Spark-X2.6-4B is here: our latest compact, general-purpose language model for on-device agents and real-world tasks.
It keeps the architecture of Spark-X2.5-4B and improves capabilities through post-training, with gains in coding, agent workflows, long-context tasks, multilingual use and reasoning.
The release focuses on tool use, multi-step planning and software engineering. Selected results from our published evaluation:
| Benchmark | Spark-X2.6-4B | Spark-X2.5-4B |
|---|---|---|
| BFCL-V4 | 71.8 | 65.1 |
| MCP-Atlas | 62.4 | 54.6 |
| BrowseComp | 53.1 | 40.9 |
| SWE Pro | 54.3 | 44.4 |
| SWE Verified | 62.8 | 41.6 |
| AA-LCRv1.1 | 67.3 | 64.7 |
The full comparison includes similarly sized models and larger 9B and 12B models. Spark-X2.6-4B leads on several listed tasks; rankings vary by benchmark.
These are the release team's reported results. The table evaluates Spark-X2.6-4B with thinking set to high. Asterisks identify comparison scores taken from public model cards or papers; dashes mean scores are unavailable. The original footnotes are preserved in the image.
Three thinking levels—none, low and high—let applications balance reasoning effort, latency and inference cost. Use the model card's configuration guidance for the selected runtime.
The inference chart reports prefill and decode throughput on RTX 4090 and Mac M5 Pro (16-core) across context lengths. It labels each runtime and quantization setting, including llama.cpp Q4_K_M and Spark INT4 runs using TensorRT or MLX. Compare the relevant hardware, runtime and context length when choosing a deployment.
| Platform | Download | Description |
|---|---|---|
| Hugging Face | Spark-X2.6 in Huggingface | Official Hugging Face model collection for Spark-X2.6 |
| ModelScope | Spark-X2.6 in ModelScope | Recommended download source for users in China |
| Ollama | Spark-X2.6 in Ollama | Download and run the model locally with Ollama |
Direct model weights and model card: https://huggingface.co/XHToken/Spark-X2.6-4B.
With Ollama installed, run:
ollama run SparkLLM/Spark-X2.6-4B
The release documentation also covers Transformers, SGLang, vLLM, MLX and llama.cpp. Follow the runtime-specific setup in the model card for required versions, images, plugins and hardware configuration.
The model is released under Apache 2.0. Try it on a coding task or tool-use workflow and share your runtime, hardware and results with the SparkLLM community.