Ornith 1.5 9B MLX 8bit

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released August 2026context N/A

A compact, open-weight text model quantized to 8-bit precision for the MLX framework, making it suited for running locally on Apple Silicon hardware. The 9B parameter scale sits in a middle ground — more capable than smaller models but lighter than large frontier systems. Details about its specific strengths or behavioral tendencies are limited beyond its technical packaging.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Creative Writing

Moderate

Long Context

Moderate

Coding

Use Case Fit

Fit scores are AI-generated based on model capabilities, intended use, and technical specifications. Learn more

Ornith 1.5 9B MLX 8bit

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released August 2026context N/A

A compact, open-weight text model quantized to 8-bit precision for the MLX framework, making it suited for running locally on Apple Silicon hardware. The 9B parameter scale sits in a middle ground — more capable than smaller models but lighter than large frontier systems. Details about its specific strengths or behavioral tendencies are limited beyond its technical packaging.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Creative Writing

Moderate

Long Context

Moderate

Coding

Use Case Fit

Fit scores are AI-generated based on model capabilities, intended use, and technical specifications. Learn more

Glossary

8-bit PrecisionA quantization method that represents model weights using 8 bits instead of the standard 32 bits, reducing memory usage by approximately 75% while maintaining reasonable performance.Apple SiliconApple's custom-designed processors (like M1, M2, M3) optimized for running machine learning models on Mac computers.Bit PrecisionThe number of bits used to represent each number in a model; lower bit precision (like 3-bit) means smaller file size but potentially less accurate calculations.MLXA machine learning framework optimized for running models efficiently on Apple Silicon chips.MLX FrameworkA machine learning framework specifically designed for running AI models efficiently on Apple Silicon hardware.Parameter ScaleThe total number of trainable weights in a model, often expressed in billions (B); larger models generally have more capacity but require more computing power.PrecisionThe level of numerical detail a model uses to represent its internal values; higher precision means more accurate calculations but requires more memory.QuantizedA technique that reduces a model's size and memory usage by storing weights with lower precision (fewer bits), trading some accuracy for efficiency.Text ModelA language model that processes and generates only text, without support for images, audio, or other media types.