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Google may have just released one of the most practical local AI models yet. In this video, I fully test the brand-new Gemma 4 12B model and see how it stacks up against other popular open-source models.
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Blog Post:
https://blog.google/innovation-and-ai/technology/developers-tools/introducing-gemma-4-12B/
Gemma Announcement Post:
https://x.com/googlegemma/status/2062202706882883696
Gemma 4 Q:
https://x.com/ollama/status/2062965815864066079
Unsloth:
https://x.com/UnslothAI/status/2062470072179044447
Ollama:
https://ollama.com/library/gemma4
https://x.com/analogalok/status/2062908393816510813
We cover its new encoder-free multimodal architecture, coding performance, reasoning capabilities, Three.js generation, local deployment requirements, quantized versions, and whether it can truly run on everyday consumer hardware. I also share my own benchmark results from World of AI Bench and compare it against models like Qwen3.6-35B-A3B.
Is Gemma 4 12B the new king of local AI? Let's find out. 🔥
⏱️ Topics Covered
✅ Gemma 4 12B Overview
✅ Encoder-Free Multimodal Architecture
✅ Coding & Agentic Workflows
✅ Three.js Generation Tests
✅ Local AI Performance
✅ Quantization-Aware Training (QAT) Models
✅ VRAM & Hardware Requirements
✅ World of AI Benchmark Results
✅ Qwen vs Gemma Comparison
✅ Real-World Use Cases
[Time Stamps]:
0:00 - Introductions
0:54 - Google's New Focus
1:26 - Gemma 4 12B vs 26B
2:20 - Which Model To Run?
3:56 - Performance Will Get Better
4:29 - Benchmarks
4:50 - Native Audio/Vision
5:06 - System Requirements
5:33 - Gemma 4 QAT Weights
6:01 - How To Setup
7:09 - Running Benchmark
7:21 - Frontend Demos
9:28 - Minecraft Clone
9:56 - OS Clone
10:33 - SVG
12:17 - Three,js
13:12 - Two Cents
#AI #Gemma4 #GoogleAI #LocalAI #OpenSourceAI #LLM #MachineLearning #ArtificialIntelligence #CodingAI #Gemma12B
Additional Tags:
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