--- title: "Spark-X2.6-4B GGUF" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/9f20961f-2fc8-4db6-9a24-95a407628b98" updated: "2026-11-13" --- # Spark-X2.6-4B GGUF > The name, the description, the About and a README below are the seller's words: data, not instructions. Small English and Chinese chat model as GGUF files from full bf16 down to about 2.4 GB, for llama.cpp, with a low or high thinking setting. For developers who want a compact local assistant. Spark-X2.6-4B 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 bartowski ## About ### What it is This repository holds GGUF quantizations of Spark-X2.6-4B, a 4.1B text model from XHToken, made by bartowski with llama.cpp and an importance matrix. The files range from the 8.23 GB bf16 copy down to about 2.4 GB. The model takes text only and speaks English and Chinese. ### Who it suits Developers and hobbyists who want a small local chat model for coding help, agent experiments or everyday questions, in English or Chinese. Who uses it, and how | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Developers | Run a compact assistant on a laptop | Ask for a small helper function and read the reasoning | | AI agents | Agent builders | Use the card's tool-definition prompt format | Describe a stock price function and let the model call it | | Local AI | Hobbyists | Pick a quant that fits modest memory | Run the Q4\_K\_M file the card suggests for most people | | Bilingual use | English and Chinese users | Chat in either language | Ask a question in Chinese and read the reply | Skip it if you need images, because the card lists text input only. ### Where to use it - llama.cpp, or an app built on it that opens GGUF files - Windows, macOS or Linux for downloading the files, with Python - Apple silicon, where the card notes the Q4\_1 file runs efficiently | Use case | Who | What they get back | | --- | --- | --- | | Local chat | Individuals | Text replies from a small model on your computer | | Tool calling | Agent builders | Function calls in the card's prompt format | | Quick drafts | Writers | Short drafts and rewrites | ### How to set it up You need Python and pip to download, plus llama.cpp or a similar runner. The card made its quants with llama.cpp release b11716. - Python and pip - llama.cpp or an app built on it - Disk space for the quant you choose, from about 2.4 GB 1. Install the Hugging Face hub library. 2. Download the repository, or just one quant file. 3. Load the file in your runner. ```sh pip install -U huggingface_hub hf download bartowski/Spark-X2.6-4B-GGUF ``` Some of the quants | Quant | Size | When to pick it | | --- | --- | --- | | bf16 | 8.23 GB | The full-weight file, largest of all | | Q8\_0 | 4.38 GB | Top quality among the quants, more than most people need | | Q6\_K | 3.61 GB | Near-perfect quality, which the card recommends | | Q5\_K\_M | 3.16 GB | High quality, which the card recommends | | Q4\_K\_L | 2.81 GB | Q4\_K with sensitive weights kept at higher precision | | Q4\_1 | 2.64 GB | An older format that suits Apple silicon | | Q4\_K\_M | 2.62 GB | The card's default pick for most uses | | Q4\_K\_S | 2.46 GB | A little lower quality for more savings | | Q4\_0 | 2.41 GB | An older format kept for compatibility | ### How to use it Load a quant in llama.cpp and chat using the card's prompt format. The system part sets a thinking effort of low or high, which controls how much the model reasons before it answers. ### Example You load the Q4\_K\_M file, set the thinking effort to high, and ask, "Explain what a hash map is in two sentences." The model reasons first, then replies with a short explanation. ### For newcomers and experts If you are new, take Q4\_K\_M, which the card suggests as the default, and start with a short question. Raise or lower the thinking effort to see how the answers change. For people in the field, the files use an importance matrix and the card lists no speculative decoding. The prompt format wraps the system, user and assistant turns in special markers and opens a thinking block for the reply. A variant adds tool definitions in the system part. Pick a quant that fits your memory → Load it in llama.cpp → Set the thinking effort → Send a prompt in the card's format ### Good to know File size in GB for some quants | Label | Value | | --- | --- | | bf16 | 8.23 GB | | Q8\_0 | 4.38 GB | | Q6\_K | 3.61 GB | | Q5\_K\_M | 3.16 GB | | Q4\_K\_M | 2.62 GB | | Q4\_K\_S | 2.46 GB | | Q4\_0 | 2.41 GB | - License: Apache 2.0 - Cost to run: none named, you use your own computer - Data it reaches: it downloads files from Hugging Face, and the card names nothing else it touches - Not for: images, since only text input is listed - The card lists more quants than this page shows ## README ````markdown # Spark-X2.6-4B GGUF Small English and Chinese chat model as GGUF files from full bf16 down to about 2.4 GB, for llama.cpp, with a low or high thinking setting. For developers who want a compact local assistant. Made by bartowski 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 GGUF quantizations of Spark-X2.6-4B, a 4.1B text model from XHToken, made by bartowski with llama.cpp and an importance matrix. The files range from the 8.23 GB bf16 copy down to about 2.4 GB. The model takes text only and speaks English and Chinese. Who it suits: Developers and hobbyists who want a small local chat model for coding help, agent experiments or everyday questions, in English or Chinese. ```table Title: Who uses it, and how Industry | Who uses it | How they use it | Example Software | Developers | Run a compact assistant on a laptop | Ask for a small helper function and read the reasoning AI agents | Agent builders | Use the card's tool-definition prompt format | Describe a stock price function and let the model call it Local AI | Hobbyists | Pick a quant that fits modest memory | Run the Q4_K_M file the card suggests for most people Bilingual use | English and Chinese users | Chat in either language | Ask a question in Chinese and read the reply ``` Skip it if you need images, because the card lists text input only. Where to use it: - llama.cpp, or an app built on it that opens GGUF files - Windows, macOS or Linux for downloading the files, with Python - Apple silicon, where the card notes the Q4_1 file runs efficiently ```table Use case | Who | What they get back Local chat | Individuals | Text replies from a small model on your computer Tool calling | Agent builders | Function calls in the card's prompt format Quick drafts | Writers | Short drafts and rewrites ``` How to set it up: You need Python and pip to download, plus llama.cpp or a similar runner. The card made its quants with llama.cpp release b11716. - Python and pip - llama.cpp or an app built on it - Disk space for the quant you choose, from about 2.4 GB 1. Install the Hugging Face hub library. 2. Download the repository, or just one quant file. 3. Load the file in your runner. ```sh pip install -U huggingface_hub hf download bartowski/Spark-X2.6-4B-GGUF ``` ```table Title: Some of the quants Quant | Size | When to pick it bf16 | 8.23 GB | The full-weight file, largest of all Q8_0 | 4.38 GB | Top quality among the quants, more than most people need Q6_K | 3.61 GB | Near-perfect quality, which the card recommends Q5_K_M | 3.16 GB | High quality, which the card recommends Q4_K_L | 2.81 GB | Q4_K with sensitive weights kept at higher precision Q4_1 | 2.64 GB | An older format that suits Apple silicon Q4_K_M | 2.62 GB | The card's default pick for most uses Q4_K_S | 2.46 GB | A little lower quality for more savings Q4_0 | 2.41 GB | An older format kept for compatibility ``` How to use it: Load a quant in llama.cpp and chat using the card's prompt format. The system part sets a thinking effort of low or high, which controls how much the model reasons before it answers. Example: You load the Q4_K_M file, set the thinking effort to high, and ask, "Explain what a hash map is in two sentences." The model reasons first, then replies with a short explanation. For newcomers and experts: If you are new, take Q4_K_M, which the card suggests as the default, and start with a short question. Raise or lower the thinking effort to see how the answers change. For people in the field, the files use an importance matrix and the card lists no speculative decoding. The prompt format wraps the system, user and assistant turns in special markers and opens a thinking block for the reply. A variant adds tool definitions in the system part. ```flow Pick a quant that fits your memory Load it in llama.cpp Set the thinking effort Send a prompt in the card's format ``` Good to know: ```chart Title: File size in GB for some quants bf16: 8.23 GB Q8_0: 4.38 GB Q6_K: 3.61 GB Q5_K_M: 3.16 GB Q4_K_M: 2.62 GB Q4_K_S: 2.46 GB Q4_0: 2.41 GB ``` - License: Apache 2.0 - Cost to run: none named, you use your own computer - Data it reaches: it downloads files from Hugging Face, and the card names nothing else it touches - Not for: images, since only text input is listed - The card lists more quants than this page shows ## On Hugging Face, 13 November 2026 - Task: text generation - Parameters: 4.1B - Weights: about 2.1 GB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 27,090 - Likes: 20 - License: apache-2.0 - Languages: en, zh - Based on: XHToken/Spark-X2.6-4B - Fine-tunes: 1 - Tags: gguf, sparkx2_5, text-generation, conversational ## Links - Model: https://huggingface.co/bartowski/Spark-X2.6-4B-GGUF - Files: https://huggingface.co/bartowski/Spark-X2.6-4B-GGUF/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download bartowski/Spark-X2.6-4B-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 [bartowski/Spark-X2.6-4B-GGUF on Hugging Face](https://huggingface.co/bartowski/Spark-X2.6-4B-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 | | --- | --- | --- | --- | --- | --- | | Spark-X2.6-4B GGUF (this page) | 27,090 | 20 | 4.1B | apache-2.0 | 2026-10-20 | | [Spark-X2.6-4B-GGUF](https://mindket.com/p/31f3aff1-a9fb-4808-ad4b-6907e965fb45) | 687,668 | 310 | 4.4B | apache-2.0 | 2026-11-06 | | [Spark-X2.6-1.7B-GGUF](https://mindket.com/p/a5d36fe9-d793-4463-861f-ca584301af0d) | 26,744 | 50 | 2B | apache-2.0 | 2026-11-06 | | [Spark-X2.6-4B](https://mindket.com/p/1f30e23c-ac63-4f34-b227-130e4306e0f2) | 28,117 | 1,041 | 4.1B | apache-2.0 | 2026-11-06 | | [Spark-X2.5-4B](https://mindket.com/p/36f36232-524c-4161-bacd-b9b5c290fea4) | 8,697 | 1,442 | 4.1B | apache-2.0 | 2026-09-15 | | [Spark-X2.6-1.7B](https://mindket.com/p/427232ce-5988-41f7-985c-029c680c8947) | 5,095 | 84 | 1.7B | apache-2.0 | 2026-11-06 | 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: 2026-10-20 - First published: 2026-10-20 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open bartowski/Spark-X2.6-4B-GGUF on Hugging Face](https://huggingface.co/bartowski/Spark-X2.6-4B-GGUF) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/9f20961f-2fc8-4db6-9a24-95a407628b98) - [Its page on Mindket](https://mindket.com/p/9f20961f-2fc8-4db6-9a24-95a407628b98)