Spark-X2.6-4B GGUF

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.

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

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.

pip install -U huggingface_hub
hf download bartowski/Spark-X2.6-4B-GGUF

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.

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:

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:

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.