majentik/harrier-oss-v1-0.6b-MLX-4bit

Harrier-OSS-v1-0.6B MLX 4-bit

MLX 4-bit quantization of microsoft/harrier-oss-v1-0.6b, produced with mlx-embeddings on Apple Silicon.

What is this?

Harrier-OSS-v1 is Microsoft's state-of-the-art multilingual text embedding model family (Mar 2026). This 0.6B variant uses a Qwen3 backbone with sentence-transformers dense projection heads. Top-tier MMTEB multilingual performance (~74.3 average) under a fully-permissive MIT license.

Quantization

• —Method: MLX affine quantization (mlx_embeddings.convert), group_size=64
• —Bits per weight: 4
• —Output size: 334M

Quickstart

from mlx_embeddings import load

model, tokenizer = load("majentik/harrier-oss-v1-0.6b-MLX-4bit")
inputs = tokenizer(["query: what is Harrier-OSS?", "passage: Harrier-OSS is a text embedding model..."],
                   padding=True, truncation=True, return_tensors="mlx")
outputs = model(inputs["input_ids"], attention_mask=inputs["attention_mask"])
embeddings = outputs.text_embeds  # L2-normalised
print((embeddings[0] @ embeddings[1:].T).tolist())

Specifications

License

MIT — inherited from the upstream Harrier-OSS-v1 model.

See also

• —Base: microsoft/harrier-oss-v1-0.6b
• —mlx-embeddings: https://github.com/Blaizzy/mlx-embeddings
• —Garden hub: majentik/garden