Google just dropped something massive: Gemma 4. If you’ve been following the AI space, you know Gemma has always been about efficient, open models. But this time, it feels different. Built on the research behind Gemini 3, Gemma 4 isn’t just a small update—it’s a leap into "agentic" territory.
I’ve spent the last few days hammering these models in my lab, testing the E4B on my main machine and the lightweight E2B on a Raspberry Pi. Here’s everything you need to know, from the specs to my real-world benchmarks.
What Makes Gemma 4 Special?
Gemma 4 isn't just about chat; it’s built to think. One of the biggest shifts is the configurable thinking modes, making it a much more capable reasoner than previous versions.
Here are the features that really stand out:
- Extended Multimodalities: It’s not just text anymore. All models handle images (with variable resolution support), while the E2B and E4B models natively feature Video and Audio support (ASR and translation).
- Architecture Variety: Google is offering both Dense and Mixture-of-Experts (MoE) variants. This is great because you can choose the right balance between speed and raw intelligence.
- Massive Context Windows: This is a big one for local AI. The small models (E2B/E4B) feature a 128K context window, while the larger ones go up to 256K. You can finally feed entire documentation folders into a model running on your laptop!
- Agentic Power: With native function-calling and better coding benchmarks, this model is designed to actually do things, like calling tools or managing autonomous workflows.
- System Prompt Support: Finally, native support for the
systemrole is here, giving us way more control over the model's behavior and structure.
My Testing Lab: Real-World Benchmarks
Specs are one thing, but how does it actually feel to use? I tested it in two setups.
Setup 1: High-Performance (Windows 11 + Ollama)
I ran Gemma 4 E4B on my Windows 11 machine via Ollama. This is where I did the "hard" tests.
- Test 1: Multi-step Reasoning: I gave it a complex logic puzzle. It used its "thinking" mode to break down the problem step-by-step. The structural understanding was impressive.
- Test 2: Memory Test: PASS. I pushed a lot of context to it, and it didn't forget the original instructions.
- Test 3: Instruction Trap: PASS. I tried to "trap" it with contradictory rules. It stayed on track and didn't break character.
- Test 4 & 5: Hallucination Test: This was the interesting part. On the first attempt, it FAILED. It hallucinated facts about a niche library. But on the second attempt, it PASSED. It seems that with a bit of "thinking" time, it can catch its own mistakes.
- Test 6: Programming/Coding: AVERAGE. It’s great at writing scripts and fixing bugs, but it’s not quite at the level of the giant models when it comes to whole-system architecture.
- Test 7: Image Recognition (Vision): AVERAGE. It can handle OCR, handwriting, and even chart comprehension (thanks to that variable resolution support), but it occasionally misses very small details in busy images.
Setup 2: The Raspberry Pi Challenge (LM Studio)
Can you really run a next-gen model on a Raspberry Pi? I tried the Gemma 4 E2B model in LM Studio.
The speed was surprisingly good for a Pi, but the size comes with a cost. In my series of 3 tests, it FAILED the hallucination test. While the reasoning is there, the smaller parameter count means you have to be very careful with its factual accuracy on small devices.
Watch the Full Walkthrough
I’ve put together a full demo video showing these tests live, including the Raspberry Pi setup and the exact prompts I used to catch those hallucinations.
The Bottom Line
Gemma 4 is a game-changer for local AI. The vision and audio support in such small packages (E2B/E4B) is a huge win for privacy-conscious developers. While the hallucination issues in the smaller models mean you shouldn't use it for medical or legal advice just yet, its agentic capabilities and 128K context window make it my new favorite for local hobbyist projects.
Have you tried running Gemma 4 locally yet? Let me know your results in the comments!