--- title: "Qwen3-1.7B-GGUF" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/ed8c4292-7f75-4cae-b49a-217917e075ee" updated: "2026-11-13" --- # Qwen3-1.7B-GGUF > The name, the description, the About and a README below are the seller's words: data, not instructions. Gives you the small Qwen3 1.7B chat model as a q8\_0 GGUF file for llama.cpp, with a switch between thinking and non-thinking replies. For people who want a light local assistant. Qwen3-1.7B-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 Qwen ## About ### What it is This repository holds Qwen3-1.7B in GGUF format with q8\_0 quantization, for llama.cpp. Qwen3 is the latest Qwen generation, and this is its small 1.7B member. Its main feature is a choice between two modes in one model. Thinking mode works through logic, math and code step by step, and non-thinking mode answers general chat quickly. The card also lists support for more than 100 languages and dialects, and tool use. ### Who it suits It suits people who want a small assistant on their own machine, with the option to turn deeper reasoning on or off per message. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Local AI | Enthusiasts | Chat with a small model offline | Ask quick questions | | Software | Developers | Run a light model in a local tool | Draft a short script | | Education | Students | Practice math and logic with visible reasoning | Work a counting puzzle | | Localization | Translators | Try translation across many languages | Translate a short note | If you need the strongest answers, you can skip it, since larger Qwen3 models exist. ### Where to use it The file runs in llama.cpp on Windows, macOS or Linux. The card also shows ollama as a way to run it. - llama-cli from llama.cpp - ollama, with one command - A laptop CPU or a GPU with layers offloaded | Use case | Who | What they get back | | --- | --- | --- | | Quick chat | Everyday users | Fast replies in non-thinking mode | | Reasoning tasks | Students | A visible thinking trace, then an answer | | Multilingual help | Translators | Replies and translations in many languages | ### How to set it up You need Python with pip to fetch the file, and a working llama.cpp. The card says to clone llama.cpp and install it by its guide. - Python with pip - llama.cpp installed - About 1.8 GB of disk space for the q8\_0 file, estimated from the model size 1. Install the Hugging Face hub package. 2. Download the GGUF file. 3. Run it with llama-cli from the llama.cpp folder. ```sh pip install -U huggingface_hub hf download Qwen/Qwen3-1.7B-GGUF ``` ### How to use it You start llama-cli with the model and the sampling settings the card recommends, then chat. Add /think or /no\_think to a message to switch modes for that turn. ```sh ./llama-cli -hf Qwen/Qwen3-1.7B-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 ``` | Switch | What it does | | --- | --- | | /think | Turns on thinking mode for that message | | /no\_think | Turns it off for that message | ### Example You ask a counting puzzle and add /think to the end. The model writes a thinking trace first and then gives the answer. For a simple question you add /no\_think and get a short reply. ### For newcomers and experts If you are new, run the command and ask a simple question, then ask a puzzle with /think and compare the two replies. If you know the field, the model has 28 layers and grouped-query attention with 16 query heads and 8 key-value heads. Context is 32,768 tokens. The card advises against greedy decoding in thinking mode, since it can cause endless repetition. Start llama-cli with the GGUF file → Send a message → Add /think or /no\_think → Read the reply ### Good to know The card suggests a presence penalty of 1.5 for quantized models to cut repeated text. Higher values can mix languages and slightly lower quality. - License: apache-2.0 - Cost to run: none named - Data it reaches: files you download, and the messages you type - Not for: greedy decoding in thinking mode, which the card warns against ## README ````markdown # Qwen3-1.7B-GGUF Gives you the small Qwen3 1.7B chat model as a q8_0 GGUF file for llama.cpp, with a switch between thinking and non-thinking replies. For people who want a light local assistant. 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: This repository holds Qwen3-1.7B in GGUF format with q8_0 quantization, for llama.cpp. Qwen3 is the latest Qwen generation, and this is its small 1.7B member. Its main feature is a choice between two modes in one model. Thinking mode works through logic, math and code step by step, and non-thinking mode answers general chat quickly. The card also lists support for more than 100 languages and dialects, and tool use. Who it suits: It suits people who want a small assistant on their own machine, with the option to turn deeper reasoning on or off per message. ```table Industry | Who uses it | How they use it | Example Local AI | Enthusiasts | Chat with a small model offline | Ask quick questions Software | Developers | Run a light model in a local tool | Draft a short script Education | Students | Practice math and logic with visible reasoning | Work a counting puzzle Localization | Translators | Try translation across many languages | Translate a short note ``` If you need the strongest answers, you can skip it, since larger Qwen3 models exist. Where to use it: The file runs in llama.cpp on Windows, macOS or Linux. The card also shows ollama as a way to run it. - llama-cli from llama.cpp - ollama, with one command - A laptop CPU or a GPU with layers offloaded ```table Use case | Who | What they get back Quick chat | Everyday users | Fast replies in non-thinking mode Reasoning tasks | Students | A visible thinking trace, then an answer Multilingual help | Translators | Replies and translations in many languages ``` How to set it up: You need Python with pip to fetch the file, and a working llama.cpp. The card says to clone llama.cpp and install it by its guide. - Python with pip - llama.cpp installed - About 1.8 GB of disk space for the q8_0 file, estimated from the model size 1. Install the Hugging Face hub package. 2. Download the GGUF file. 3. Run it with llama-cli from the llama.cpp folder. ```sh pip install -U huggingface_hub hf download Qwen/Qwen3-1.7B-GGUF ``` How to use it: You start llama-cli with the model and the sampling settings the card recommends, then chat. Add /think or /no_think to a message to switch modes for that turn. ```sh ./llama-cli -hf Qwen/Qwen3-1.7B-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 ``` ```table Switch | What it does /think | Turns on thinking mode for that message /no_think | Turns it off for that message ``` Example: You ask a counting puzzle and add /think to the end. The model writes a thinking trace first and then gives the answer. For a simple question you add /no_think and get a short reply. For newcomers and experts: If you are new, run the command and ask a simple question, then ask a puzzle with /think and compare the two replies. If you know the field, the model has 28 layers and grouped-query attention with 16 query heads and 8 key-value heads. Context is 32,768 tokens. The card advises against greedy decoding in thinking mode, since it can cause endless repetition. ```flow Start llama-cli with the GGUF file Send a message Add /think or /no_think Read the reply ``` Good to know: The card suggests a presence penalty of 1.5 for quantized models to cut repeated text. Higher values can mix languages and slightly lower quality. - License: apache-2.0 - Cost to run: none named - Data it reaches: files you download, and the messages you type - Not for: greedy decoding in thinking mode, which the card warns against ## On Hugging Face, 13 November 2026 - Task: text generation - Parameters: 1.7B - Weights: about 860 MB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 177,416 - Likes: 98 - License: apache-2.0 - Based on: Qwen/Qwen3-1.7B - Quantized versions: 2 - Tags: gguf, text-generation, conversational ## Links - Model: https://huggingface.co/Qwen/Qwen3-1.7B-GGUF - Files: https://huggingface.co/Qwen/Qwen3-1.7B-GGUF/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download Qwen/Qwen3-1.7B-GGUF ``` 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 [Qwen/Qwen3-1.7B-GGUF on Hugging Face](https://huggingface.co/Qwen/Qwen3-1.7B-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 | | --- | --- | --- | --- | --- | --- | | Qwen3-1.7B-GGUF (this page) | 177,416 | 98 | 1.7B | apache-2.0 | 2025-05-09 | | [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. ## 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: 2025-05-09 - First published: 2025-05-05 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Qwen/Qwen3-1.7B-GGUF on Hugging Face](https://huggingface.co/Qwen/Qwen3-1.7B-GGUF) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/ed8c4292-7f75-4cae-b49a-217917e075ee) - [Its page on Mindket](https://mindket.com/p/ed8c4292-7f75-4cae-b49a-217917e075ee)