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This review tests Gemma 4 12B as a local LLM for coding, mainly through LM Studio and OpenCode. The speaker uses an Apple Mac Studio M3 Ultra with 256 GB of memory and an 8-bit quantization. He cites a release claim that the model fits systems with 16 GB of VRAM or unified memory, describes its encoder-free audio and image input, and notes an Apache 2.0 license. He points to Unsloth's guide for sampling settings and thinking-mode instructions.
The coding tests produce mixed results. A browser desktop needs syntax repairs before its apps and small GTA-style scene work. Several 3D tasks repeat import-map errors and require manual help. The image-to-SVG result captures some colors and composition rather than a faithful replica. Website generation from image references earns a more favorable assessment, though layout and asset quality remain uneven.
In OpenCode, the model eventually builds a C++ skate game using Raylib after dependency installation and repeated file rewrites. A subway FPS remains partly functional after intervention. The speaker also uses ChatGPT to repair syntax and import issues in a flight simulator, so that result includes outside assistance.
The macOS Edge Gallery test demonstrates audio input, but the speaker encounters model-selection friction and a Python skill fails because uv is missing. His positive verdict rests chiefly on coding experiments. He does not test Q4 or establish that this is universally the best coding model.
