Instructions to use nightmedia/gemma-4-26B-A4B-it-mxfp8-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use nightmedia/gemma-4-26B-A4B-it-mxfp8-mlx with MLX:

# Make sure mlx-vlm is installed
# pip install --upgrade mlx-vlm

from mlx_vlm import load, generate
from mlx_vlm.prompt_utils import apply_chat_template
from mlx_vlm.utils import load_config

# Load the model
model, processor = load("nightmedia/gemma-4-26B-A4B-it-mxfp8-mlx")
config = load_config("nightmedia/gemma-4-26B-A4B-it-mxfp8-mlx")

# Prepare input
image = ["http://images.cocodataset.org/val2017/000000039769.jpg"]
prompt = "Describe this image."

# Apply chat template
formatted_prompt = apply_chat_template(
    processor, config, prompt, num_images=1
)

# Generate output
output = generate(model, processor, formatted_prompt, image)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps Settings
LM Studio

How to use nightmedia/gemma-4-26B-A4B-it-mxfp8-mlx with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "nightmedia/gemma-4-26B-A4B-it-mxfp8-mlx"

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "mlx-lm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "nightmedia/gemma-4-26B-A4B-it-mxfp8-mlx"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent

How to use nightmedia/gemma-4-26B-A4B-it-mxfp8-mlx with Hermes Agent:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "nightmedia/gemma-4-26B-A4B-it-mxfp8-mlx"

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 nightmedia/gemma-4-26B-A4B-it-mxfp8-mlx

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use nightmedia/gemma-4-26B-A4B-it-mxfp8-mlx with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "nightmedia/gemma-4-26B-A4B-it-mxfp8-mlx"

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 "nightmedia/gemma-4-26B-A4B-it-mxfp8-mlx" \
  --custom-provider-id mlx-lm \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

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

gemma-4-26B-A4B-it-mxfp8-mlx

Brainwaves

         arc   arc/e boolq hswag obkqa piqa  wino
mxfp8    0.454,0.598,0.871,0.582,0.394,0.723,0.645
mxfp4    0.462,0.596,0.855,0.578,0.378,0.723,0.637
qx86-hi  0.472,0.605,0.873,0.565,0.386,0.712,0.644
qx64-hi  0.472,0.621,0.866,0.564,0.382,0.717,0.637

Perplexity               Peak Memory   Tokens/sec
mxfp8   103.904 ± 1.765   33.28 GB      880
mxfp4   123.621 ± 2.121   20.66 GB     1266
qx86-hi  75.542 ± 1.247   29.23 GB     1145
qx64-hi  98.161 ± 1.645   22.92 GB     1135

Based on this model

         arc   arc/e boolq hswag obkqa piqa  wino

TeichAI/gemma-4-26B-A4B-it-Claude-Opus-Distill
qx86-hi  0.433,0.522,0.468,0.506,0.370,0.687,0.612
Instruct
qx86-hi  0.564,0.763,0.861,0.657,0.450,0.771,0.680

See parent model for instructions on install and use with Transformers.