Instructions to use GiaHuy/Darwin-36B-Opus-mlx-text-only-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use GiaHuy/Darwin-36B-Opus-mlx-text-only-8bit with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("GiaHuy/Darwin-36B-Opus-mlx-text-only-8bit") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
- Pi new
How to use GiaHuy/Darwin-36B-Opus-mlx-text-only-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 "GiaHuy/Darwin-36B-Opus-mlx-text-only-8bit"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "GiaHuy/Darwin-36B-Opus-mlx-text-only-8bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use GiaHuy/Darwin-36B-Opus-mlx-text-only-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 "GiaHuy/Darwin-36B-Opus-mlx-text-only-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 GiaHuy/Darwin-36B-Opus-mlx-text-only-8bit
Run Hermes
hermes
- MLX LM
How to use GiaHuy/Darwin-36B-Opus-mlx-text-only-8bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "GiaHuy/Darwin-36B-Opus-mlx-text-only-8bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "GiaHuy/Darwin-36B-Opus-mlx-text-only-8bit" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GiaHuy/Darwin-36B-Opus-mlx-text-only-8bit", "messages": [ {"role": "user", "content": "Hello"} ] }'
Darwin-36B-Opus MLX Text-Only 8-bit
This repository contains a text-only 8-bit MLX conversion of FINAL-Bench/Darwin-36B-Opus.
The model was converted with mlx-lm and is intended for efficient inference on Apple Silicon.
Model Details
- Original model:
FINAL-Bench/Darwin-36B-Opus - Format: MLX
- Quantization: 8-bit
- Modality: Text-only
- Runtime: Apple Silicon
- Recommended server:
cubist38/mlx-openai-server
Run with mlx-openai-server
This model is designed to be served through my open-source OpenAI-compatible MLX server:
Install the server:
pip install mlx-openai-server
Then launch the model:
mlx-openai-server launch \
--model-path Darwin-36B-Opus-mlx-text-only-8bit \
--reasoning-parser qwen3_moe \
--tool-call-parser qwen3_coder \
--debug \
--served-model-name Darwin-36B-Opus
The server exposes an OpenAI-compatible API, making it easy to use with existing OpenAI SDKs, agents, and tools.
Example: OpenAI-Compatible Python Client
from openai import OpenAI
client = OpenAI(
base_url="http://localhost:8000/v1",
api_key="not-needed",
)
response = client.chat.completions.create(
model="Darwin-36B-Opus",
messages=[
{
"role": "user",
"content": "Explain evolutionary model merging in simple terms.",
}
],
temperature=0.7,
max_tokens=512,
)
print(response.choices[0].message.content)
Example: curl
curl http://localhost:8000/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer not-needed" \
-d '{
"model": "Darwin-36B-Opus",
"messages": [
{
"role": "user",
"content": "What makes Darwin-36B-Opus interesting?"
}
],
"temperature": 0.7,
"max_tokens": 512
}'
Notes
- This is a text-only MLX conversion.
- This is an 8-bit quantized version, so outputs may differ from the original checkpoint.
- The recommended way to serve this model is through
mlx-openai-server. - The launch command uses:
--reasoning-parser qwen3_moe--tool-call-parser qwen3_coder--served-model-name Darwin-36B-Opus
Attribution
All credit for the original model goes to FINAL-Bench/Darwin-36B-Opus.
This repository provides only an MLX text-only 8-bit conversion for Apple Silicon users.
License
Please refer to the original model repository for licensing and usage terms.
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