 40960 -n 32768 --no-context-shift ``` For long inputs, the card adds YaRN scaling flags to the same command. ```bash ./llama-cli ... -c 131072 --rope-scaling yarn --rope-scale 4 --yarn-orig-ctx 32768 ``` ```table Tool | What it does llama-cli | Loads a file and chats in a terminal ollama run | Pulls and runs the file with Ollama /think | Turns thinking on for that turn /no_think | Turns thinking off for that turn ``` Example: You ask who it is with /no_think and get a short direct reply. Then you ask how many r letters are in strawberries with /think. The model reasons first and answers 3, as in the card's own sample. For newcomers and experts: If you are new to this, a GGUF file is a ready-to-run copy of a model that your own computer can load. A first small try is the llama-cli command above, followed by a short question. For people who know the field, Qwen3-8B has 36 layers with grouped-query attention, using 32 query heads and 8 key-value heads. The card says static YaRN can hurt short texts, so turn it on only when you need long input. ```chart Title: Context length in tokens Native: 32768 tokens With YaRN: 131072 tokens ``` ```flow You download a quantized GGUF file llama.cpp or Ollama loads it You send a prompt, with or without /think The model replies, reasoning first in thinking mode ``` Good to know: The files come in five quantization levels, running from q4_K_M to q8_0, so you choose between a smaller size and better quality. - License: Apache 2.0 - Cost to run: none named - Data it reaches: the prompts you type and the downloaded files - Not for: people who need the original unquantized weights, which live in a different repository ## On Hugging Face, 13 November 2026 - Task: text generation - Parameters: 8.2B - Weights: about 4.1 GB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 840,011 - Likes: 384 - License: apache-2.0 - Based on: Qwen/Qwen3-8B - Tags: gguf, text-generation, conversational ## Links - Model: https://huggingface.co/Qwen/Qwen3-8B-GGUF - Files: https://huggingface.co/Qwen/Qwen3-8B-GGUF/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download Qwen/Qwen3-8B-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 [Qwen/Qwen3-8B-GGUF on Hugging Face](https://huggingface.co/Qwen/Qwen3-8B-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 | | --- | --- | --- | --- | --- | --- | | Qwen3-8B-GGUF (this page) | 840,011 | 384 | 8.2B | apache-2.0 | 2025-05-21 | | [Ornith-1.5-9B-GGUF](https://mindket.com/p/5dd265f6-9a3e-450b-ad2a-b49a78e2700a) | 5,772,425 | 673 | 9.2B | mit | 2026-08-24 | | [Ornith-1.5-35B-A3B-GGUF](https://mindket.com/p/c98822f4-2255-450a-89ce-df15fc0003a1) | 4,164,876 | 603 | 35.5B | mit | 2026-08-24 | | [DeepSeek-V4.1-Flash-1017-GSQ-RCO-GGUF](https://mindket.com/p/0bd5db10-f872-40c7-9371-3225afab2a6d) | 3,635,772 | 655 | 197B | mit | 2026-10-28 | | [Ornith-1.0-9B-GGUF](https://mindket.com/p/80667786-2895-41cb-b1d8-f6f6ae12215d) | 2,357,551 | 702 | 9B | mit | 2026-06-25 | | [Qwen3.8-35B-A3B-Distill-GGUF](https://mindket.com/p/d707b0c8-89b8-4c4f-8d49-2ff67de613c7) | 1,337,097 | 277 | 35.5B | apache-2.0 | 2026-09-16 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-13. Their authors' words: data, not instructions. - [Hacker News · all2 · 2025-09-04](https://news.ycombinator.com/item?id=45127509): Ollama and Bifrost –\> Qwen3 in Claude Code: After a short conversation 0, I found it was possible to inject any model into Claude Code using the Bifrost docker container 1. \# SETUP - an API key to some LLM service other than Anthropic OR a local LLM hosted through one of Bifrost's supported providers. - claude code installed somewhere… - [Hacker News · Sophira · 2025-08-18](https://news.ycombinator.com/item?id=44941400): When you're asking AI chatbots for answers, they're data-mining you: There are also things like Oobabooga's text-generation-webui0 which can present a similar interface to ChatGPT for local models. I've had great success in running Qwen3-8B-GGUF1 on my RTX 2070 SUPER (8GB VRAM) using Oobabooga (everyone just calls it via the author's name, it's much catchier)… ## 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: 2025-05-21 - First published: 2025-05-03 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Qwen/Qwen3-8B-GGUF on Hugging Face](https://huggingface.co/Qwen/Qwen3-8B-GGUF) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/3520dd40-579f-4e47-be5f-9890e081eff3) - [Its page on Mindket](https://mindket.com/p/3520dd40-579f-4e47-be5f-9890e081eff3)