Gemma 4 12B

Gemma 4 12B loads in 8 GB at Q4_K_M and is comfortable from 16 GB of memory, Macs included from the Mac Mini M6 16GB. Below: the full memory math, the cheapest card that runs it well, and the fastest machine we track.

PARAMETERS

12B

FORMAT

Q4_K_M

MIN MEMORY

12 GB

BEST FOR

Chat, Coding, Multimodal

Memory math

Weights (Q4_K_M)

8 GB

+ KV cache (16k)

~3.0 GB

Total at 16k

~11.0 GB

Comfortable from

16 GB

KV = fp16 estimate (q8_0 cache roughly halves it). "Comfortable" = weights + KV within the engine's tiered budget (~70-85% of memory).

Hardware snapshot

Cheapest GPU

AMD Radeon RX 7900 XT

~52 tok/s est. — ~$550 used

Fastest

NVIDIA GeForce RTX 5090

~103 tok/s est.

Runs on a Mac?

Mac Mini M6 16GB

~19 tok/s est.

Go deeper

Every Gemma 4 12B quant by real GGUF file sizeAlso tracked: Gemma 4 12B (Q8) (Q8_0, 12.8 GB, min 24 GB)

More Gemma models

Gemma 3 1B Instruct Gemma 2 2B Instruct Gemma 4 E2B Gemma 3 4B Instruct Gemma 4 E4B Gemma 2 9B Instruct Gemma 3 12B Instruct Gemma 4 26B-A4B Gemma 2 27B Instruct Gemma 3 27B Instruct Gemma 4 31B

Frequently asked questions

How much memory does Gemma 4 12B need?

8 GB for the Q4_K_M weights, plus ~3.0 GB of KV-cache at 16k context — about 11.0 GB total. Comfortable from 16 GB of VRAM or unified memory.

Does Gemma 4 12B run on a Mac?

Yes — from the Mac Mini M6 16GB (~19 tok/s est.). Unified memory means the RAM budget is the only limit.

What is the cheapest GPU for Gemma 4 12B?

The AMD Radeon RX 7900 XT is the cheapest tracked card that runs Gemma 4 12B comfortably — ~52 tok/s est. at ~$550 used.

Cite this page

ModelFit: Gemma 4 12B — specs, memory math and hardware verdicts.
https://modelfit.io/models/gemma4-12b/ (dataset updated 2026-09-03, CC BY 4.0).