Instructions to use pipenetwork/GLM-5.3-Flash-MLX-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use pipenetwork/GLM-5.3-Flash-MLX-8bit 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("pipenetwork/GLM-5.3-Flash-MLX-8bit")
config = load_config("pipenetwork/GLM-5.3-Flash-MLX-8bit")

# 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 pipenetwork/GLM-5.3-Flash-MLX-8bit with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "pipenetwork/GLM-5.3-Flash-MLX-8bit"

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": "pipenetwork/GLM-5.3-Flash-MLX-8bit"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent

How to use pipenetwork/GLM-5.3-Flash-MLX-8bit 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 "pipenetwork/GLM-5.3-Flash-MLX-8bit"

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 pipenetwork/GLM-5.3-Flash-MLX-8bit

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use pipenetwork/GLM-5.3-Flash-MLX-8bit with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "pipenetwork/GLM-5.3-Flash-MLX-8bit"

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 "pipenetwork/GLM-5.3-Flash-MLX-8bit" \
  --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"

pipenetwork commited on about 1 month ago

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@@ -75,6 +75,12 @@ bootstrapped over one shared index set (20,000 resamples):
 | [6bit](https://huggingface.co/pipenetwork/GLM-5.3-Flash-MLX-6bit) | 255.9 GB | 3.4646 | +0.0011 [−0.0017, +0.0038] | 89/141 |
 | [mixed-4_8bit](https://huggingface.co/pipenetwork/GLM-5.3-Flash-MLX-mixed-4_8bit) | 181.9 GB | 3.5705 | +0.0312 [+0.0271, +0.0355] | 131/141 |
 | [4bit](https://huggingface.co/pipenetwork/GLM-5.3-Flash-MLX-4bit) | 177.6 GB | 3.7549 | +0.0816 [+0.0755, +0.0879] | 140/141 |
 Read the interval, not the point estimate; "windows worse" counts how many of the 141
 windows the build lost outright.

 | [6bit](https://huggingface.co/pipenetwork/GLM-5.3-Flash-MLX-6bit) | 255.9 GB | 3.4646 | +0.0011 [−0.0017, +0.0038] | 89/141 |
 | [mixed-4_8bit](https://huggingface.co/pipenetwork/GLM-5.3-Flash-MLX-mixed-4_8bit) | 181.9 GB | 3.5705 | +0.0312 [+0.0271, +0.0355] | 131/141 |
 | [4bit](https://huggingface.co/pipenetwork/GLM-5.3-Flash-MLX-4bit) | 177.6 GB | 3.7549 | +0.0816 [+0.0755, +0.0879] | 140/141 |
+| [REAP25-mixed-4_8bit](https://huggingface.co/pipenetwork/GLM-5.3-Flash-REAP25-MLX-mixed-4_8bit) | 139.1 GB | 4.2249 | +0.1995 [+0.1657, +0.2377] | 139/141 |
+| [REAP37-mixed-4_8bit](https://huggingface.co/pipenetwork/GLM-5.3-Flash-REAP37-MLX-mixed-4_8bit) | 118.3 GB | 4.8752 | +0.3427 [+0.2968, +0.3929] | 141/141 |
+| [REAP50-mixed-4_8bit](https://huggingface.co/pipenetwork/GLM-5.3-Flash-REAP50-MLX-mixed-4_8bit) | 96.3 GB | 6.0757 | +0.5628 [+0.5071, +0.6219] | 141/141 |
+| [REAP25-4bit](https://huggingface.co/pipenetwork/GLM-5.3-Flash-REAP25-MLX-4bit) | — | 4.4361 | +0.2483 [+0.2135, +0.2873] | 141/141 |
+| [REAP37-4bit](https://huggingface.co/pipenetwork/GLM-5.3-Flash-REAP37-MLX-4bit) | — | 5.1057 | +0.3889 [+0.3424, +0.4393] | 141/141 |
+| [REAP50-4bit](https://huggingface.co/pipenetwork/GLM-5.3-Flash-REAP50-MLX-4bit) | — | 6.3840 | +0.6123 [+0.5552, +0.6722] | 141/141 |
 Read the interval, not the point estimate; "windows worse" counts how many of the 141
 windows the build lost outright.