Can the RTX 2000 Ada run Gemma 4 12B?

Yes. Gemma 4 12B fits the RTX 2000 Ada's 16 GB at Q4_K_M (about 8.8 GB needed), running at an estimated 21 tok/s. There's room for up to Q8_0 if you want higher quality.

VRAM
16 GB
Needs at Q4
8.8 GB
Headroom
7.2 GB
Speed (Q4_K_M)
~21 tok/s

Every quantization

Gemma 4 12B (12B) on 16 GB

QuantWeightsNeedsFitEst. speed
Q4_K_M7 GB8.8 GBFits easily~21 tok/s
Q5_K_M9 GB10.8 GBFits~16 tok/s
Q8_013 GB14.8 GBTight~11 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 RTX 2000 Ada's 256 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 →

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

Gemma 4 12B on other hardware

Also runs on the RTX 2000 Ada

Frequently asked

Quick answers

Can the RTX 2000 Ada Generation run Gemma 4 12B?

Yes. Gemma 4 12B fits the RTX 2000 Ada's 16 GB at Q4_K_M (about 8.8 GB needed), running at an estimated 21 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 RTX 2000 Ada?

Roughly 21 tokens per second at Q4_K_M (single user, llama.cpp-style decode). This is an estimate from the RTX 2000 Ada's 256 GB/s memory bandwidth.