LLM model: Gemma 4 12B

What Local AI Models Can a Regular Computer Run?

Token generation speeds were measured for Gemma 4 E2B, Gemma 4 12B, gpt-oss 20B, Gemma 4 26B, Qwen 3.6 35B, and Qwen 3.8 27B using Ollama on a Geekom A9 Max mini PC with 32 GB RAM.

IBM Granite 4.2 vs Qwen 3.8 27B vs Gemma 4 - Local LLM Benchmark

Benchmark IBM Granite 4.2, Qwen 3.8 27B, Gemma 4, and Ornith 1.5 on an RTX 5090, measuring KV cache cost, usable context, generation speed, coding, math, and tool calling via Python tests.

Gemma 4 12B Coder Tested: Where Small Local Models Break

Tests Gemma 4 12B Coder locally on MacBook M4 Pro using Ollama and Pi agent via color palette generator, pixel art editor single prompts, and step-by-step development across 18 tasks.

LLM Battle 2 - Qwen, Ornith, Qwythos, Gemma 4

Qwen, Ornith, Qwythos, and Gemma 4 compete in a two-round battle using easy and challenging prompts to demonstrate the importance of writing a good prompt.

Can a 3.5GB model replace my 35B daily driver? (Bonsai 27B)

Tests Bonsai 27B binary and ternary variants against Qwen 3.6 35B-A3B and Gemma 4 12B on an RTX 3060 using llama.cpp, measuring generation speed, total memory footprint, and performance on web design

Gemma 4's Big Update in 4-Bit QAT — Low VRAM, Local

Tests major Gemma 4 update with QAT GGUF, covering tool-calling fix, FA4 support, and vision token control.

Can this TINY $399 ZimaBoard 2 Run Local AI? 🔥 (Ollama & Llama.cpp)

Tests Ollama and Llama.cpp running inside Docker on ZimaBoard 2, evaluating speed using Gemma-4 with Vision and GPT-OSS from OpenAI, plus an endurance thermal throttle check.

LLM battle 1

Qwen 3.6 and Gemma 4 variants are tested to design and build a full-screen visualizer using MusicPlayer, with results hosted in the ext-mp-ai-visualizers repo.

Ornith-1.0 9B vs Gemma4 12B: Local AI Model Showdown

Tests Ornith-1.0-9B versus Gemma-4-12B in local AI coding tasks to evaluate whether Ornith's benchmark scores align with real-world performance.

Gemma4 12B Coder - Composer 2.5 × Fable 5 v2 vs base - 16GB Local LLM setup

Tests Gemma 4 12B finetune with Fable 5 and Composer 2.5 against base via Q4_K_M quant on 16GB VRAM using Performance, Memory, Agency, OpenAI Human Eval, Sand Physics and Dungeon Crawler benchmarks.

Google QAT vs Unsloth QAT + MTP - Which Gemma 4 12B Is Actually Better?

Compares Google QAT and Unsloth QAT + MTP using identical QAT base weights and MTP setup to evaluate performance differences where the quantization method is the sole variable.

Gemma4 12B vs 12B QAT | 16GB vRAM Head to Head

Compares Gemma4 12B and Gemma4 12B QAT via VPS Dashboard Setup, Tower Defense Game addition, and Chat Client Build to evaluate instruction following, UI cleanliness, reliability, and usability under f

Gemma 4 Was Broken for Agents - Google Just Fixed It

A bug fix in Gemma 4's chat template resolves issues that were silently degrading multi-turn agent performance.

Gemma4 12B vs 12B QAT | 16GB vRAM Head to Head Battle

Compares Gemma4 12B and Gemma4 12B QAT via iOS UI Clone, Weather Dashboard, and Broken Code Debug + Repair Challenge using single-file HTML, CSS, and JavaScript tests.

The Best Free Local AI on Windows: LM Studio, Gemma 4, VS Code (HOWTO in 5 Minutes)

Demonstrates running Gemma 4 12B QAT locally via LM Studio on Windows PCs with 8GB VRAM, integrated into VS Code using the Continue extension for offline coding assistance.

Gemma 4 12B QAT vs non-QAT - 16GB VRAM Local LLM setup

Compares Unsloth’s q4 QAT and regular q4 GGUF variants of Gemma 4 12B on adherence, agency, coding, and memory using a 16GB VRAM system.

Gemma 4 12B QAT + MTP on llama.cpp Locally - Twice the Speed, Same Quality?

Stacks Google's QAT quantization with llama.cpp's MTP support to run Gemma 4 12B at double the speed locally.

Google QAT vs Unsloth Q4_0 - Which Gemma 4 12B Quantization Is Better?

Tests Google QAT versus Unsloth Q4_0 quantized versions of Gemma 4 12B at identical file sizes to determine which approach yields better results.

Gemma 4 12B Quant Comparison - q8 vs q4 - 16GB VRAM Local LLM setup

Tests Gemma 4 12B q8 vs q4 quantizations on a system with 16GB VRAM and 32GB DDR4 RAM across performance, memory, coding, and agency benchmarks using unsloth/gemma-4-12b-it-GGUF.

Gemma 4 12B Is INCREDIBLE! BEST Local AI Coding Model! IS POWERFUL! (Fully Tested)

Tests Gemma 4 12B's encoder-free multimodal architecture, coding, reasoning, and Three.js generation via World of AI Bench, comparing it against Qwen3.6-35B-A3B.

Gemma4 12B in Quantization-Aware Training (QAT) with Ollama - Full Testing

Locally installs and tests Gemma 4 12B QAT via Ollama using coding demos, multilingual translation, creativity, and situation demonstrations.

Gemma4 12B IT vs Qwen3.5 9B |16GB vRAM Head to Head

Evaluates instruction adherence, UI cleanliness, functionality, and interactivity using single-file HTML/CSS/JavaScript tests: iPhone Replica, Top-Down Car Game, and Live Weather Dashboard.

Gemma 4 12B Reviewed and Tested - 16GB Local LLM setup

Evaluates unsloth/gemma-4-12b-it-GGUF on a system with 16GB VRAM and 32GB DDR4 RAM across memory, agency, reasoning, implementation, audio and vision tasks.

Gemma4 12B vs Qwen3.6 27B — The Veteran vs The Newcomer

Compares Gemma4 12B against Qwen3.6 27B using the same GPU setup.

Google's Gemma 4 12b is CRAZY good and only needs 8gb (Day ZERO Testing)

Tests Gemma-4-12b-it vision, security via Splunk CTF and AWS S3 investigation with Anvor AI, tool-calling, and building a game with Pi on NVIDIA or AMD GPUs.

Gemma 4 12B Is INSANE – Is THIS the BEST Local Coding Model Yet?

Tests Gemma 4 12B via local setup config and practical evaluations including browser OS, 3D printer simulation, image to SVG, scene generation, multimodal websites, wireframe to site, and OpenCode tas

Gemma 4 12B - Google's Unified Multimodal Model Running Locally

Locally installed Gemma 4 12B encoder-free model demonstrates unified architecture through text inference, coding, multilingual translation, image understanding, OCR, and audio transcription demos.