Qwen3.5 122B A10B 8bit

Qwen 3

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

Released February 2026context N/A122B params

A large mixture-of-experts model from the Qwen 3 family, quantized to 8-bit precision and optimized for Apple Silicon via the MLX framework. It activates around 10 billion parameters per forward pass despite having 122 billion total, keeping inference costs manageable. Handles both text and image inputs, making it multimodal out of the box.

Capabilities

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

Coding

Moderate

Instruction Following

Moderate

Reasoning & Logic

Use Case Fit

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

Qwen3.5 122B A10B 8bit

Qwen 3

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

Released February 2026context N/A122B params

A large mixture-of-experts model from the Qwen 3 family, quantized to 8-bit precision and optimized for Apple Silicon via the MLX framework. It activates around 10 billion parameters per forward pass despite having 122 billion total, keeping inference costs manageable. Handles both text and image inputs, making it multimodal out of the box.

Capabilities

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

Coding

Moderate

Instruction Following

Moderate

Reasoning & Logic

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.Forward PassA single computation cycle where input data flows through the model's layers to produce an output prediction.InferenceThe process of running a trained model to generate predictions or outputs from new inputs.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.MultimodalA model that can process and understand multiple types of input, such as both text and images.ParametersThe learned numerical values in a model — more parameters generally means more capacity but higher compute cost.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.