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meshllm/
gemma-4-26B-A4B-it-UD-Q4_K_M-layers

Name: gemma-4-26B-A4B-it-UD-Q4_K_M-layers
Availability: InStock

distributed-inference

local-inference

openai-compatible

text-generation

unsloth/gemma-4-26B-A4B-it-GGUF

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Mesh LLM

gemma-4-26B-A4B-it-UD-Q4_K_M

Distributed GGUF inference package for Mesh LLM

GitHub

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GGUF layer package for running gemma-4-26B-A4B-it-UD-Q4_K_M across a local Mesh LLM cluster.

This package is derived from unsloth/gemma-4-26B-A4B-it-GGUF and keeps the original GGUF distribution split into per-layer artifacts for distributed inference.

Highlights

Run locally	Pool multiple machines	OpenAI-compatible	Package variant
Private inference on your hardware	Split layers across peers	Serve `/v1/chat/completions` locally	`UD-Q4_K_M` layer package

Model Overview

Property	Value
Source model	unsloth/gemma-4-26B-A4B-it-GGUF
Model id	`unsloth/gemma-4-26B-A4B-it-GGUF:UD-Q4_K_M`
Family	Gemma
Parameter scale	26B-A4B
Quantization	`UD-Q4_K_M`
Layer count	30
Activation width	2816
Package size	16.3 GB
Source file	`gemma-4-26B-A4B-it-UD-Q4_K_M.gguf`
Package repo	meshllm/gemma-4-26B-A4B-it-UD-Q4_K_M-layers

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/gemma-4-26B-A4B-it-GGUF.

Quickstart

bash

# Run this on each machine that should contribute memory/compute.
mesh-llm serve --model "meshllm/gemma-4-26B-A4B-it-UD-Q4_K_M-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/gemma-4-26B-A4B-it-GGUF:UD-Q4_K_M",
    "messages": [{"role": "user", "content": "Write a tiny hello-world function in Rust."}],
    "max_tokens": 128
  }'

Package Variant

Property	Value
Format	`layer-package`
Canonical source ref	`unsloth/gemma-4-26B-A4B-it-GGUF@main/gemma-4-26B-A4B-it-UD-Q4_K_M.gguf`
Source revision	`main`
Source SHA-256	`34c746b1d50ab813e29cd46c4796e3f43c741901a582f93a67b55b9fc9687b35`
Skippy ABI	`0.1.22`
Package manifest SHA-256	`23c1e32d371c3f50aa393e046894d1f893f22d99f0ccee91552be17cf9c88b65`

What Is Included

Artifact	Path	Contents	SHA-256
Manifest	`model-package.json`	Package schema, source identity, checksums	`23c1e32d371c3f50aa393e046894d1f893f22d99f0ccee91552be17cf9c88b65`
Metadata	`shared/metadata.gguf`	1 tensors, 15.1 MB	`4ea990cfa36597971790aa1dcc4658cd8c946685b3d16dbaac4f685efb382002`
Embeddings	`shared/embeddings.gguf`	2 tensors, 763.1 MB	`6eb39617e6999290dd4c338cdcadf98ea42f948812fb4aeb0eab50735c7e0dd3`
Output head	`shared/output.gguf`	2 tensors, 15.1 MB	`88f7262cffae57f67ffb7b8db8fa9c04439d43a3af7d53fa3df81f0c6511e522`
Transformer layers	`layers/layer-*.gguf`	30 layer artifacts, 685 tensors, 15.5 GB	`see model-package.json`

Validation

Generated by the Mesh LLM HF Jobs splitter from mesh-llm ref main and validated before upload:

skippy-model-package validate-package "/source/gemma-4-26B-A4B-it-UD-Q4_K_M.gguf" "$PACKAGE_DIR"

meshllm/gemma-4-26B-A4B-it-UD-Q4_K_M-layers

gemma-4-26B-A4B-it-UD-Q4_K_M

Highlights

Model Overview

Recommended Use

Quickstart

Package Variant

What Is Included

Validation

Links

meshllm/
gemma-4-26B-A4B-it-UD-Q4_K_M-layers