Instructions to use AutomatosX/AX-Cyber-Tiel-Coder-35B-A3B-MLX-AXQ-MXFP8-MTP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AutomatosX/AX-Cyber-Tiel-Coder-35B-A3B-MLX-AXQ-MXFP8-MTP 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-Cyber-Tiel-Coder-35B-A3B-MLX-AXQ-MXFP8-MTP")

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-Cyber-Tiel-Coder-35B-A3B-MLX-AXQ-MXFP8-MTP 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-Cyber-Tiel-Coder-35B-A3B-MLX-AXQ-MXFP8-MTP"

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-Cyber-Tiel-Coder-35B-A3B-MLX-AXQ-MXFP8-MTP"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

MLX LM

How to use AutomatosX/AX-Cyber-Tiel-Coder-35B-A3B-MLX-AXQ-MXFP8-MTP 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-Cyber-Tiel-Coder-35B-A3B-MLX-AXQ-MXFP8-MTP"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "AutomatosX/AX-Cyber-Tiel-Coder-35B-A3B-MLX-AXQ-MXFP8-MTP"
# 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-Cyber-Tiel-Coder-35B-A3B-MLX-AXQ-MXFP8-MTP",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Hermes Agent

How to use AutomatosX/AX-Cyber-Tiel-Coder-35B-A3B-MLX-AXQ-MXFP8-MTP 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-Cyber-Tiel-Coder-35B-A3B-MLX-AXQ-MXFP8-MTP"

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-Cyber-Tiel-Coder-35B-A3B-MLX-AXQ-MXFP8-MTP

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use AutomatosX/AX-Cyber-Tiel-Coder-35B-A3B-MLX-AXQ-MXFP8-MTP 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-Cyber-Tiel-Coder-35B-A3B-MLX-AXQ-MXFP8-MTP"

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-Cyber-Tiel-Coder-35B-A3B-MLX-AXQ-MXFP8-MTP" \
  --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-Cyber-Tiel-Coder-35B-A3B-MLX-AXQ-MXFP8-MTP

File size: 912 Bytes

b68a546

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  "created_at": "2026-10-04T22:12:11.707592Z",
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    "BF16"
  ],
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    "sha256": "590e87c9c3fbbaa370c8dddbcc22611f00bbc78019d28e3192f180841c030527",
    "size_bytes": 1689387928
  },
  "parameters": 844640768,
  "role": "mtp",
  "schema_version": "axquant.protected-tensor-sidecar.v1",
  "source_files": [
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      "path": "model-mtp.safetensors",
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  ],
  "source_model": {
    "architecture": "Qwen3_5MoeForConditionalGeneration",
    "format": "mlx",
    "local_path": null,
    "model_id": "peculiar-ragdoll/Cyber-Tiel-Coder-35B-A3B-MLX-oQ6e-MTP",
    "revision": "a443d4e30fd5228942cb7695f916f4b14a88fae9"
  },
  "tensor_count": 785,
  "tensor_names_sha256": "f314fb9463ef9c7685e61dbbf5d5d3c49d95667c1059736c83b694d384d290c8"
}