Spark-X2.6-4B-GGUF

Spark-X2.6-4B-GGUF

A compact 4B language model in GGUF form for on-device use, tuned for coding, agents and long context, with three thinking levels from none to high. Works in English and Chinese.

Made by XHToken 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: Spark-X2.6-4B-GGUF holds GGUF files of Spark-X2.6-4B, a compact general-purpose language model from XHToken for running on your own device. Hugging Face lists it for English and Chinese.

The model keeps the architecture of Spark-X2.5-4B. The authors say the gains come from better post-training, mainly in coding, agent work, long context, multilingual use and reasoning.

Who it suits: Developers who want a small local model that handles tool use, planning and code, and people who build apps that must run on a device with limited resources.

Industry | Who uses it | How they use it | Example
Software | Developers of on-device agents | Run a small model that plans and calls tools | A local assistant that works through a coding task
Product teams | Builders of apps with limited resources | Tune thinking to balance quality and speed | Use low effort for quick replies
Research | People comparing small models | Test a 4B model against larger ones | Check it against a 9B model

Skip it if you need the largest models, since this one is built for small devices.

Where to use it:

• Your own computer, using a local runner that reads GGUF files
• Windows, macOS or Linux with Python, to download the files
• Python programs, using the Transformers route the card shows for the original model

Use case | Who | What they get back
Agentic workflows | Agent builders | Multi-step plans and tool calls from a small model
Coding help | Developers | Code and explanations on local hardware
Long-context tasks | Researchers | Answers over longer inputs

How to set it up:

• Python and pip to run the download commands
• A local runner that opens GGUF files
• Transformers 4.57.1, if you follow the card Python route for the original model

1. Install the Hugging Face tools.
2. Download the GGUF files from this repository.
3. Open the file in your runner.

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

pip install transformers==4.57.1

How to use it: Chat with the model through your runner and pick one of three thinking levels, none, low or high. The card Python example loads the original model, builds a chat prompt with thinking switched on and generates a reply.

Thinking level | What it trades
none | No thinking, for the fastest and cheapest replies
low | Shorter reasoning, with a small score drop and much shorter output
high | Full reasoning for the best quality

Example: You ask the model a short factual question, with thinking set to low for a quick reply. The card says low effort cuts average output length by 22.0 percent for the 4B model, with a 1.7 point drop in score.

For newcomers and experts: If you are new to local models, download the files, open them in a runner and start with a plain question at the low thinking level. Move to high only when answers need more care.

If you know the field, the architecture is unchanged from the earlier Spark-X2.5-4B and the improvements are credited to post-training. The authors say it runs as efficiently as Qwen3.5-4B and Gemma-E4B, or more so.

Download the GGUF file
Open it in a local runner
Choose a thinking level
Read the reply

Good to know:

• The benchmark claims, including matching some 9B models, come from the authors and are shown as pictures in the card
• The 4-bit files come to roughly 2.2 GB, by Hugging Face estimate
• Hugging Face lists 2 quantized and 1 fine-tuned version made by other people

Title: Average output length drop from high to low effort
Spark-X2.6-1.7B: 37.3 percent
Spark-X2.6-4B: 22.0 percent

• License: Apache 2.0
• Cost to run: none named
• Data it reaches: the files you download and the prompts you give it
• Not for: the source states no restrictions

On Hugging Face, 13 November 2026

• Task: text generation
• Library: transformers
• Parameters: 4.4B
• Weights: about 2.2 GB at 4-bit (estimate)
• Formats: GGUF
• Downloads in the last 30 days: 687,668
• Likes: 310
• License: apache-2.0
• Languages: en, zh
• Based on: XHToken/Spark-X2.6-4B
• Quantized versions: 2
• Fine-tunes: 1
• Tags: transformers, gguf, sparkx2_5, text-generation, conversational

Links

• Model: https://huggingface.co/XHToken/Spark-X2.6-4B-GGUF
• Files: https://huggingface.co/XHToken/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 XHToken/Spark-X2.6-4B-GGUF

Then follow the usage in its model card. Nothing in this kit runs by itself.