Scrimba
Scrimba

Published: April 4, 2026
Video Description
Gemma 4 is honestly one of the craziest open model drops we’ve seen. In this video, I put Google’s latest models through real tests not just benchmarks, but actual workflows. We’re talking frontend generation, agentic tool use, multimodal reasoning, and even running these models locally at speeds that shouldn’t be possible.
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📌 LINKS & RESOURCES
Blog Post: https://blog.google/innovation-and-ai/technology/developers-tools/gemma-4/
API: https://aistudio.google.com/u/1/prompts/new_chat
Kilo: https://kilo.ai/cli
Ollama: https://ollama.com/library/gemma4
HuggingFace: https://huggingface.co/collections/google/gemma-4
OpenRouter: https://openrouter.ai/google/gemma-4-31b-it
https://x.com/stevibe/status/2040039108748177706
https://x.com/ggerganov/status/2039752638384709661
The biggest surprise? It’s not just about being powerful it’s about being efficient. Gemma 4 is hitting near frontier-level performance while using way fewer tokens and running on real hardware like a Mac Studio.
I also break down:
• 31B vs 26B performance
• Real coding + UI generation tests
• Agent workflows running locally
• Multimodal capabilities in action
• Whether it actually beats Qwen in real usage
If you’re into open-source AI, local LLMs, or building with agents, this is a huge shift you need to understand.
[Time Stamp]:
0:00 - Introduction
1:16 - Running 3005/s on Mac M2
1:53 - Benchmarks
3:14 - How To Use
4:12 - MacOS Demo
5:52 - Frontend Demo 31B vs 26B
7:19 - F1 Donut Sim Demo
8:06 - Product Page Demo
8:49 - SVG Demo
9:32 - AirBNB Demo
9:50 - Game Dev Demo
10:21 - Mobile Demo
11:31 - Multimodal Demo
#AI #Gemma4 #OpenModels #LocalAI #LLM #GoogleAI #AIAgents #MachineLearning #Tech
tags:
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