Instructions to use AutomatosX/AX-Nemotron-3.5-Lightning-30B-A3B-MLX-AXQ-MXFP4-MTP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AutomatosX/AX-Nemotron-3.5-Lightning-30B-A3B-MLX-AXQ-MXFP4-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-Nemotron-3.5-Lightning-30B-A3B-MLX-AXQ-MXFP4-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-Nemotron-3.5-Lightning-30B-A3B-MLX-AXQ-MXFP4-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-Nemotron-3.5-Lightning-30B-A3B-MLX-AXQ-MXFP4-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-Nemotron-3.5-Lightning-30B-A3B-MLX-AXQ-MXFP4-MTP"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

MLX LM

How to use AutomatosX/AX-Nemotron-3.5-Lightning-30B-A3B-MLX-AXQ-MXFP4-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-Nemotron-3.5-Lightning-30B-A3B-MLX-AXQ-MXFP4-MTP"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "AutomatosX/AX-Nemotron-3.5-Lightning-30B-A3B-MLX-AXQ-MXFP4-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-Nemotron-3.5-Lightning-30B-A3B-MLX-AXQ-MXFP4-MTP",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Hermes Agent

How to use AutomatosX/AX-Nemotron-3.5-Lightning-30B-A3B-MLX-AXQ-MXFP4-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-Nemotron-3.5-Lightning-30B-A3B-MLX-AXQ-MXFP4-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-Nemotron-3.5-Lightning-30B-A3B-MLX-AXQ-MXFP4-MTP

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use AutomatosX/AX-Nemotron-3.5-Lightning-30B-A3B-MLX-AXQ-MXFP4-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-Nemotron-3.5-Lightning-30B-A3B-MLX-AXQ-MXFP4-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-Nemotron-3.5-Lightning-30B-A3B-MLX-AXQ-MXFP4-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"

Runtime format audit (2026-10-06)

No quantization-container correction was needed. This family has no n-gram tensors; no n-gram file or declaration was added. This remote format audit does not grant an oMLX/MTPLX runtime profile or a successful load/generation claim.

See runtime_audit.json for pinned config/index/header bindings, architecture, physical-format findings, and applied corrections. This is development evidence; no quality, MTP exactness, speed, or certification claim is added. Historical evidence stays bound to its original revision.

AX-Nemotron-3.5-Lightning-30B-A3B-MLX-AXQ-MXFP4-MTP

This repository contains an AXQuant development conversion of the pinned NVIDIA BF16 source. The main checkpoint uses standard MLX-LM config, tokenizer, index, and safetensors files. MXFP quantization is applied to eligible backbone weights; protected tensors keep their declared precision.

Source and format

Source: nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16
Immutable source revision: a9904d24bcc1d289a1950fa9d2b978c47cf903b9
AXQuant physical format: MXFP4
AXQuant plan and file hashes are included in this repository.
This is a development artifact; no quality certificate is claimed.

MTP payload

The source integrates Nemotron-H MTP tensors into its original checkpoint shards. AXQuant preserves those tensor payloads byte-for-byte in mtp.safetensors and records the source and payload digests in ax_nemotron_mtp_manifest.json. Runtime compatibility is unverified. This package does not claim MTP execution support in MLX-LM, AX Engine, MTPLX, or oMLX; each runtime owns that support.

Load the standard MLX backbone

from mlx_lm import load, generate
model, tokenizer = load("AutomatosX/AX-Nemotron-3.5-Lightning-30B-A3B-MLX-AXQ-MXFP4-MTP")
print(generate(model, tokenizer, prompt="Hello", max_tokens=32))

The example loads the text backbone. It does not load or activate the separate MTP payload. Super needs substantial memory; actual use depends on format, context, and runtime.

License and notices

The source uses OpenMDW License 1.1; its license and notices are included.

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Safetensors

Model size

32B params

Tensor type

U32

BF16

F32

MLX

Hardware compatibility

4-bit

Model tree for AutomatosX/AX-Nemotron-3.5-Lightning-30B-A3B-MLX-AXQ-MXFP4-MTP

Base model

nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16

Quantized

(114)

this model

Collections including AutomatosX/AX-Nemotron-3.5-Lightning-30B-A3B-MLX-AXQ-MXFP4-MTP