For the fastest local setup of this model, Docker is the best choice.
Use the instructions provided below to complete the setup.
Then, simply start the container with the provided Docker command.
The **gemma-4-E4B-it-MLX-5bit** model represents a compact yet powerful addition to the Gemma family, optimized for on-device inference. Built on a 4ābillion parameter architecture, it leverages MLX optimizations to deliver high throughput while maintaining a minimal footprint. By employing 5ābit quantization, the model achieves a favorable balance between accuracy and memory usage, making it suitable for resourceāconstrained environments. Inference is tailored for interactive tasks, providing realātime responses with reduced latency compared to larger counterparts. The design incorporates advanced routing mechanisms that enhance contextual understanding without sacrificing speed. Overall, the **gemma-4-E4B-it-MLX-5bit** offers a compelling solution for developers seeking efficient AI capabilities in edge deployments.
| Parameters | 4āÆB |
| Quantization | 5ābit |
| Framework | MLX |
| Inference Type | IT (Interactive) |
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