Instructions to use axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-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 axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-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 axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF:BF16
# Run inference directly in the terminal:
llama cli -hf axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF:BF16
# Run inference directly in the terminal:
llama cli -hf axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF:BF16

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 axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF:BF16
# Run inference directly in the terminal:
./llama-cli -hf axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF:BF16

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 axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF:BF16

Use Docker

docker model run hf.co/axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF:BF16

LM Studio
Jan

vLLM

How to use axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-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": "axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-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/axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF:BF16

Ollama
How to use axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF with Ollama:
```
ollama run hf.co/axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF:BF16
```
Unsloth Desktop

How to use axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF:BF16

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF:BF16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF with Docker Model Runner:
```
docker model run hf.co/axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF:BF16
```

Lemonade

How to use axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF:BF16

Run and chat with the model

lemonade run user.Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF-BF16

List all available models

lemonade list

Hermes Agent

How to use axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-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 axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF:BF16

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 axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF:BF16

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF:BF16

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 "axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4-GGUF:BF16" \
  --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"

Qwen3.8-Flash-Next W4A16 NVFP4 GGUF

GGUF conversion of axiomofmind/Qwen3.8-Flash-Next-W4A16-NVFP4, based on Qwen/Qwen3.8-Flash-Next.

The routed-expert weights use W4A16 NVFP4. Attention, shared experts, routers, embeddings, PLE, and other retained tensors remain in BF16 or F32.

Files

File	Description	Size
`Qwen3.8-Flash-Next-W4A16-NVFP4-BF16attn-PLE-noMTP.gguf`	Main text model	180.4 GB
`mmproj-Qwen3.8-Flash-Next-BF16.gguf`	BF16 vision projector	907.5 MB

The vision projector is required for image inputs. It is not required for text-only use.

This GGUF does not include MTP weights.

Requirements

A llama.cpp build with Qwen4Exp and NVFP4 GGUF support is required.

For multimodal use, load the main model together with the included mmproj file.

License

This model is distributed under the Qwen Community License 1.0. Refer to the official model card for architecture details, usage guidance, and limitations.