Instructions to use AutomatosX/AX-Qwen3-Coder-Next-MLX-AXQ-6bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use AutomatosX/AX-Qwen3-Coder-Next-MLX-AXQ-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-AXQ-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
- Pi
How to use AutomatosX/AX-Qwen3-Coder-Next-MLX-AXQ-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-AXQ-6bit"
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": "AutomatosX/AX-Qwen3-Coder-Next-MLX-AXQ-6bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- MLX LM
How to use AutomatosX/AX-Qwen3-Coder-Next-MLX-AXQ-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-AXQ-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-AXQ-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-AXQ-6bit", "messages": [ {"role": "user", "content": "Hello"} ] }' - Hermes Agent
How to use AutomatosX/AX-Qwen3-Coder-Next-MLX-AXQ-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-AXQ-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-AXQ-6bit
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use AutomatosX/AX-Qwen3-Coder-Next-MLX-AXQ-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-AXQ-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-AXQ-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"
AX-Qwen3-Coder-Next-MLX-AXQ-6bit
Research development artifact. Base affine6 packing with higher-precision protection, not MXFP6 or uniformly six-bit storage. No quality certificate is issued.
| Property | Value |
|---|---|
| Source | Qwen/Qwen3-Coder-Next |
| Immutable source revision | a7fbcb5c0e12d62a448eaa0e260346bf5dcc0feb |
| Complete storage | 70,213,282,892 bytes |
| Complete measured BPW | 7.050023 |
| Manifest budget class | 7p0bpw |
| MTP | No MTP payload is advertised. |
The precision distribution and exact per-module settings are recorded in
axquant_manifest.json, axquant_plan.json, and config.json. Complete BPW
includes protected tensors and storage overhead. File size does not establish
peak runtime memory requirements. Converted from the pinned original source with existing precision protection floors.
Observed runtime evidence
The exact runtime payload passed the following scoped check on Metal. The receipt binds its runtime input files. This is a functional smoke, not a quality benchmark, MTEB evaluation, coding evaluation, long-context test or MTP acceleration result.
{
"task": "text",
"runtime": "mlx-lm",
"version": "0.32.2",
"mlx_version": "0.32.4",
"cases": [
{
"expected": "42",
"final_answer": "42",
"output": "42",
"passed": true,
"prompt": "What is 19 plus 23? Reply with only the number."
},
{
"expected": "READY",
"final_answer": "READY",
"output": "READY",
"passed": true,
"prompt": "Reply with exactly the word READY."
}
]
}
| Runtime | Evidence for this artifact |
|---|---|
| MLX-LM 0.32.2 | Passed the task-specific smoke above |
| MLX-VLM | Not separately tested |
| AX Engine | Not tested; architecture metadata is not execution evidence |
| omlx | unsupported (static only) |
| mtplx | unsupported (static only) |
Unexercised modalities and MTP behavior remain unverified. Peer runtime-specific exports require distinct variants and their own testing. See the manifest-bound static report.
Use and provenance
python -m pip install -U huggingface_hub mlx-vlm
hf download AutomatosX/AX-Qwen3-Coder-Next-MLX-AXQ-6bit --local-dir ./AX-Qwen3-Coder-Next-MLX-AXQ-6bit
Pin the immutable Hub revision. Use the architecture-aware runtime above and preserve the source processor/template. The source license and notices are retained where supplied. The upstream repository and its license govern downstream use; no additional commercial grant or upstream benchmark/certification transfer is implied.
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6-bit
Model tree for AutomatosX/AX-Qwen3-Coder-Next-MLX-AXQ-6bit
Base model
Qwen/Qwen3-Coder-Next