Instructions to use AutomatosX/AX-Qwen3-Coder-Next-MLX-6bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AutomatosX/AX-Qwen3-Coder-Next-MLX-6bit 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("AutomatosX/AX-Qwen3-Coder-Next-MLX-6bit")

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 AutomatosX/AX-Qwen3-Coder-Next-MLX-6bit with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "AutomatosX/AX-Qwen3-Coder-Next-MLX-6bit"

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": "AutomatosX/AX-Qwen3-Coder-Next-MLX-6bit"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use AutomatosX/AX-Qwen3-Coder-Next-MLX-6bit 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 "AutomatosX/AX-Qwen3-Coder-Next-MLX-6bit"

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 AutomatosX/AX-Qwen3-Coder-Next-MLX-6bit

Run Hermes

hermes

OpenClaw new

How to use AutomatosX/AX-Qwen3-Coder-Next-MLX-6bit with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "AutomatosX/AX-Qwen3-Coder-Next-MLX-6bit"

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 "AutomatosX/AX-Qwen3-Coder-Next-MLX-6bit" \
  --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"

MLX LM

How to use AutomatosX/AX-Qwen3-Coder-Next-MLX-6bit with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "AutomatosX/AX-Qwen3-Coder-Next-MLX-6bit"

Run an OpenAI-compatible server

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

AX Qwen3 Coder Next MLX 6-bit

Parameter count: approximately 79.67B logical parameters (80B total, 3B active per token). 6-bit is the quantization precision, not a 6B model-size claim.

This is a revision-pinned, transparent mirror of mlx-community/Qwen3-Coder-Next-6bit at commit 9d12cc36cc6c386ffd04f7c8f0de6ccb29c5927e.

The model weights, index, configuration, tokenizer, chat template, generation configuration, and tool-parser files are byte-identical to that upstream revision. AutomatosX did not fine-tune, merge, re-quantize, or otherwise alter the model artifacts. We add only mirror documentation, a copy of the declared Apache 2.0 license, and machine-readable provenance.

Model details

Base model: Qwen/Qwen3-Coder-Next
Format: MLX Safetensors for Apple Silicon
Architecture: Qwen3NextForCausalLM, mixture of experts
Main quantization: 6-bit affine, group size 64
Quantization exceptions: router and shared-expert gate tensors remain 8-bit, as defined by the unchanged upstream config
Layers: 48
Experts: 512 total, 10 selected per token
Configured context limit: 262,144 tokens
Weight shards: 13, totaling 64,749,929,465 bytes
Upstream conversion tool: mlx-lm 0.30.5

Download

hf download AutomatosX/AX-Qwen3-Coder-Next-MLX-6bit \
  --local-dir ./AX-Qwen3-Coder-Next-MLX-6bit

Use with MLX-LM

pip install mlx-lm
mlx_lm.generate \
  --model AutomatosX/AX-Qwen3-Coder-Next-MLX-6bit \
  --prompt "Write a Python function that merges two sorted lists."

Applications should apply the included chat template for conversational or tool-using prompts.

Serve with AX Engine

You can also serve the downloaded model through the OpenAI-compatible API in AX Engine:

ax-engine serve ./AX-Qwen3-Coder-Next-MLX-6bit --port 31418

Mirror policy and provenance

This release is meant to group a required upstream artifact under the AutomatosX catalog, not to claim a new conversion. UPSTREAM_README.md preserves the original upstream model card. ax_provenance.json pins the source commit and records SHA-256 values and sizes for every mirrored artifact.

This is a standard direct-decoding model. It does not contain an MTP head and no MTP conversion was applied.

License

The upstream model metadata declares Apache License 2.0. See LICENSE, the upstream model card, and the base-model card for limitations and responsible-use guidance.

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Safetensors

Model size

80B params

Tensor type

BF16

U32

MLX

Hardware compatibility

6-bit

Model tree for AutomatosX/AX-Qwen3-Coder-Next-MLX-6bit

Base model

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(111)

this model

Collection including AutomatosX/AX-Qwen3-Coder-Next-MLX-6bit

AutomatosX MLX Model Catalog

Collection

Official AutomatosX MLX releases for Apple Silicon. OptiQ mixed 4/8-bit packages sit next to uniform 4bit/6bit siblings. • 31 items • Updated 3 days ago