To get this model running locally in no time, utilize the built-in WSL tools.
Execute the commands and steps outlined below.
An automated background process downloads all required large-scale files.
During setup, the script automatically determines and applies the best settings.
Gemma-4-E4B-it is a state‑of‑the‑art language model engineered for high‑efficiency inference on edge devices. It incorporates 2 B parameters and a 4 K context window, allowing nuanced comprehension while preserving low latency. The architecture leverages advanced quantization techniques to achieve sub‑2 ms token generation on consumer hardware. Its design includes multi‑head attention and grouped‑query attention, delivering strong performance across benchmarks such as MMLU and GSM‑8K. The model also supports seamless integration with developer tools through its open‑source API.
| Parameters | 2 B |
| Context Length | 4 K tokens |
| Quantization | INT4 |
| Throughput | >2000 tokens/s on GPU |
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