Google has unleashed Gemma 4; a brand-new family of open AI models; and the developer community is doing a collective happy dance.

Built on the same "secret sauce" powering Gemini 3 Gemma 4 comes in multiple sizes, from a tiny 2 billion parameters to a massive 31 billion. Whether you are running AI on a laptop or a beefy server farm, there is a Gemma 4 with your name on it.

Meet the Four Models: 

But first get this: Gemma 4 is organized into two distinct tiers. 

1. Edge Tier: These models are designed to live natively on your devices.

Both edge models support a 128K-token context window — that's roughly the length of an entire novel worth of memory per conversation.

2. The Workstation Tier is built for developers who need local "frontier-class" intelligence.

Unlike older models that had vision and audio awkwardly "stitched" on, Gemma 4 is natively multimodal from scratch:

But Here’s where it gets legendary: Previous Gemma models came with Google's own custom license that had legal teams sweating, but Google slapped an Apache 2.0 license on this entire family, and in case you don't know, this is  the same no-strings-attached license used by most of the open-source AI world. 

In plain English? Startups and indie builders can grab these models, use them commercially, modify them, and build empires without paying Google a single cent. In a world of restrictive licenses, this is the AI equivalent of finding a sports car with free lifetime fuel.

The Reality Check: Gemma 4 is straight-up embarrassing its predecessor. The tiny E2B now outperforms the old Gemma 3 27B on major benchmarks. It’s like the intern outperforming last year’s senior manager. Awkward, but amazing for us.

you can grab the weights right now on Hugging Face, Kaggle, or Ollama. Or go learn more here.

That's the AI paradox hiding in your CX stack. Tickets close. Customers leave. And most teams don't see it coming because they're measuring the wrong things.

Efficiency metrics look great on paper. Handle time down. Containment rate up. But customer loyalty? That's a different story — and it's one your current dashboards probably aren't telling you.

Gladly's 2026 Customer Expectations Report surveyed thousands of real consumers to find out exactly where AI-powered service breaks trust, and what separates the platforms that drive retention from the ones that quietly erode it.

If you're architecting the CX stack, this is the data you need to build it right. Not just fast. Not just cheap. Built to last.

See the data

Ever asked an AI for help, but got vague or surface-level answers? That’s because the way you prompt decides the quality of the response. 

Today’s prompt is designed to make AI think like a strategist; breaking down problems step by step and giving you a clear action plan.

How to Use It Effectively

Here’s the trick: don't just throw in a generic problem like ‘I need business advice.’ Be specific. Say something like ‘I’m growing my tutoring business, but I suck at marketing and time management.’ The more detail and context you give, the smarter and deeper ChatGPT’s response gets.

💡 Prompts to try: