---
license: mit
base_model: ornith-ai/Ornith-1.5-9B
base_model_relation: quantized
language:
- en
library_name: mlx
pipeline_tag: text-generation
tags:
- mlx
- mtplx
- mtp
- speculative-decoding
- apple-silicon
- 4-bit
---

# Ornith-1.5-9B-MTPLX-4bit

A 4-bit affine quantization of [ornith-ai/Ornith-1.5-9B](https://huggingface.co/ornith-ai/Ornith-1.5-9B) for Apple Silicon, exported with [MTPLX](https://github.com/youssofal/MTPLX) 2.12.2. The native MTP head and vision tower are included in BF16.

## Quantization and files

| Component | Format | File | Size |
| --- | --- | --- | --- |
| Language model | 4-bit affine, group size 64; unquantized tensors in BF16 | `model.safetensors` | 5.038 GB |
| Native MTP head | BF16, one layer | `mtp.safetensors` | 0.487 GB |
| Vision tower | BF16 | `model-vision.safetensors` | 0.912 GB |

The complete download is approximately **6.46 GB (6.01 GiB)**. The tokenizer, chat template, processor configurations, weight index, and MTPLX runtime contract are included.

All 250 packed language-model weight matrices were checked to use 4 bits. The MTP head is preserved in BF16 with the Forge recipe `mtp_policy: keep_bf16`.

## Usage

Install MTPLX following the [official project instructions](https://github.com/youssofal/MTPLX), then download this repository with the Hugging Face CLI:

```sh
hf download 0xzknw/Ornith-1.5-9B-MTPLX-4bit \
  --local-dir ./Ornith-1.5-9B-MTPLX-4bit

mtplx start cli --model ./Ornith-1.5-9B-MTPLX-4bit
```

For one completion using native MTP:

```sh
mtplx run --model ./Ornith-1.5-9B-MTPLX-4bit \
  --prompt "Write a Python function that reverses a string." \
  --max-tokens 512 --mtp --depth 3
```

The included runtime contract recommends the `sustained` profile and supports MTP depths up to 3. Its sampler defaults are temperature 0.6, top-p 0.95, and top-k 20. Run `mtplx tune --model ./Ornith-1.5-9B-MTPLX-4bit --retune` to measure performance on your Mac.

## Provenance

- Source model: [ornith-ai/Ornith-1.5-9B](https://huggingface.co/ornith-ai/Ornith-1.5-9B).
- Source revision: [`489cb97981b8654bcfcf30ce1f94ed1b62e07b53`](https://huggingface.co/ornith-ai/Ornith-1.5-9B/tree/489cb97981b8654bcfcf30ce1f94ed1b62e07b53).
- Exported with MTPLX 2.12.2 on October 4, 2026.
- This repository publishes the first local 4-bit export. The weight files and tokenizer are preserved unchanged from that export; publication metadata uses portable paths.

## Validation and scope

The 1,275 tensor shapes and byte ranges were checked, including the 15 MTP tensors and 333 vision tensors. All 1,260 entries in the main weight index match the language and vision files. Local Forge verification covers autoregressive text generation and MTP depths 1, 2, and 3; the detailed runtime record is in `mtplx_runtime.json`.

Image and video inference were not separately tested for this publication. No independent downstream accuracy benchmark is claimed for this quantization; upstream benchmark scores describe the original model.

## License

MIT, following the license declared by the [upstream model card](https://huggingface.co/ornith-ai/Ornith-1.5-9B). Credit for the original model belongs to the Ornith team; MTPLX provides the conversion and inference tooling.