gemma 4 12B it 8bit

Gemma

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

Released June 2026context N/A12B params

A mid-sized multimodal model that handles both text and image inputs, quantized to 8-bit for reduced memory footprint. It trades some precision for accessibility, making it runnable on hardware that couldn't otherwise fit the full-precision version. Behavior reflects Gemma 4's underlying capabilities, with the MLX-community packaging optimizing it for Apple Silicon workflows.

Capabilities

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

Multimodal

Strong

Factual Knowledge

Strong

Reasoning & Logic

Use Case Fit

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

gemma 4 12B it 8bit

Gemma

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

Released June 2026context N/A12B params

A mid-sized multimodal model that handles both text and image inputs, quantized to 8-bit for reduced memory footprint. It trades some precision for accessibility, making it runnable on hardware that couldn't otherwise fit the full-precision version. Behavior reflects Gemma 4's underlying capabilities, with the MLX-community packaging optimizing it for Apple Silicon workflows.

Capabilities

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

Multimodal

Strong

Factual Knowledge

Strong

Reasoning & Logic

Use Case Fit

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

Glossary

AccessibilityDesigning technology so people with disabilities can use it effectively.Apple SiliconApple's custom-designed processors (like M1, M2, M3) optimized for running machine learning models on Mac computers.Full-PrecisionA model using standard 32-bit floating-point numbers to represent weights, providing maximum accuracy but requiring more memory.MLXA machine learning framework optimized for running models efficiently on Apple Silicon chips.Memory FootprintThe amount of RAM or storage space a model requires to run, which is critical for deployment on resource-constrained devices.MultimodalA model that can process and understand multiple types of input, such as both text and images.Multimodal ModelAn AI model that can process and understand multiple types of input data, such as video, images, and text together.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.