Gemma 3 4B · 11 GPUs measured first-party · llama.cpp Q4_K_M · Updated July 2026

What GPU Do You Need for Gemma 3 4B?

Gemma 3 4B is Google's small open model, a polished generalist with vision support in a ~4GB package. We measured it on 11 GPUs (llama.cpp, Q4_K_M): 301 tok/s on the B300, with the RTX PRO 6000 essentially tied at 298 while drawing 45% less power.

Benchmarked weights: bartowski/google_gemma-3-4b-it-GGUF

The Gemma pattern, stated plainly. Our view of the Gemma 3 line: good models that aren't specialized at anything, middle of the pack across the board rather than best-in-class at one thing. At 4B that's actually a defensible profile: you get Google's training polish, clean multilingual behavior and image understanding in one small package. But the small tier is brutal company, Phi-4 Mini answers better, Qwen3 4B has the wider ecosystem, so Gemma 3 4B earns its slot mainly when you specifically want its vision capability or Google's instruction style in a tiny footprint.

Bench behavior. 301 tok/s peak with the usual flat top (the workstation PRO 6000 at 298 tok/s and 1.76 tok/W is the efficiency pick), and a ~4GB floor that any 6GB card clears. A T4 still manages 67 tok/s, comfortably interactive. Hardware is a non-issue for this model; the decision is entirely about which small model's temperament fits your task.

Our verdict

Gemma 3 4B: 301 tok/s peak, ~4GB floor, vision included, a capable all-rounder in the most competitive weight class we cover. Nothing about it is bad; nothing about it leads. Pick it for the multimodal support or the Google instruction style, not for benchmarks.

FAQ

What GPU does Gemma 3 4B need?

~4GB measured peak at Q4_K_M: any 6GB card runs it comfortably, and even a T4 delivers 67 tok/s. Hardware is genuinely not a consideration at this size.

Is Gemma 3 4B better than Phi-4 Mini or Qwen3 4B?

On raw answer quality we'd take Phi-4 Mini; on ecosystem, Qwen. Gemma's edge is built-in vision and multilingual polish. It's the generalist of the three, best when you need a bit of everything in one small model.

Does it really do image understanding at 4B?

Yes, Gemma 3 models from 4B up accept images. That's its clearest differentiator in this class; the comparable Qwen and Phi small models we benchmark are text-only.

What's the efficiency picture?

The RTX PRO 6000 measured 298 tok/s at 169W (1.76 tok/W), near-peak speed at moderate draw. Small models can't stress big silicon, so the flat chart top means cheap cards get you most of the experience.

Where does it fit in the Gemma lineup?

The entry point: 4B for light multimodal work on any hardware, 12B as the practical mid-size, 27B only if you've compared it against Mistral Small 24B for your tasks first, see those pages for our measurements.