---
base_model_relation: quantized
language: en
library_name: mlx
pipeline_tag: image-text-to-text
tags:
- mlx
- text-generation-inference
- apple-silicon
- 4-bit
- 8-bit
- qwen3_5
- mlx-vlm
base_model:
- prithivMLmods/Zenith-9B-CodeCore-Merge
license: apache-2.0
---

# **Zenith-9B-CodeCore-Merge-MLX**

> Zenith-9B-CodeCore-Merge is a merged 9B-parameter coding and reasoning model designed for long-horizon coding tasks, agentic coding, and agentic reasoning. It is built by merging [Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B) as the base model with [OxCoder-9B](https://huggingface.co/OrionLLM/OxCoder-9B), [Qwopus3.5-9B-Coder](https://huggingface.co/Jackrong/Qwopus3.5-9B-Coder), and [Ornith-1.5-9B](https://huggingface.co/ornith-ai/Ornith-1.5-9B), combining their capabilities for code generation, multi-step problem solving, instruction following, and autonomous coding workflows. The model is intended for complex software-engineering tasks that require sustained reasoning across multiple steps, code understanding, modification, debugging, and tool-oriented agentic workflows. This model is experimental and may generate artifacts.

- *GGUF: [Zenith-9B-CodeCore-Merge-GGUF](https://huggingface.co/prithivMLmods/Zenith-9B-CodeCore-Merge-GGUF). Note: The Multi-Token Prediction (MTP) heads are not preserved in this format. The model runs as a standard single-token-per-step autoregressive decoder.*

## Repository layout

```plaintext
+-- prithivMLmods/Zenith-9B-CodeCore-Merge-MLX (main)
    +-- / (Root: bf16)
    +-- 4bit/ (Quantized: 4-bit)
    +-- 8bit/ (Quantized: 8-bit)
```    


## Use with mlx

Install the required library:

```bash
pip install -U mlx-vlm
```

> **Model Note:** `Zenith-9B-CodeCore-Merge` is a 9-billion parameter multimodal coding model designed for code generation, visual debugging, repository reasoning, and architecture diagram analysis. It supports both text and image/screenshot inputs.

### BF16 Variant (Base Weights)

The full-precision BF16 files reside directly in the root of the repository:

#### CLI (Terminal)

```bash
python -m mlx_vlm generate \
  --model prithivMLmods/Zenith-9B-CodeCore-Merge-MLX \
  --max-tokens 512 \
  --temperature 0.0 \
  --prompt "Analyze this code screenshot, explain what it does, and fix any potential bugs or edge cases." \
  --image <path_to_image>
```

#### Python API

```python
from mlx_vlm import load, generate
from mlx_vlm.prompt_utils import apply_chat_template
from mlx_vlm.utils import load_config

model_path = "prithivMLmods/Zenith-9B-CodeCore-Merge-MLX"
model, processor = load(model_path)
config = load_config(model_path)

image = ["<path_to_image>"]
prompt = "Analyze this code screenshot, explain what it does, and fix any potential bugs or edge cases."
formatted_prompt = apply_chat_template(processor, config, prompt, num_images=len(image))

output = generate(
    model, 
    processor, 
    formatted_prompt, 
    image=image, 
    max_tokens=512, 
    temperature=0.0
)
print(output.text)
```

### 8-bit Variant

Target the `8bit` subfolder:

#### CLI (Terminal)

```bash
python -m mlx_vlm generate \
  --model prithivMLmods/Zenith-9B-CodeCore-Merge-MLX/8bit \
  --max-tokens 512 \
  --temperature 0.0 \
  --prompt "Analyze this code screenshot, explain what it does, and fix any potential bugs or edge cases." \
  --image <path_to_image>
```

#### Python API

```python
from mlx_vlm import load, generate
from mlx_vlm.prompt_utils import apply_chat_template
from mlx_vlm.utils import load_config

model_path = "prithivMLmods/Zenith-9B-CodeCore-Merge-MLX"
model, processor = load(model_path, subfolder="8bit")
config = load_config(model_path, subfolder="8bit")

image = ["<path_to_image>"]
prompt = "Analyze this code screenshot, explain what it does, and fix any potential bugs or edge cases."
formatted_prompt = apply_chat_template(processor, config, prompt, num_images=len(image))

output = generate(
    model, 
    processor, 
    formatted_prompt, 
    image=image, 
    max_tokens=512, 
    temperature=0.0
)
print(output.text)
```

### 4-bit Variant

Target the `4bit` subfolder:

#### CLI (Terminal)

```bash
python -m mlx_vlm generate \
  --model prithivMLmods/Zenith-9B-CodeCore-Merge-MLX/4bit \
  --max-tokens 512 \
  --temperature 0.0 \
  --prompt "Analyze this code screenshot, explain what it does, and fix any potential bugs or edge cases." \
  --image <path_to_image>
```

#### Python API

```python
from mlx_vlm import load, generate
from mlx_vlm.prompt_utils import apply_chat_template
from mlx_vlm.utils import load_config

model_path = "prithivMLmods/Zenith-9B-CodeCore-Merge-MLX"
model, processor = load(model_path, subfolder="4bit")
config = load_config(model_path, subfolder="4bit")

image = ["<path_to_image>"]
prompt = "Analyze this code screenshot, explain what it does, and fix any potential bugs or edge cases."
formatted_prompt = apply_chat_template(processor, config, prompt, num_images=len(image))

output = generate(
    model, 
    processor, 
    formatted_prompt, 
    image=image, 
    max_tokens=512, 
    temperature=0.0
)
print(output.text)
```

## License and Attribution

This model is based on and/or incorporates the following open-source projects and models:

* **Qwen3.5-9B (Base):** [https://huggingface.co/Qwen/Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B)
* **Zenith-9B-CodeCore-Merge:** [https://huggingface.co/prithivMLmods/Zenith-9B-CodeCore-Merge](https://huggingface.co/prithivMLmods/Zenith-9B-CodeCore-Merge)
* **mlx-vlm:** [https://github.com/Blaizzy/mlx-vlm](https://github.com/Blaizzy/mlx-vlm)
* **MLX:** [https://github.com/ml-explore/mlx](https://github.com/ml-explore/mlx)

This model is released under the [Apache License 2.0](https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/apache-2.0.md).