Instructions to use majentik/KAT-Coder-V2.5-Dev-MLX-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use majentik/KAT-Coder-V2.5-Dev-MLX-4bit 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/KAT-Coder-V2.5-Dev-MLX-4bit")

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/KAT-Coder-V2.5-Dev-MLX-4bit 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/KAT-Coder-V2.5-Dev-MLX-4bit"

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/KAT-Coder-V2.5-Dev-MLX-4bit"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

MLX LM

How to use majentik/KAT-Coder-V2.5-Dev-MLX-4bit 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/KAT-Coder-V2.5-Dev-MLX-4bit"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "majentik/KAT-Coder-V2.5-Dev-MLX-4bit"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "majentik/KAT-Coder-V2.5-Dev-MLX-4bit",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Hermes Agent

How to use majentik/KAT-Coder-V2.5-Dev-MLX-4bit 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/KAT-Coder-V2.5-Dev-MLX-4bit"

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/KAT-Coder-V2.5-Dev-MLX-4bit

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use majentik/KAT-Coder-V2.5-Dev-MLX-4bit 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/KAT-Coder-V2.5-Dev-MLX-4bit"

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/KAT-Coder-V2.5-Dev-MLX-4bit" \
  --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"

KAT-Coder-V2.5-Dev-MLX-4bit

File size: 1,956 Bytes

---
license: apache-2.0
base_model: Kwaipilot/KAT-Coder-V2.5-Dev
library_name: mlx
tags:
  - mlx
  - kat-coder
  - qwen3_5_moe
  - code
  - quantized
pipeline_tag: text-generation
---

# KAT-Coder-V2.5-Dev-MLX-4bit

MLX **4bit** (affine, group size 64) quantized
variant of [Kwaipilot/KAT-Coder-V2.5-Dev](https://huggingface.co/Kwaipilot/KAT-Coder-V2.5-Dev) for Apple
silicon via [mlx-lm](https://github.com/ml-explore/mlx-lm).

## Provenance

- Source: [Kwaipilot/KAT-Coder-V2.5-Dev](https://huggingface.co/Kwaipilot/KAT-Coder-V2.5-Dev) @ revision
  `7be56fe773e72b6f5ca93c1ae45d828ddb893922` (Apache-2.0).
- Quantized with `mlx_lm.convert` (mlx-lm 0.31.3): affine,
  4-bit, group size 64.
- **Text-only pack**: the upstream checkpoint is multimodal
  (`Qwen3_5MoeForConditionalGeneration`); mlx-lm's `qwen3_5_moe` loader
  drops the vision tower (`model.visual.*`) by design, so this pack
  ships only the text MoE. Use the upstream repo if you need vision.

## Smoke gate

Before upload this pack passed a deterministic coherence gate: greedy
64-token chat generation loaded through `mlx_lm.load`,
judged for emptiness, repetition loops, multi-script gibberish, and
special-token debris. Verdict: `ok`.

## Usage

```bash
pip install mlx-lm
mlx_lm.generate --model majentik/KAT-Coder-V2.5-Dev-MLX-4bit --prompt "Write a binary search in Python"
```

## Evaluation

| Benchmark | Score |
| --- | --- |
| arc_easy_acc | 0.7000 |
| hellaswag_acc | 0.5400 |

## Available tiers

| Repo | Quant |
| --- | --- |
| [majentik/KAT-Coder-V2.5-Dev-MLX-4bit](https://huggingface.co/majentik/KAT-Coder-V2.5-Dev-MLX-4bit) | 4bit |
| [majentik/KAT-Coder-V2.5-Dev-MLX-6bit](https://huggingface.co/majentik/KAT-Coder-V2.5-Dev-MLX-6bit) | 6bit |
| [majentik/KAT-Coder-V2.5-Dev-MLX-8bit](https://huggingface.co/majentik/KAT-Coder-V2.5-Dev-MLX-8bit) | 8bit |
| [majentik/KAT-Coder-V2.5-Dev-MLX-MXFP4](https://huggingface.co/majentik/KAT-Coder-V2.5-Dev-MLX-MXFP4) | MXFP4 |