Instructions to use unsloth/gemma-4-31B-it-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use unsloth/gemma-4-31B-it-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf unsloth/gemma-4-31B-it-GGUF:UD-Q4_K_XL
# Run inference directly in the terminal:
llama cli -hf unsloth/gemma-4-31B-it-GGUF:UD-Q4_K_XL

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf unsloth/gemma-4-31B-it-GGUF:UD-Q4_K_XL
# Run inference directly in the terminal:
llama cli -hf unsloth/gemma-4-31B-it-GGUF:UD-Q4_K_XL

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf unsloth/gemma-4-31B-it-GGUF:UD-Q4_K_XL
# Run inference directly in the terminal:
./llama-cli -hf unsloth/gemma-4-31B-it-GGUF:UD-Q4_K_XL

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf unsloth/gemma-4-31B-it-GGUF:UD-Q4_K_XL
# Run inference directly in the terminal:
./build/bin/llama-cli -hf unsloth/gemma-4-31B-it-GGUF:UD-Q4_K_XL

Use Docker

docker model run hf.co/unsloth/gemma-4-31B-it-GGUF:UD-Q4_K_XL

LM Studio
Jan

vLLM

How to use unsloth/gemma-4-31B-it-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "unsloth/gemma-4-31B-it-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "unsloth/gemma-4-31B-it-GGUF",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/unsloth/gemma-4-31B-it-GGUF:UD-Q4_K_XL

Ollama
How to use unsloth/gemma-4-31B-it-GGUF with Ollama:
```
ollama run hf.co/unsloth/gemma-4-31B-it-GGUF:UD-Q4_K_XL
```

Unsloth Studio

How to use unsloth/gemma-4-31B-it-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for unsloth/gemma-4-31B-it-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for unsloth/gemma-4-31B-it-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for unsloth/gemma-4-31B-it-GGUF to start chatting

How to use unsloth/gemma-4-31B-it-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf unsloth/gemma-4-31B-it-GGUF:UD-Q4_K_XL

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "unsloth/gemma-4-31B-it-GGUF:UD-Q4_K_XL"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use unsloth/gemma-4-31B-it-GGUF with Docker Model Runner:
```
docker model run hf.co/unsloth/gemma-4-31B-it-GGUF:UD-Q4_K_XL
```

Lemonade

How to use unsloth/gemma-4-31B-it-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull unsloth/gemma-4-31B-it-GGUF:UD-Q4_K_XL

Run and chat with the model

lemonade run user.gemma-4-31B-it-GGUF-UD-Q4_K_XL

List all available models

lemonade list

Hermes Agent

How to use unsloth/gemma-4-31B-it-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf unsloth/gemma-4-31B-it-GGUF:UD-Q4_K_XL

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default unsloth/gemma-4-31B-it-GGUF:UD-Q4_K_XL

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use unsloth/gemma-4-31B-it-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf unsloth/gemma-4-31B-it-GGUF:UD-Q4_K_XL

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "unsloth/gemma-4-31B-it-GGUF:UD-Q4_K_XL" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Apr 11: Updated with Google chat template fixes + more

#16

by danielhanchen - opened Apr 11

Discussion

danielhanchen

Unsloth AI org Apr 11

Hey everyone, we’ve updated the quants again to include all of Google’s official chat template fixes (which fixed/improved tool-calling), along with the latest llama.cpp fixes.

We know there have been a lot of re-downloading lately, so we appreciate your patience. We’re pushing updates whenever fixes become available to make sure you always have the latest and best-performing quants.

NVIDIA is working on the CUDA 13.2 issue. Until it is fixed, do not use CUDA 13.2.

danielhanchen pinned discussion Apr 11

SlavikF

Apr 11

do we need to use this parameter with llama.cpp:

--chat-template-file google-gemma-4-31B-it-interleaved.jinja

firsak

Apr 11

latest gemma-4-31B-it-UD-Q4_K_XL.gguf is literary twice as slow for me in LMStudio, compared to the one that was downloaded a week ago or so.

keick

Apr 11

I can't even RUN this version now... How can I download the old one???

/llama.cpp/ggml/src/ggml-cuda/ggml-cuda.cu:97: CUDA error
ggml_cuda_compute_forward: SCALE failed
CUDA error: device kernel image is invalid

tales59

Apr 11

•

edited Apr 11

The latest Q8XL UD - (11 Apr 4:47GMT) is far worse at reasoning/math than any of the prior downloads of this dynamic quant. It's worse than the current Q4XL UD (11 Apr 4:33GMT) when tested on AIME level math problems.

rusoloco73

Apr 12

ollama Error: 500 Internal Server Error: unable to load model: C:\Users\xxx.ollama\models\blobs\sha256-xxxxxxxxxxxxxxxxxxx

cpuq

Apr 12

also experiencing slower inference speeds and less accurate responses as well, but maybe i need more testing

danielhanchen

Unsloth AI org Apr 12

•

edited Apr 13

do we need to use this parameter with llama.cpp:

--chat-template-file google-gemma-4-31B-it-interleaved.jinja

?

Yes you will still need to use llama.cpp's interleaved chat template I don't think Google has updated it

latest gemma-4-31B-it-UD-Q4_K_XL.gguf is literary twice as slow for me in LMStudio, compared to the one that was downloaded a week ago or so.

also experiencing slower inference speeds and less accurate responses as well, but maybe i need more testing

We didn't change anything with the layers, so it might be llama.cpp or LM Studio not updated to the latest.

I can't even RUN this version now... How can I download the old one???

/llama.cpp/ggml/src/ggml-cuda/ggml-cuda.cu:97: CUDA error
ggml_cuda_compute_forward: SCALE failed
CUDA error: device kernel image is invalid

Did you update to the latest version of llama.cpp?

danielhanchen

Unsloth AI org Apr 12

ollama Error: 500 Internal Server Error: unable to load model: C:\Users\xxx.ollama\models\blobs\sha256-xxxxxxxxxxxxxxxxxxx

GGUFs with separate mmproj files are not supported in Ollama. Use llama.cpp supported backends.

Meanwhile you can try and "remove" the vision model part:

Run this command to create a Modelfile:
ollama show --modelfile hf.co/unsloth/gemma-4-26B-A4B-it-GGUF:UD-Q4_K_M > gemma_4_unsloth_modelfile

Then open the gemma_4_unsloth_modelfile and add a # character in front of the second FROM line:

# Modelfile generated by "ollama show"
# To build a new Modelfile based on this, replace FROM with:
# FROM hf.co/unsloth/gemma-4-26B-A4B-it-GGUF:UD-Q4_K_M

FROM /root/.ollama/models/blobs/sha256-2f8672b0c2cca8dedfb8782815c2769ccdaa6512788f3ee87b32cf117f0dffc1
#FROM /root/.ollama/models/blobs/sha256-fc2ebf4c44528daa2cea7b39891712847ca5e4f87dcf578054a06c46bfe6da27
TEMPLATE "{{ if .System }}<bos><|turn>system
{{ .System }}<turn|>
{{ end }}{{ if .Prompt }}<|turn>user
{{ .Prompt }}<turn|>
{{ end }}<|turn>model
{{ .Response }}<turn|>
"
PARAMETER stop <bos>
PARAMETER stop <|turn>
PARAMETER stop <turn|>
PARAMETER stop <|turn>user

Then run:

ollama create gemma-4-unsloth -f gemma_4_unsloth_modelfile

Now you can run the unsloth version without vision:

ollama run gemma-4-unsloth

From this [GitHub issue](https://github.com/ollama/ollama/issues/15235#issuecomment-4187108500.

keick

Apr 13

Built the latest llama.cpp b8779, and it still can't run this model on a V100.

common_init_from_params: warming up the model with an empty run - please wait ... (--no-warmup to disable)
/home/bfleming/llama.cpp/ggml/src/ggml-cuda/ggml-cuda.cu:97: CUDA error
ggml_cuda_compute_forward: SCALE failed
CUDA error: device kernel image is invalid

The last upload of these models worked great.

HougeLangley

Apr 13

Built the latest llama.cpp b8779, and it still can't run this model on a V100.

common_init_from_params: warming up the model with an empty run - please wait ... (--no-warmup to disable)
/home/bfleming/llama.cpp/ggml/src/ggml-cuda/ggml-cuda.cu:97: CUDA error
ggml_cuda_compute_forward: SCALE failed
CUDA error: device kernel image is invalid

The last upload of these models worked great.

What's your linux distro ? What's your CUDA version ?

HougeLangley

Apr 13

Built the latest llama.cpp b8779, and it still can't run this model on a V100.

common_init_from_params: warming up the model with an empty run - please wait ... (--no-warmup to disable)
/home/bfleming/llama.cpp/ggml/src/ggml-cuda/ggml-cuda.cu:97: CUDA error
ggml_cuda_compute_forward: SCALE failed
CUDA error: device kernel image is invalid

The last upload of these models worked great.

In my case, working fine.

keick

Apr 13

Awesome, glad to know it's working for you and for sharing your setup.

I'm on the older 12.2/12.8 driver/library currently. I was under the impression that V100 and Compute 70 were no longer supported on the 13.x branch. But I was obviously misinformed and will update the OS and Driver to 13.0.

Just to be complete, can you share how you compiled your version of llama.cpp if you know. This is what I had come up with, and had been using.

HougeLangley

Apr 13

Awesome, glad to know it's working for you and for sharing your setup.

I'm on the older 12.2/12.8 driver/library currently. I was under the impression that V100 and Compute 70 were no longer supported on the 13.x branch. But I was obviously misinformed and will update the OS and Driver to 13.0.

Just to be complete, can you share how you compiled your version of llama.cpp if you know. This is what I had come up with, and had been using.

My apologize, this is my cuda or nvcc version.

HougeLangley

Apr 13

nvcc 13 not support v100

baton4ik

Apr 13

do we need to use this parameter with llama.cpp:

--chat-template-file google-gemma-4-31B-it-interleaved.jinja

?

Yes you will still need to use llama.cpp's interleaved chat template I don't think Google has updated it

According to the author of this PR: https://github.com/ggml-org/llama.cpp/pull/21704
The interleaving fixes are in as well.

keick

Apr 14

Thank you HougeLangley!

I've created a new VM with Ubuntu 24.4 LTS, Cuda-Toolkit 12.9, Nvidia Driver 580. And I'm excited to report that I can now run this model again.

JetpackJackson

Apr 14

is there a way to get this to run using CUDA 13.2? Not sure if i want to install 12.9 from the AUR

keick

Apr 14

JetpackJackson - I have to use 12.9 because it's the last version that supported my V100 cards. If you have newer card than there shouldn't be a reason to downgrade.

JetpackJackson

Apr 14

•

edited Apr 14

Ah ok. Just confused as to how to fix this error then:

3587] llama_model_load: error loading model: error loading model architecture: unknown model architecture: 'gemma4'
[43587] llama_model_load_from_file_impl: failed to load model
[43587] common_init_from_params: failed to load model '/home/jet/.cache/huggingface/hub/models--unsloth--gemma-4-E4B-it-GGUF/snapshots/ce152932ac27bc40bc9c727386760424d50bb456/gemma-4-E4B-it-Q4_K_M.gguf'
[43587] srv    load_model: failed to load model, '/home/jet/.cache/huggingface/hub/models--unsloth--gemma-4-E4B-it-GGUF/snapshots/ce152932ac27bc40bc9c727386760424d50bb456/gemma-4-E4B-it-Q4_K_M.gguf'
[43587] srv    operator(): operator(): cleaning up before exit...
[43587] main: exiting due to model loading error

llama-cli --version
ggml_cuda_init: found 1 CUDA devices:
  Device 0: NVIDIA GeForce RTX 2070 SUPER, compute capability 7.5, VMM: yes
version: 8796 (fae3a2807)
built with GNU 15.2.1 for Linux x86_64

nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2026 NVIDIA Corporation
Built on Mon_Mar_02_09:52:23_PM_PST_2026
Cuda compilation tools, release 13.2, V13.2.51
Build cuda_13.2.r13.2/compiler.37434383_0

JetpackJackson

Apr 14

•

edited Apr 14

Fixed it, I had an old version of llamacpp also installed, removing it gave me a missing lib error, searching for that said i should just run the commands from the build dir (for the updated one) so I did that and it loads now, sorry for the noise

danielhanchen unpinned discussion May 4

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