Instructions to use mradermacher/Qwen3-Coder-Next-REAM-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mradermacher/Qwen3-Coder-Next-REAM-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("mradermacher/Qwen3-Coder-Next-REAM-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use mradermacher/Qwen3-Coder-Next-REAM-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 mradermacher/Qwen3-Coder-Next-REAM-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mradermacher/Qwen3-Coder-Next-REAM-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf mradermacher/Qwen3-Coder-Next-REAM-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mradermacher/Qwen3-Coder-Next-REAM-GGUF:Q4_K_M

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 mradermacher/Qwen3-Coder-Next-REAM-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf mradermacher/Qwen3-Coder-Next-REAM-GGUF:Q4_K_M

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 mradermacher/Qwen3-Coder-Next-REAM-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf mradermacher/Qwen3-Coder-Next-REAM-GGUF:Q4_K_M

Use Docker

docker model run hf.co/mradermacher/Qwen3-Coder-Next-REAM-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use mradermacher/Qwen3-Coder-Next-REAM-GGUF with Ollama:
```
ollama run hf.co/mradermacher/Qwen3-Coder-Next-REAM-GGUF:Q4_K_M
```
Unsloth Desktop

How to use mradermacher/Qwen3-Coder-Next-REAM-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf mradermacher/Qwen3-Coder-Next-REAM-GGUF:Q4_K_M

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": "mradermacher/Qwen3-Coder-Next-REAM-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use mradermacher/Qwen3-Coder-Next-REAM-GGUF with Docker Model Runner:
```
docker model run hf.co/mradermacher/Qwen3-Coder-Next-REAM-GGUF:Q4_K_M
```

Lemonade

How to use mradermacher/Qwen3-Coder-Next-REAM-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull mradermacher/Qwen3-Coder-Next-REAM-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Qwen3-Coder-Next-REAM-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use mradermacher/Qwen3-Coder-Next-REAM-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 mradermacher/Qwen3-Coder-Next-REAM-GGUF:Q4_K_M

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 mradermacher/Qwen3-Coder-Next-REAM-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use mradermacher/Qwen3-Coder-Next-REAM-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf mradermacher/Qwen3-Coder-Next-REAM-GGUF:Q4_K_M

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 "mradermacher/Qwen3-Coder-Next-REAM-GGUF:Q4_K_M" \
  --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"

These GGUF quants do not work with Ollama

by DannyEli - opened Feb 23

Discussion

DannyEli

Feb 23

Multiple users report:

Error: llama runner process has terminated
error loading model: missing tensor 'blk.0.ssm_in.weight'
llama_model_load_from_file_impl: failed to load model

with Qwen3-Coder-Next on Ollama.

A discussion on the Hugging Face Unsloth Qwen3-Coder-Next GGUF repo shows people getting this same missing tensor error when trying to run the model - https://huggingface.co/unsloth/Qwen3-Coder-Next-GGUF/discussions/8

The model’s GGUF file does not actually contain a tensor called blk.0.ssm_in.weight.
Users confirmed this by inspecting the model file contents, and indeed it lacked the required weight, so Ollama cannot load it.

A comment in that thread from someone associated with the model maintainer says:
“Starting from late last year, GGUFs don’t work out of the box with Ollama anymore, so at the moment we only recommend using GGUFs with llama.cpp compatible backends.”

That means the model format and Ollama’s current loader aren’t fully compatible.

Could this be addressed, please? Perhaps using just the llama.cpp to convert it to GGUF quants that could be actually used in Ollama?

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