Run Gemma 4 E4B locally through Ollama, then use it as a coding assistant to complete a small, reviewable code task. The model is instruction-tuned, text-capable, and suited to text generation, coding, and reasoning; Ollama provides the documented local runtime and a 9.6 GB package for this model.
Run Gemma 4 E4B locally through Ollama, then use it as a coding assistant to complete a small, reviewable code task. The model is instruction-tuned, text-capable, and suited to text generation, coding, and reasoning; Ollama provides the documented local runtime and a 9.6 GB package for this model.
This setup uses the package documented for this task. Review its source and supported platforms before starting.
Save your machine in My Hardware to get an automatic starting choice. You can always choose any package yourself.
For the publisher's 9.6 GB Ollama text package at a short 4K context, we estimate at least 16 GB GPU memory or 24 GB Apple unified memory. For a more comfortable starting point, use 24 GB GPU memory or 32 GB unified memory. These are capacity estimates, not speed tests; longer context and other apps need additional headroom.
Pick your operating system. Every command below is for the selected package and runtime.
Install Ollama for this operating system before running the model command.
Install Ollama from the official download for your operating system. After installation, confirm the Ollama command is available in a new terminal and that the background service is running. This provides the runtime that executes the Gemma model.
Pull and launch the exact model package. The first run downloads the 9.6 GB package, then starts an interactive session in your terminal where you can chat with the model. Keep this session open for the next step.
ollama run gemma4:e4bIn the interactive Ollama session, type the following prompt and press Enter. This gives the model a small, reviewable coding task: write a pure function with a clear input, output, and edge case, and ask for a short usage example. Wait for the model to generate the code.
Read the generated code from the previous step. Confirm that it includes the requested function, that the logic handles the stated edge case, and that the usage example calls the function correctly. The model response is the setup result you verify, not just the fact that the Ollama server or session started.
Ask for a self-contained example, run it in a disposable file, and inspect the code and output before using it in a real project.
This is a source-linked setup, not a YouRunAI hardware test. Confirm your exact runtime version, package, and output before relying on it.
Close and reopen your terminal so the updated PATH is loaded, then try the command again. If it is still missing, reinstall Ollama using the official installer for your operating system.
Confirm you have at least 9.6 GB of free disk space and a stable internet connection, then run `ollama run gemma4:e4b` again. Ollama resumes the download when possible.
The model is a 9.6 GB package and may be memory-bound on a CPU-only machine. For faster responses, use a machine with a supported GPU and enough VRAM to hold the loaded model.
Restate the function name, input type, output type, and edge case in a new prompt in the same session. Gemma 4 E4B is an instruction-tuned model, so more specific constraints usually produce a closer match.
Original instructions, model files, and compatibility notes behind this setup.
Save your machine to see a personalized rating and its reasoning.
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