Google, my favourite tech firm for reasons exactly as this one, has done it once again. It has got the worldwide community of developers supercharged with one new product. This one is called Gemma 4.
What’s the hype? Well, a completely open-source model that competes with AI models 20 times its size. And this one isn’t just your regular AI chatbot. It has been custom-built for advanced reasoning and agentic workflows. Meaning, AI handles your entire tasks, on your system, even without the need for the internet.
Your personal LLM, if you will.
Of course, that was enough to get AI-savvy people across the world to try their hands on it. And the results are nothing short of revolutionary. Here, I share a list of some of the top such projects, which are simple yet effective use cases that people have managed to bring to life, all thanks to Gemma 4.
But before we dive in, here is a little about the new AI model by Google for those unaware.
As I mentioned, Gemma 4 is not just another model you open for chat and close five minutes later. Google calls it its most intelligent open model family yet. And all this firepower is meant to think through multi-step tasks, work with tools, generate code, and run on your own hardware. That alone is enough to make the developers sit up straight.
And then comes the part that really fuels the hype: Google says Gemma 4 delivers unusually high intelligence for its size. It comes in 4 sizes, with the larger models ranking among the top open models in the world while competing with systems far bigger than them. That means developers are suddenly getting a model that feels powerful, flexible, and actually usable for real projects. Open, multimodal, agent-ready, and light enough to run in places where frontier AI usually does not. That is exactly why Gemma 4 is starting to feel less like a model release and more like a shift.
You can learn all about the new Gemma 4 here.
For now, we shall look at how developers around the world are putting the capable model to use.
This was a proper “wait, you can do that?” moment for me.
A developer showed how to use Claude Code coding workflows with Gemma 4 running locally on your machine. Which basically means you get Claude’s coding assistant on your own laptop, without paying per prompt and without constantly depending on the cloud. The setup uses Ollama to run Gemma 4 locally, and the tweet frames it as a beginner-friendly process that takes roughly 15 minutes on a laptop.
Why is this cool? Because it turns Gemma 4 from “another AI model release” into something instantly practical. Instead of treating AI like a chatbot tab you open and close, you can plug it into a coding workflow and let it help with writing, fixing, and understanding code right on your system. And yes, the whole appeal here is exactly what got people hyped about Gemma in the first place: no subscriptions, no API key drama, more privacy, and much more control.
— m0h (@exploraX_) April 7, 2026how to run claude code with gemma 4 completely free (beginner's guide):
this guide shows you how to use claude code completely free with gemma 4, no subscriptions &no api keys.
just your laptop + 15 mins setup.
this lets you run open-source models (like google’s gemma)… pic.twitter.com/Urxa19MI8w
What is happening here?
In very simple terms:
The basic setup looks like this
When I said ‘your personal LLM’, this was the Gemma 4 project I was referring to.
Imagine an AI model in your pocket. No internet, no cloud connection, and no monthly fee. Sharbel on X showed just that – Gemma 4 running directly on an iPhone. That means the AI model is not sitting on some remote server waiting for your request. It is right there on the phone, handling tasks locally like a pocket-sized brain.
— Sharbel (@sharbel) April 7, 2026🚨 Running Google's Gemma 4 on my iPhone… without internet
No data plan. No cloud. No monthly fee.
Gemma 4 runs completely offline, handles 128K context, and fits in my pocket.
Here's how I set it up in under 1 minute: pic.twitter.com/O1pSIbFWJ2
The flow is simple and wild at the same time:
That opens the door to all kinds of personal AI experiences. Think private assistants, offline study tools, local note analysis, or even agentic workflows on the go. And that is exactly why Gemma 4 has people so excited.
In case your local LLM on your iPhone wasn’t enough, here comes Gemma 4 running on a Nintendo Switch. Yes, an actual gaming console. maddiedreese shared Gemma 4 running locally on the device at around 1.5 tokens per second. That speed is obviously not built for high-pressure office work, but that is not the point here. The point is that a modern multimodal, agent-ready model can now be squeezed into places where AI was never really expected to live.
And that is exactly why this use case hits so hard. The workflow itself is simple in spirit:
Gemma 4 is making one thing very clear here: powerful AI is leaving the cloud and entering personal devices in all kinds of bizarre, wonderful ways. At this rate, developers are basically treating every screen around them like a potential home for an LLM.
This is where things start getting seriously fun. ai_for_success showed Gemma 4 E2B being used for audio transcription on a Pixel 10 Pro. In plain English, that means your phone can listen to a short audio clip and turn it into text, locally, without needing a big cloud setup that sends every request back and forth. The post notes that it supports up to 30 seconds for now, which may sound small, but honestly, even that is enough to show where this is heading.
Why is this exciting? Because it takes AI out of the “chatbot box” and turns it into something your device can do in the real world. The flow is beautifully simple:
Imagine the possibilities it opens up: quick note-taking, voice memos, meeting snippets, lecture highlights, or even just converting your random burst of genius into text before it disappears. It is not a full-blown studio transcription yet. But as a glimpse of what small, local AI can already do on a phone, this is absolutely wild.
This one is pure power-user energy. jessegenet shared Gemma 4 31B running on a Mac Studio, hooked up to OpenClaw, and the line that really jumps out is this: “$0 in token expenses now.” That is the dream, isn’t it? A serious local AI setup that can chat, reason, and run workflows on your own machine, feeling that constant token-ticking in the back of your head.
— Jesse Genet (@jessegenet) April 3, 2026It’s happened.
Mac Studio is here. Gemma 4 31b @GoogleDeepMind installed, chatting with my main @openclaw for $0 in token expenses now…
I've burned $5-6k on tokens on my crazy ideas over past few months, so this mac studio should pencil out for me within 3 months or so 🤓 pic.twitter.com/OV3ebyprVd
What is happening here is actually very simple:
Why this is such a big deal: most people experience AI through a website or app. This setup flips that completely. Instead of going to the AI, the AI lives with you, right on your machine. Ready for longer chats, custom workflows, private work, and repeated use without per-prompt pricing pressure from a hosted provider. That is when Gemma 4 starts looking less like “another model launch” and more like the beginning of a proper personal AI workstation.
This one is much like a full-time AI assistant that is way smarter than the standard AI chatbots you use every day. measure_plan built an app that combines Gemma 4’s vision capabilities with Roboflow’s RF-DETR. The result is a browser-based setup that can look at what your camera sees and make sense of it in real time. We can learn from the post that Gemma handles the actual understanding, while RF-DETR does the first-pass object detection. In other words, one model spots what is in the frame, and the other explains what is going on.
— AA (@measure_plan) April 7, 2026i gave a voice to my jarvis system
everything running in real-time using open source models
– roboflow RF-DETR for object detection
– gemma 4 for scene summarization
– kokoro text-to-speech
– live in the browser using transformers jsprompt: "you are a dystopian science… https://t.co/kiE8FAmApz pic.twitter.com/UjJlSS6yu2
That combo opens up a lot of fun possibilities really fast:
The super-cool project shows Gemma 4 doing way more than chatting or coding. It is starting to act like a visual brain. Point your camera somewhere, and the system can begin identifying what is there, following the scene, and describing it back in the language of your choice. Now imagine such a system as an assistive tool or a smart camera app that helps guide you through a process that is completely new to you. The possibilities are simply wild.
Imagine an AI that checks your calendar at the start of the day, and then sends messages that need to be sent to your contacts, without you even typing a word. OsaurusAI created exactly this in a project with Gemma 4 26B. Running locally at around 50 tokens per second, the AI was able to read a calendar and text contacts. That is a big jump from “AI can chat” to “AI can actually do things for me.”
The idea is simple:
Why this matters: once a model can move this fast locally, it stops feeling like a demo and starts feeling like a real personal agent. The kind that can check your schedule, find the right person, and help you take action instantly. All of this, without sending every little request to the cloud.
This is the kind of demo that makes developers grin. UnslothAI showed Gemma 4 E4B (4-bit) completing a full repo audit by executing Bash commands and tool calls locally. The wild part is that it reportedly runs on just 6GB RAM. That is not “AI writes one helper function.” That is AI stepping through a real codebase, using tools, and helping inspect the whole thing, just like a mini coding agent on your own machine would.
The setup is beautifully simple:
This one is much more relatable as it shows Gemma 4 doing actual developer work, not just code autocomplete cosplay. And the fact that it can happen on such modest hardware is exactly what makes Gemma 4 feel so disruptive. Powerful AI is one thing. Powerful AI that fits into ordinary machines is a revolution in itself.
This one is a useful feature that Google itself introduced along with the Gemma 4. Omar Sanseviero, who is the Developer Experience Lead at Google DeepMind, announced Agent Skills for Gemma 4 on X recently. Much as the name suggests, Agent Skills work exactly like the skills we have seen with Claude or other AI models. It is an Android app experience launched with Gemma 4, where you can import different skills and let Gemma 4 E2B reason through and use them directly on-device. That means your phone is not just chatting back. It is starting to behave more like a real local agent.
— Omar Sanseviero (@osanseviero) April 2, 2026As part of the Gemma 4 release, we're launching Agent Skills: an Android app experience where you can import different skills and have Gemma 4 E2B reason and use the skills!
Running entirely in the phone, available in the Google PlayStore. Try it now! pic.twitter.com/UFvptXxFsw
What makes this exciting is how simple the idea is:
Agent Skills takes Gemma 4 beyond chatbot territory and into something much more useful: AI that can actually do things on your phone, not just talk about them. And because it runs on-device, it also pushes the whole “personal AI” idea much closer to reality.
I’ve kept the most fun for the last. Once you are done using the new Gemma model for all your work, it is time to have some fun with it. ai_for_success, in his X post, shares how to do just that. He built an agent skill that lets Gemma 4 E2B call Lyria 3 and generate songs. Yes, actual songs. The post says it works for image-to-song, which means you can show the system a visual, let Gemma understand it, and then have it trigger music generation around that vibe.
— AshutoshShrivastava (@ai_for_success) April 3, 2026I built an agent skill that lets the Google new Gemma 4 E2B model call Lyria 3 and generate songs .
It works for:
– Image to song
– Text to songI’m using Google AI Edge Gallery.
I’ve added the skill link below, you can use it directly. You’ll just need your own API key, which… pic.twitter.com/hQ79Q7OxHb
The flow is super simple:
Why is this such a cool final example? Because it shows Gemma 4 doing what all great agentic models should do: not just answer prompts, but help create something new. One minute, it is reading images. The next minute, it is making music out of them. That is a creative that shows a lot of human touch to it.
Also Read:
These projects show exactly why Gemma 4 feels bigger than a normal model launch.
From coding assistants and offline iPhone LLMs to video understanding, repo audits, agent skills, and even image-to-song generation, developers are already stretching it in all directions. Practical, or for pure fun, Google’s new launch has become the go-to AI model within days of its launch. And all of this, for one very potent reason – it runs locally, all for free.
Such widespread traction early on is usually the clearest sign that a product has landed well. People do not just test it, they start building with it. More importantly, Gemma 4 is showing what the next phase of AI could look like: more personal, more local, more controllable, and far less dependent on giant cloud setups for any of your projects.
Of course, these are the early experiments. The real wave of Gemma 4 projects may only just be getting started. So make sure you stay tuned to this space for more such updates on the new Gemma model.
Technical content strategist and communicator with a decade of experience in content creation and distribution across national media, Government of India, and private platforms
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