--- license: apache-2.0 base_model: ornith-ai/Ornith-1.5-9B-MLX base_model_relation: quantized library_name: mlx pipeline_tag: text-generation language: - en tags: - mlx - optiq - quantized - 4bit - mixed-precision - qwen3.5 - reasoning - long-context - function-calling - tool-use - agentic - apple-silicon --- # mlx-community/Ornith-1.5-9B-OptiQ-4bit > **Built with [mlx-optiq](https://mlx-optiq.com)**, the MLX-native toolkit to quantize, fine-tune, and serve LLMs locally on Apple Silicon, no PyTorch and no cloud. [All OptiQ quants](https://mlx-optiq.com/models) ยท [Docs](https://mlx-optiq.com/docs/) OptiQ mixed-precision quant of [ornith-ai/Ornith-1.5-9B-MLX](https://huggingface.co/ornith-ai/Ornith-1.5-9B-MLX), a 9B reasoning model. 7 GB on disk. ## What it is | Property | Value | |---|---| | Base | ornith-ai/Ornith-1.5-9B-MLX (Qwen3.5, 9B, 32 layers) | | Method | OptiQ mixed-precision, per-layer 4/8-bit | | Bit allocation | Reused from the [Ornith-1.0-9B OptiQ recipe](https://huggingface.co/mlx-community/Ornith-1.0-9B-OptiQ-4bit): same architecture and layer count, so the per-layer sensitivity ranking transfers directly and no per-model sweep is needed | | Layer split | 116 components at 4-bit, 134 at 8-bit | | Group size | 64 | | On disk | 7 GB | Following the naming `llama.cpp` uses for its mixed quants, the "4bit" label denotes the family, not the weighted average. ## Run it ```bash pip install "mlx-optiq>=0.4.28" ``` ```python import optiq # registers the arch from mlx_lm import load, generate model, tok = load("mlx-community/Ornith-1.5-9B-OptiQ-4bit") prompt = tok.apply_chat_template( [{"role": "user", "content": "Explain mixed-precision quantization in two sentences."}], tokenize=False, add_generation_prompt=True, ) print(generate(model, tok, prompt=prompt, max_tokens=400)) ``` For an OpenAI- and Anthropic-compatible endpoint with mixed-precision KV cache: ```bash optiq serve --model mlx-community/Ornith-1.5-9B-OptiQ-4bit ``` This is a reasoning model, so give it a generous token budget. ## Links - **Project website:** [mlx-optiq.com](https://mlx-optiq.com/) - **All OptiQ quants:** [mlx-optiq.com/models](https://mlx-optiq.com/models) - **Base model:** [ornith-ai/Ornith-1.5-9B-MLX](https://huggingface.co/ornith-ai/Ornith-1.5-9B-MLX)