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meshllm/Kimi-K3-UD-Q4_K_XL-layers

sourceHugging Faceotherupdated 13d agoView on Hugging Face
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Model Card

<div align="center"> <a href="https://www.meshllm.cloud"> <img src="https://meshllm.cloud/assets/images/jelly-logo-wordmark.png" alt="Mesh LLM" width="220"> </a>

<h1>Kimi-K3-UD-Q4KXL</h1>

<p> <strong>Distributed GGUF inference package for Mesh LLM</strong> </p>

<p> <a href="https://www.meshllm.cloud"><img alt="Website" src="https://img.shields.io/badge/Website-meshllm.cloud-111111?style=for-the-badge"></a> <a href="https://github.com/Mesh-LLM/mesh-llm"><img alt="GitHub" src="https://img.shields.io/badge/GitHub-Mesh--LLM-24292f?style=for-the-badge&logo=github"></a> <a href="https://discord.gg/rs6fmc63eN"><img alt="Discord" src="https://img.shields.io/badge/Discord-Join-5865F2?style=for-the-badge&logo=discord&logoColor=white"></a> </p> </div>

GGUF layer package for running Kimi-K3-UD-Q4_K_XL across a local Mesh LLM cluster.

This package is derived from unsloth/Kimi-K3-GGUF and keeps the original GGUF distribution split into per-layer artifacts for distributed inference.

Highlights

Run locallyPool multiple machinesOpenAI-compatiblePackage variant
Private inference on your hardwareSplit layers across peersServe /v1/chat/completions locallyUD-Q4_K_XL layer package

Model Overview

PropertyValue
Source modelunsloth/Kimi-K3-GGUF
Model idunsloth/Kimi-K3-GGUF:UD-Q4_K_XL
FamilyKimi
Parameter scalenot recorded
QuantizationUD-Q4_K_XL
Layer count93
Activation widthnot recorded
Package size0 B
Source fileUD-Q4_K_XL/Kimi-K3-UD-Q4_K_XL-00001-of-00032.gguf
Package repomeshllm/Kimi-K3-UD-Q4_K_XL-layers
Licenseother from unsloth/Kimi-K3-GGUF

Recommended Use

  • —Local and private inference with Mesh LLM.
  • —Multi-machine serving when the full GGUF is too large for one host.
  • —OpenAI-compatible chat/completions workflows through Mesh LLM's local API.

For upstream architecture details, chat template guidance, sampling recommendations, license terms, and benchmark notes, see the source model card: unsloth/Kimi-K3-GGUF.

Quickstart

bash
# Run this on each machine that should contribute memory/compute.
mesh-llm serve --model "meshllm/Kimi-K3-UD-Q4_K_XL-layers" --split
bash
# Check the mesh and discover the OpenAI-compatible model name.
curl -s http://localhost:3131/api/status
curl -s http://localhost:3131/v1/models
bash
# Send an OpenAI-compatible chat request.
curl -s http://localhost:3131/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "unsloth/Kimi-K3-GGUF:UD-Q4_K_XL",
    "messages": [{"role": "user", "content": "Write a tiny hello-world function in Rust."}],
    "max_tokens": 128
  }'

Package Variant

PropertyValue
Formatgguf
Canonical source refunsloth/Kimi-K3-GGUF@a0836360ce58dfec088d966a97f2ddc8a606279b/UD-Q4_K_XL/Kimi-K3-UD-Q4_K_XL-00001-of-00032.gguf
Source revisiona0836360ce58dfec088d966a97f2ddc8a606279b
Source SHA-2566a4946f4e60ebf19a3a8b0ac9f0fe7cd7f8c62936644b88c262c2fc01814ad87
Skippy ABInot recorded
Package manifest SHA-256240b16cc6ddb7bb8c8073ca609b74fe93af14e8407cc9bdf2bc4ef675161b849

What Is Included

ArtifactPathContentsSHA-256
Manifestmodel-package.jsonPackage schema, source identity, checksums240b16cc6ddb7bb8c8073ca609b74fe93af14e8407cc9bdf2bc4ef675161b849

Validation

Generated by the Mesh LLM HF Jobs splitter from mesh-llm ref f932c4d1dc12b3e3a670d5f470cedd5cdcc5db39. Each artifact is checksummed as it is written, uploaded to this repository, and removed from the job workspace before the next artifact is produced.

bash
skippy-model-package write-package "/hf-cache/UD-Q4_K_XL/Kimi-K3-UD-Q4_K_XL-00001-of-00032.gguf" --out-dir "/tmp/meshllm-layer-job-meshllm_Kimi-K3-UD-Q4_K_XL-layers-1"

Links