The promise of cutting-edge thinking from the Ge modelmini and its integration into the Google Workspace ecosystem is tempting. But to make everything work perfectly from Gemini has become a real virtual assistant, you have to pay. And the same applies to ChatGPT and its most advanced models. Which I don't really like. Fortunately, with the advent of a new generation of open models like Gemma 4 or Qwen 3.6, the options have expanded and the selection is much more diverse even without a subscription.
After experimenting with Gemini I decided to cancel. cloudnew tariff from Google and transferred her work and literally virtual life to a local infrastructure running on her own hardware. After a few weeks, I can say that I have my privacy under control again., the response speed has decreased significantly and my productivity has not suffered a single crack. However, there are more options you can use.
Gemma 4
Door Design Gemma 4, open-weight sibling of Gemini, has virtually erased the performance gap in my daily workflow. Its strength lies not in its universality, but in specializationIn my setup, I use two specific options that cover the full spectrum of my needs.
I have a model for mobile use Gemma 4 E2BIt's a masterpiece of mobile engineering that runs fully on Android. offline through Google AI Edge Gallery. Thanks miniWith minimal hardware requirements (approximately 1,5 GB of RAM is enough), it can quickly generate professional correspondence or summarize large PDFs even in places without a signal.
The moment I sit down at the computer with Windows, takes the reins Gemma 4 26B-A4BAlthough it has 26 billion parameters, thanks to its efficient architecture, it only uses 3,8 billion to calculate a single token. This allows me to perform in-depth analysis of technical data in real time.
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Qwen 3.6-27B
While Gemma takes care of the regular agenda, Qwen 3.6-27B holds the role of senior developer. For programmerswho want to eliminate addiction to cloudu, it is a groundbreaking tool. Its main advantage is agent fluency. The model does not only work at the line level of code, but understands the context the entire repository.
Thanks to the deployment over LM Studio using GPU acceleration, it achieves almost instant response. ExcelIt is in the Terminal-Bench benchmark, making it an ideal companion for task automation.
Ministerial 3 3B
If you are looking for speed that cloudpushes the old models into the background, there is Ministerial 3 3BThis compact model is proof that size doesn't matter as much as training efficiency. I have it pinned to my dashboard for hundreds of small tasks, which would otherwise unnecessarily consume time and tokens of large models.
Despite his subtlety, the ministroller maintains a surprising contextual coherence even in longer conversations. His answers are impressive. forever and technically, without unnecessary "mentoring" that is typical of large commercial models like ChatGPT.
So switching from a Google AI subscription isn't necessarily a compromise, but rather an upgrade. You'll get a system that's faster, safer and fully under your control. Local LLMs are no longer a toy for enthusiasts, but professional tools for comprehensive development and research. You just need to choose the right model.
