Instructions to use majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-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("majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-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 Settings
LM Studio

How to use majentik/Qwen3.6-35B-A3B-RotorQuant-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 "majentik/Qwen3.6-35B-A3B-RotorQuant-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": "majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

MLX LM

How to use majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-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 "majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Hermes Agent

How to use majentik/Qwen3.6-35B-A3B-RotorQuant-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 "majentik/Qwen3.6-35B-A3B-RotorQuant-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 majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-8bit

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use majentik/Qwen3.6-35B-A3B-RotorQuant-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 "majentik/Qwen3.6-35B-A3B-RotorQuant-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 "majentik/Qwen3.6-35B-A3B-RotorQuant-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"

majentik commited on 11 days ago

Commit

d5e783f

verified ·

1 Parent(s): 9bbac10

Remove links to retired duplicate brand variants

Browse files

Files changed (1) hide show

README.md +0 -9

README.md CHANGED Viewed

@@ -95,7 +95,6 @@ upstream options described above (`-ctk/-ctv q8_0`, `OLLAMA_KV_CACHE_TYPE`).
 |---|---|---|
 | FP16 (original) | ~70 GB (approx.) | -- |
 | **8-bit quantized** | **~35 GB** | **This model** |
-| 4-bit quantized | ~18 GB | [RotorQuant-MLX-4bit](https://huggingface.co/majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-4bit) |
 | 2-bit quantized | ~9 GB | [RotorQuant-MLX-2bit](https://huggingface.co/majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-2bit) |
 ## Hardware Requirements
@@ -108,9 +107,7 @@ This model requires approximately 35 GB of unified memory. Recommended hardware:
 ## See Also
 - [Qwen/Qwen3.6-35B-A3B](https://huggingface.co/Qwen/Qwen3.6-35B-A3B) -- Base model
-- [majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-4bit](https://huggingface.co/majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-4bit) -- MLX 4-bit variant
 - [majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-2bit](https://huggingface.co/majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-2bit) -- MLX 2-bit variant
-- [majentik/Qwen3.6-35B-A3B-TurboQuant-MLX-8bit](https://huggingface.co/majentik/Qwen3.6-35B-A3B-TurboQuant-MLX-8bit) -- TurboQuant MLX 8-bit variant
 - [RotorQuant GitHub](https://github.com/scrya-com/rotorquant)
 - [MLX Framework](https://github.com/ml-explore/mlx)
@@ -140,14 +137,8 @@ This model requires approximately 35 GB of unified memory. Recommended hardware:
 | [RotorQuant-GGUF-Q5_K_M](https://huggingface.co/majentik/qwen3.6-35b-a3b-rotorquant-gguf-Q5_K_M) | llama.cpp | ~46 GB | Higher fidelity, more RAM |
 | [RotorQuant-GGUF-Q8_0](https://huggingface.co/majentik/qwen3.6-35b-a3b-rotorquant-gguf-Q8_0) | llama.cpp | ~74 GB | Near-lossless reference |
 | [RotorQuant-MLX-2bit](https://huggingface.co/majentik/qwen3.6-35b-a3b-rotorquant-mlx-2bit) | mlx-lm | ~11 GB | Apple Silicon, smallest |
-| [RotorQuant-MLX-3bit](https://huggingface.co/majentik/qwen3.6-35b-a3b-rotorquant-mlx-3bit) | mlx-lm | ~16 GB | Apple Silicon, small |
-| [RotorQuant-MLX-4bit](https://huggingface.co/majentik/qwen3.6-35b-a3b-rotorquant-mlx-4bit) | mlx-lm | ~22 GB | Apple Silicon balanced |
 | [RotorQuant-MLX-5bit](https://huggingface.co/majentik/qwen3.6-35b-a3b-rotorquant-mlx-5bit) | mlx-lm | ~27 GB | Apple Silicon, higher fidelity |
 | [RotorQuant-MLX-6bit](https://huggingface.co/majentik/qwen3.6-35b-a3b-rotorquant-mlx-6bit) | mlx-lm | ~32 GB | Apple Silicon, near-lossless |
 | **RotorQuant-MLX-8bit** | mlx-lm | ~41 GB | Apple Silicon reference |
-| [TurboQuant-MLX-2bit](https://huggingface.co/majentik/qwen3.6-35b-a3b-turboquant-mlx-2bit) | mlx-lm | ~11 GB | Apple Silicon, smallest |
 | [TurboQuant-MLX-3bit](https://huggingface.co/majentik/qwen3.6-35b-a3b-turboquant-mlx-3bit) | mlx-lm | ~16 GB | Apple Silicon, small |
 | [TurboQuant-MLX-4bit](https://huggingface.co/majentik/qwen3.6-35b-a3b-turboquant-mlx-4bit) | mlx-lm | ~22 GB | Apple Silicon balanced |
-| [TurboQuant-MLX-5bit](https://huggingface.co/majentik/qwen3.6-35b-a3b-turboquant-mlx-5bit) | mlx-lm | ~27 GB | Apple Silicon, higher fidelity |
-| [TurboQuant-MLX-6bit](https://huggingface.co/majentik/qwen3.6-35b-a3b-turboquant-mlx-6bit) | mlx-lm | ~32 GB | Apple Silicon, near-lossless |
-| [TurboQuant-MLX-8bit](https://huggingface.co/majentik/qwen3.6-35b-a3b-turboquant-mlx-8bit) | mlx-lm | ~41 GB | Apple Silicon reference |

 |---|---|---|
 | FP16 (original) | ~70 GB (approx.) | -- |
 | **8-bit quantized** | **~35 GB** | **This model** |
 | 2-bit quantized | ~9 GB | [RotorQuant-MLX-2bit](https://huggingface.co/majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-2bit) |
 ## Hardware Requirements
 ## See Also
 - [Qwen/Qwen3.6-35B-A3B](https://huggingface.co/Qwen/Qwen3.6-35B-A3B) -- Base model
 - [majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-2bit](https://huggingface.co/majentik/Qwen3.6-35B-A3B-RotorQuant-MLX-2bit) -- MLX 2-bit variant
 - [RotorQuant GitHub](https://github.com/scrya-com/rotorquant)
 - [MLX Framework](https://github.com/ml-explore/mlx)
 | [RotorQuant-GGUF-Q5_K_M](https://huggingface.co/majentik/qwen3.6-35b-a3b-rotorquant-gguf-Q5_K_M) | llama.cpp | ~46 GB | Higher fidelity, more RAM |
 | [RotorQuant-GGUF-Q8_0](https://huggingface.co/majentik/qwen3.6-35b-a3b-rotorquant-gguf-Q8_0) | llama.cpp | ~74 GB | Near-lossless reference |
 | [RotorQuant-MLX-2bit](https://huggingface.co/majentik/qwen3.6-35b-a3b-rotorquant-mlx-2bit) | mlx-lm | ~11 GB | Apple Silicon, smallest |
 | [RotorQuant-MLX-5bit](https://huggingface.co/majentik/qwen3.6-35b-a3b-rotorquant-mlx-5bit) | mlx-lm | ~27 GB | Apple Silicon, higher fidelity |
 | [RotorQuant-MLX-6bit](https://huggingface.co/majentik/qwen3.6-35b-a3b-rotorquant-mlx-6bit) | mlx-lm | ~32 GB | Apple Silicon, near-lossless |
 | **RotorQuant-MLX-8bit** | mlx-lm | ~41 GB | Apple Silicon reference |
 | [TurboQuant-MLX-3bit](https://huggingface.co/majentik/qwen3.6-35b-a3b-turboquant-mlx-3bit) | mlx-lm | ~16 GB | Apple Silicon, small |
 | [TurboQuant-MLX-4bit](https://huggingface.co/majentik/qwen3.6-35b-a3b-turboquant-mlx-4bit) | mlx-lm | ~22 GB | Apple Silicon balanced |