--- title: "Qwen3-0.6B-GGUF" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/f417eff2-dac2-49a0-97f8-d78f731ace1e" updated: "2026-11-13" --- # Qwen3-0.6B-GGUF > The name, the description, the About and a README below are the seller's words: data, not instructions. A small 0.6B chat model in GGUF format that runs locally in llama.cpp or ollama and can switch between thinking and plain replies. Suits people with modest hardware and developers testing local models. Qwen3-0.6B-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 Qwen3-0.6B-GGUF is a small chat model from Qwen in GGUF format, so it runs locally in llama.cpp or ollama. It has about 0.6 billion parameters and the q8\_0 quantization. A single model can switch between a thinking mode for hard problems and a plain mode for quick replies. ### Who it suits People who want a language model that runs on modest hardware, and developers who need a small local model for tests, prototypes or tools. Anyone curious about thinking and non-thinking replies can try both in one chat. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | App developers | Run a small local model inside a prototype | Test a chat feature without a hosted service | | Education | Students and teachers | Experiment with an open language model on a laptop | Compare thinking and non-thinking answers | | Research | Hobbyists and researchers | Try sampling settings on a compact model | Check how presence penalty changes repetition | | Developer tools | Tool builders | Wire a small model into local tools | Call it through ollama in a script | Anyone who needs top answer quality on hard tasks can skip it, since this is the smallest size in the Qwen3 family. ### Where to use it - llama.cpp on Windows, macOS or Linux, through its llama-cli tool - ollama, which can pull the model with one command - Any other app that reads GGUF files | Use case | Who | What they get back | | --- | --- | --- | | Quick local chat | Anyone with a laptop | Short replies without calling an online service | | Reasoning on request | Developers and students | Step by step thinking when you switch the mode on | | Translation and instruction following | Multilingual users | Replies in many languages, as the card describes it | ### How to set it up - Python with pip, if you want the files on disk - llama.cpp installed by following its official guide, or ollama - Little memory, since the 4-bit weights are an estimated 298 MB 1. Install the Hugging Face hub package and download the files. 2. Or skip the download and run the model straight from llama.cpp or ollama with the commands below. ```sh pip install -U huggingface_hub hf download Qwen/Qwen3-0.6B-GGUF ``` ### How to use it Run the model in llama.cpp from the llama.cpp folder, or in ollama with one command. Then chat in the terminal. Add /think or /no\_think to a message to switch the thinking mode for that turn. ```sh ./llama-cli -hf Qwen/Qwen3-0.6B-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 ``` ```sh ollama run hf.co/Qwen/Qwen3-0.6B-GGUF:Q8_0 ``` | Tool | What it does | | --- | --- | | llama-cli | Runs the GGUF model in the terminal with the sampling settings you pass | | ollama run | Pulls the model and starts a chat with one command | | /think | Turns thinking mode on for the current and later turns | | /no\_think | Turns thinking mode off for quick replies | Suggested sampling settings | Setting | Thinking mode | Non-thinking mode | | --- | --- | --- | | Temperature | 0.6 | 0.7 | | TopP | 0.95 | 0.8 | | TopK | 20 | 20 | | MinP | 0 | 0 | | PresencePenalty | 1.5 | 1.5 | ### Example In a chat you type "How many 'r's are in 'strawberries'? /think". The model reasons through the word letter by letter first, then answers that it contains 3 instances of the letter r. Ending a message with /no\_think skips that reasoning. ### For newcomers and experts If you are new, run the ollama command, say hello, then ask a question with /think and again with /no\_think to see the difference. The first run downloads the model, which is small. Experts get a causal language model with 28 layers, 16 query heads and 8 key-value heads (GQA), about 0.44B non-embedding parameters and a 32,768 token context. The card advises against greedy decoding in thinking mode, and a presence penalty near 1.5 for quantized copies to curb repetition. Higher values can mix languages. You start llama-cli or ollama → The GGUF model loads locally → You chat, adding /think or /no\_think → It replies, thinking first when asked ### Good to know - Quantization: this repository holds the q8\_0 version - Presence penalty: values between 0 and 2 are allowed, and a high value can mix languages or lower quality slightly - License: Apache 2.0 - Cost to run: none named, no API key or account - Data it reaches: it downloads model files from Hugging Face, then answers on your own machine - Not for: the source names no forbidden uses, and a model this small is a weak fit for hard tasks ## README ````markdown # Qwen3-0.6B-GGUF A small 0.6B chat model in GGUF format that runs locally in llama.cpp or ollama and can switch between thinking and plain replies. Suits people with modest hardware and developers testing local models. 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: Qwen3-0.6B-GGUF is a small chat model from Qwen in GGUF format, so it runs locally in llama.cpp or ollama. It has about 0.6 billion parameters and the q8_0 quantization. A single model can switch between a thinking mode for hard problems and a plain mode for quick replies. Who it suits: People who want a language model that runs on modest hardware, and developers who need a small local model for tests, prototypes or tools. Anyone curious about thinking and non-thinking replies can try both in one chat. ```table Industry | Who uses it | How they use it | Example Software | App developers | Run a small local model inside a prototype | Test a chat feature without a hosted service Education | Students and teachers | Experiment with an open language model on a laptop | Compare thinking and non-thinking answers Research | Hobbyists and researchers | Try sampling settings on a compact model | Check how presence penalty changes repetition Developer tools | Tool builders | Wire a small model into local tools | Call it through ollama in a script ``` Anyone who needs top answer quality on hard tasks can skip it, since this is the smallest size in the Qwen3 family. Where to use it: - llama.cpp on Windows, macOS or Linux, through its llama-cli tool - ollama, which can pull the model with one command - Any other app that reads GGUF files ```table Use case | Who | What they get back Quick local chat | Anyone with a laptop | Short replies without calling an online service Reasoning on request | Developers and students | Step by step thinking when you switch the mode on Translation and instruction following | Multilingual users | Replies in many languages, as the card describes it ``` How to set it up: - Python with pip, if you want the files on disk - llama.cpp installed by following its official guide, or ollama - Little memory, since the 4-bit weights are an estimated 298 MB 1. Install the Hugging Face hub package and download the files. 2. Or skip the download and run the model straight from llama.cpp or ollama with the commands below. ```sh pip install -U huggingface_hub hf download Qwen/Qwen3-0.6B-GGUF ``` How to use it: Run the model in llama.cpp from the llama.cpp folder, or in ollama with one command. Then chat in the terminal. Add /think or /no_think to a message to switch the thinking mode for that turn. ```sh ./llama-cli -hf Qwen/Qwen3-0.6B-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 ``` ```sh ollama run hf.co/Qwen/Qwen3-0.6B-GGUF:Q8_0 ``` ```table Tool | What it does llama-cli | Runs the GGUF model in the terminal with the sampling settings you pass ollama run | Pulls the model and starts a chat with one command /think | Turns thinking mode on for the current and later turns /no_think | Turns thinking mode off for quick replies ``` ```table Title: Suggested sampling settings Setting | Thinking mode | Non-thinking mode Temperature | 0.6 | 0.7 TopP | 0.95 | 0.8 TopK | 20 | 20 MinP | 0 | 0 PresencePenalty | 1.5 | 1.5 ``` Example: In a chat you type "How many 'r's are in 'strawberries'? /think". The model reasons through the word letter by letter first, then answers that it contains 3 instances of the letter r. Ending a message with /no_think skips that reasoning. For newcomers and experts: If you are new, run the ollama command, say hello, then ask a question with /think and again with /no_think to see the difference. The first run downloads the model, which is small. Experts get a causal language model with 28 layers, 16 query heads and 8 key-value heads (GQA), about 0.44B non-embedding parameters and a 32,768 token context. The card advises against greedy decoding in thinking mode, and a presence penalty near 1.5 for quantized copies to curb repetition. Higher values can mix languages. ```flow You start llama-cli or ollama The GGUF model loads locally You chat, adding /think or /no_think It replies, thinking first when asked ``` Good to know: - Quantization: this repository holds the q8_0 version - Presence penalty: values between 0 and 2 are allowed, and a high value can mix languages or lower quality slightly - License: Apache 2.0 - Cost to run: none named, no API key or account - Data it reaches: it downloads model files from Hugging Face, then answers on your own machine - Not for: the source names no forbidden uses, and a model this small is a weak fit for hard tasks ## On Hugging Face, 13 November 2026 - Task: text generation - Parameters: 596M - Weights: about 298 MB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 215,881 - Likes: 113 - License: apache-2.0 - Based on: Qwen/Qwen3-0.6B - Quantized versions: 1 - Tags: gguf, text-generation, conversational ## Links - Model: https://huggingface.co/Qwen/Qwen3-0.6B-GGUF - Files: https://huggingface.co/Qwen/Qwen3-0.6B-GGUF/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download Qwen/Qwen3-0.6B-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/Qwen3-0.6B-GGUF on Hugging Face](https://huggingface.co/Qwen/Qwen3-0.6B-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 | | --- | --- | --- | --- | --- | --- | | Qwen3-0.6B-GGUF (this page) | 215,881 | 113 | 596M | 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. ## 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 · cuuupid · 2025-04-28](https://news.ycombinator.com/item?id=43824749): Qwen3 0.6B now on HuggingFace (quantized) ## 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/Qwen3-0.6B-GGUF on Hugging Face](https://huggingface.co/Qwen/Qwen3-0.6B-GGUF) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/f417eff2-dac2-49a0-97f8-d78f731ace1e) - [Its page on Mindket](https://mindket.com/p/f417eff2-dac2-49a0-97f8-d78f731ace1e)