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What you can do with Spark X2 6

Spark-X2.6-4B is a compact, general-purpose language model for on-device agents, released with Transformers, SGLang, vLLM, and Ollama deployment paths.

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XHToken/Spark-X2.6 on GitHub

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What do you want to do?

3 use cases

  • Run Spark-X2.6-4B locally in Python with Transformers

    Load the 4B model in a Python script and get a chat reply on your own machine.

    View prompt
    Using the XHToken/Spark-X2.6-4B Transformers Quickstart in the Spark-X2.6 GitHub README, install transformers==4.57.1, replace the user message with <your question>, and run the script. Expected output: a text answer printed to the console. Verify that the printed answer addresses <your question> and that the script ran without a trust_remote_code error.

  • Serve Spark-X2.6-4B as an API with SGLang on NVIDIA GPUs

    Run an OpenAI-compatible endpoint with tool-call and reasoning parsers enabled.

    View prompt
    Using the Spark-X2.6 README SGLang NVIDIA GPU server block, start an OpenAI-compatible server for the checkpoint at <MODEL_PATH> on port 30000 with served model name spark2.6. Send the chat request <your prompt> to http://localhost:30000/v1/chat/completions and report the reply text. Verify that the response JSON has a choices array with non-empty content.

  • Serve Spark-X2.6-4B with vLLM for an OpenAI-style API

    Deploy the model with the official vLLM Docker image and prefix caching turned on.

    View prompt
    Using the Spark-X2.6 README vLLM NVIDIA deployment block, start vllm/vllm-openai:latest with the model at <MODEL_PATH> mounted and served as spark25 on port 30000. Send <your prompt> to the chat completions endpoint and return the reply. Verify that the response contains a non-empty message content field.

How to use Spark X2 6

  1. Check you have what it needs: A machine with an NVIDIA GPU or Ascend NPU for the server use cases, or enough local memory for the Transformers example; Docker installed for the SGLang and vLLM use cases; Python with pip for the Transformers use case, using transformers==4.57.1.
  2. Open XHToken/Spark-X2.6 on GitHub and read the README and license.
  3. Run pip install transformers==4.57.1 to install the version the README specifies.
  4. Copy the Transformers code block from the README Quickstart into a new file.
  5. Change the content in the messages list to your own question.
  6. Run the script and read the decoded output printed at the end.

These steps come from our top use case, Run Spark-X2.6-4B locally in Python with Transformers, which also has a copy-paste agent prompt.

Spark X2 6 alternatives · Best AI repos for Software and DevOps

About this repo

  • Who it is forDevelopers and ML engineers who want to run a small open model locally or on their own GPU or Ascend hardware and call it from their own applications or agents.
  • Why it is hot
  • Sourcegithub.com/XHToken/Spark-X2.6 · Back to Hot repos

Requirements

  • A machine with an NVIDIA GPU or Ascend NPU for the server use cases, or enough local memory for the Transformers example
  • Docker installed for the SGLang and vLLM use cases
  • Python with pip for the Transformers use case, using transformers==4.57.1
  • Local copy of the model checkpoint or network access to Hugging Face, ModelScope, or Ollama to download it
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Questions about Spark X2 6

What is Spark X2 6?

Spark-X2.6-4B is a compact, general-purpose language model for on-device agents, released with Transformers, SGLang, vLLM, and Ollama deployment paths. It is an open-source project on GitHub: https://github.com/XHToken/Spark-X2.6.

Who is Spark X2 6 for?

Developers and ML engineers who want to run a small open model locally or on their own GPU or Ascend hardware and call it from their own applications or agents.

What can I do with Spark X2 6?

3 use cases so far, for example: Run Spark-X2.6-4B locally in Python with Transformers; Serve Spark-X2.6-4B as an API with SGLang on NVIDIA GPUs; Serve Spark-X2.6-4B with vLLM for an OpenAI-style API. Each has steps and a copy-paste agent prompt.

What do I need to run Spark X2 6?

A machine with an NVIDIA GPU or Ascend NPU for the server use cases, or enough local memory for the Transformers example; Docker installed for the SGLang and vLLM use cases; Python with pip for the Transformers use case, using transformers==4.57.1; Local copy of the model checkpoint or network access to Hugging Face, ModelScope, or Ollama to download it.

What are alternatives to Spark X2 6?

Other hot AI repos in Software and DevOps: Harness2, iFixAi, Orca, Diagram Design, AI Memory.

Is Spark X2 6 safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.