Open-weight local LLM

Spark-X2.5-4B

Use case: Coding assistant. Check the memory fit and choose a setup path below.

16 GB catalogue minimum16 GB RAMBF16 GGUFCoding assistant
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Parameters
4B
Minimum RAM
16 GB
Model size
7.67 GB
Quantization
BF16 GGUF

About Spark-X2.5-4B

Catalogue summary: Spark-X2.5-4B is an Apache 2.0 compact general-purpose model from XHToken with a hybrid attention architecture, 1M-token native context, multilingual coverage and official GGUF artifacts for local llama.cpp, Ollama and LM Studio-compatible workflows.

Spark-X2.5-4B has a catalogue minimum of 16 GB RAM with BF16 GGUF. Actual memory use and speed vary by context length, runtime, backend and system headroom.

Use Spark-X2.5-4B as the catalogue search term in a compatible runtime, and confirm the available format on the upstream repository before download.

chatcodereasoningtool-callinglong-contextgeneral

Install path

01
Check RAM fitMinimum 16 GB RAM. Start with the BF16 GGUF quant.
02
Load the modelSearch Spark-X2.5-4B in LM Studio.
03
Try your workloadStart with a short prompt, check memory use and adjust context length before running longer tasks.

Catalogue record

  • Family: spark
  • Parameters: 4B
  • Recommended quantization: BF16 GGUF
  • Catalogue minimum RAM: 16 GB
  • Catalogue model size: 7.67 GB
  • Tags: chat, code, reasoning, tool-calling, long-context, general

Practical limits

  • Catalogue RAM is a minimum estimate, not a guarantee for every context length or runtime.
  • Speed and memory use vary by quantization, backend, context length and system headroom.
  • Verify architecture, licence and usage restrictions in the linked upstream material before deployment.

Reading the scores

LocalClaw /10 is an editorial catalogue rating. Community /5 comes from member reviews. Your machine fit is a separate memory and runtime assessment.

Capability profile

Repository catalogue ratings used by LocalClaw's editorial rubric. They are not a standardized third-party benchmark.

speed
8
quality
7
coding
7
reasoning
7

Technical notes

Developer
XHToken / SparkLLM
License
Apache 2.0
Context window
1,048,576 tokens
Architecture
Compact 4B Spark-X2.5 causal language model with a hybrid attention design that combines full-attention and sliding-window attention layers for lower long-context overhead.

This model fits these next steps

Hardware fit is based on LocalClaw's RAM tier, model size and quantization metadata. Always leave memory headroom for your OS and runtime.

Related catalogue entries

Linked mechanically by family, shared tags and nearby RAM tier; this is not a quality ranking.

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