---
title: Spark-X2.6-4B-Base
canonical_url: "https://www.modelscope.cn/models/XHToken/Spark-X2.6-4B-Base"
md_url: "https://www.modelscope.cn/models/XHToken/Spark-X2.6-4B-Base.md"
repository: XHToken/Spark-X2.6-4B-Base
last_updated: 2026-10-27
license: apache-2.0
pipeline_tag: text-generation
tasks:
  - text-generation
model_type:
  - spark2_5
architectures:
  - Spark2_5ForCausalLM
parameters: 4.1B
tensor_type:
  - BF16
library_name:
  - safetensors
language:
  - en
  - zh
downloads: 40
stars: 3
tags:
  - llm
  - sparkx2_5
---

# Spark-X2.6-4B-Base

> Spark-X2.6-4B-Base - XHToken 在 ModelScope 开源的模型。Spark-X2.6-4B: Advancing the Frontier of On-Device Agents for Real-World Tasks

XHToken/Spark-X2.6-4B-Base 是 ModelScope 魔搭社区上的 4.1B 参数text-generation模型，采用 apache-2.0 许可。

- **Repository**: XHToken/Spark-X2.6-4B-Base
- **License**: apache-2.0
- **Tasks**: text-generation
- **Parameters**: 4.1B
- **Tags**: llm, sparkx2_5
- **Downloads**: 40
- **Stars**: 3
- **Last updated**: 2026-10-27

Source: https://www.modelscope.cn/models/XHToken/Spark-X2.6-4B-Base

---

# Spark-X2.6-4B: Advancing the Frontier of On-Device Agents for Real-World Tasks
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## Introduction
A little over a month has passed since Spark-X2.5. In the rapidly evolving world of AI agents, that is enough time to rethink, refine, and move the frontier forward. Building on the Spark-X2.5-4B, we introduce **Spark-X2.6-4B**, the latest generation of our compact, general-purpose language models for on-device deployment. 

Spark-X2.6-4B retains exactly the same architecture as Spark-X2.5-4B, achieving its capability gains through improved post-training. It delivers substantial improvements in coding, agent, long-context, multilingual, reasoning, etc. These advances enable more capable and practical on-device AI for developers and users tackling real-world tasks.


**Technical Highlights**:
- **Stronger Coding, Agentic, and Long-Context Capabilities**: The models deliver substantial improvements in agentic workflows involving complex tool use, multi-step planning, and software engineering. They achieve state-of-the-art performance among similarly sized open-source models, matching or even surpassing models with approximately 9B parameters.
- **Controllable Thinking Budget**: The models provide three configurable thinking levels—none, low, high—allowing applications to balance reasoning quality, latency, and inference cost dynamically.

### Fine-Tuning

We recommend using [Llama-Factory](https://github.com/XHToken/LlamaFactory) to fine-tune the model.


## License

The Spark-X2.6 model series is licensed under the [Apache 2.0 License](LICENSE).

## Citation
If you find our work helpful, feel free to give us a cite.

```bibtex
@misc{sparkx2.6,
    title  = {Spark-X2.6-4B&1.7B: Advancing the Frontier of On-Device Agents for Real-World Tasks},
    author = {SparkLLM Team},
    year   = {2026}
}
```