Can the Radeon RX 7900 XTX run Gemma 4 12B?

Yes. Gemma 4 12B fits the Radeon RX 7900 XTX's 24 GB at Q4_K_M (about 8.8 GB needed), running at an estimated 79 tok/s. There's room for up to Q8_0 if you want higher quality.

VRAM
24 GB
Needs at Q4
8.8 GB
Headroom
15.2 GB
Speed (Q4_K_M)
~79 tok/s

Every quantization

Gemma 4 12B (12B) on 24 GB

QuantWeightsNeedsFitEst. speed
Q4_K_M7 GB8.8 GBFits easily~79 tok/s
Q5_K_M9 GB10.8 GBFits easily~61 tok/s
Q8_013 GB14.8 GBFits~42 tok/s
FP1624 GB25.8 GBToo big -

Estimates. Needs = weights + 1.8 GB for KV cache and runtime at modest context. Speed is single-stream decode scaled from the Radeon RX 7900 XTX's 960 GB/s bandwidth (Estimated from memory bandwidth (llama.cpp decode)). Long contexts need more memory and run slower.

Run it

Copy, paste, go

llama-server -hf google/gemma-4-12B-it-qat-q4_0-gguf -ngl 99

Ollama pulls a Q4 build by default. Pick a larger quant only if the table above says it fits. Full Gemma 4 12B details →

Compare

Same model, other hardware - and other models on this card

Gemma 4 12B on other hardware

Also runs on the Radeon RX 7900 XTX

Frequently asked

Quick answers

Can the AMD Radeon RX 7900 XTX run Gemma 4 12B?

Yes. Gemma 4 12B fits the Radeon RX 7900 XTX's 24 GB at Q4_K_M (about 8.8 GB needed), running at an estimated 79 tok/s. There's room for up to Q8_0 if you want higher quality.

How much VRAM does Gemma 4 12B need?

About 7 GB of weights at Q4_K_M, 13 GB at Q8_0 and 24 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.

How fast is Gemma 4 12B on the Radeon RX 7900 XTX?

Roughly 79 tokens per second at Q4_K_M (single user, llama.cpp-style decode). This is an estimate from the Radeon RX 7900 XTX's 960 GB/s memory bandwidth.