meshllm/Qwen3.8-Flash-Next-UD-IQ4_XS-layers

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<h1>Qwen3.8-Flash-Next-UD-IQ4_XS</h1>

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

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GGUF layer package for running Qwen3.8-Flash-Next-UD-IQ4_XS across a local Mesh LLM cluster.

This package is derived from unsloth/Qwen3.8-Flash-Next-GGUF and keeps the original GGUF distribution split into per-layer artifacts for distributed inference.

Highlights

Model Overview

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/Qwen3.8-Flash-Next-GGUF.

Quickstart

# Run this on each machine that should contribute memory/compute.
mesh-llm serve --model "meshllm/Qwen3.8-Flash-Next-UD-IQ4_XS-layers" --split

# Check the mesh and discover the OpenAI-compatible model name.
curl -s http://localhost:3131/api/status
curl -s http://localhost:3131/v1/models

# Send an OpenAI-compatible chat request.
curl -s http://localhost:3131/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "unsloth/Qwen3.8-Flash-Next-GGUF:UD-IQ4_XS",
    "messages": [{"role": "user", "content": "Write a tiny hello-world function in Rust."}],
    "max_tokens": 128
  }'

Package Variant

What Is Included

Validation

Generated by the Mesh LLM HF Jobs splitter from mesh-llm ref 293d61d8fb8be914e5244f754ceb1d67f59f177b. Each artifact is checksummed as it is written, uploaded to this repository, and removed from the job workspace before the next artifact is produced.

skippy-model-package write-package "/hf-cache/UD-IQ4_XS/Qwen3.8-Flash-Next-UD-IQ4_XS-00001-of-00003.gguf" --out-dir "/tmp/meshllm-layer-job-meshllm_Qwen3.8-Flash-Next-UD-IQ4_XS-layers-14/package"

Links

• —Source model: unsloth/Qwen3.8-Flash-Next-GGUF
• —Mesh LLM website: meshllm.cloud
• —Mesh LLM: github.com/Mesh-LLM/mesh-llm
• —Discord: discord.gg/rs6fmc63eN
• —Package catalog: meshllm/catalog
• —Package format: layer-package-repos.md