Gemma on NVIDIA Ada

Can I run Gemma 3 12B on an RTX 4090?

Yes. Gemma 3 12B at Q4_K_M uses 8.6 GB of the 21.8 GB available on a RTX 4090, and runs at about 78.5 tokens per second. You can push the context to 128K.

Runs comfortably

8.6 GB of 21.8 GB · 39%
022 GB
Weights 7.0 GB
KV cache 0.8 GB
Runtime overhead 0.8 GB

Gemma 3 12B at Q4_K_M leaves 13.2 GB spare on a RTX 4090. There is room to raise the context length or move up a quantisation level.

Generation78.5tok/s
Prompt processing2840tok/s
Max context128Ktokens
KV per 1K tokens0GB

Every quantisation of Gemma 3 12B on a RTX 4090

Highlighted row is the highest quality that still fits at 8K context.

QuantisationbpwWeights TotalVerdictMax ctxtok/s
FP16 / BF16 16.00 22.7 GB 24.4 GB Won't fit 9.09
INT8 / W8A8 8.50 11.8 GB 13.5 GB Runs comfortably 128K 48.0
Q8_0 (GGUF) 8.50 11.8 GB 13.5 GB Runs comfortably 128K 48.0
FP8 (E4M3) 8.00 11.4 GB 13.0 GB Runs comfortably 128K 50.0
Q6_K 6.56 9.3 GB 10.9 GB Runs comfortably 128K 60.1
Q5_K_M 5.67 8.1 GB 9.7 GB Runs comfortably 128K 68.8
Q5_K_S 5.52 7.8 GB 9.5 GB Runs comfortably 128K 70.5
AWQ 4-bit 4.25 7.4 GB 9.0 GB Runs comfortably 128K 74.2
GPTQ 4-bit 4.25 7.4 GB 9.0 GB Runs comfortably 128K 74.2
MXFP4 4.25 7.4 GB 9.0 GB Runs comfortably 128K 74.2
Q4_K_M 4.85 7.0 GB 8.6 GB Runs comfortably 128K 78.5
Q4_K_S 4.58 6.6 GB 8.2 GB Runs comfortably 128K 82.3
Q4_0 4.55 6.6 GB 8.2 GB Runs comfortably 128K 82.7
IQ4_XS 4.25 6.2 GB 7.8 GB Runs comfortably 128K 87.4
Q3_K_M 3.91 5.7 GB 7.4 GB Runs comfortably 128K 93.3
IQ3_M 3.70 5.5 GB 7.1 GB Runs comfortably 128K 97.5
IQ3_XXS 3.06 4.6 GB 6.3 GB Runs comfortably 128K 113
Q2_K 2.63 4.1 GB 5.7 GB Runs comfortably 128K 126
IQ2_XXS 2.06 3.3 GB 5.0 GB Runs comfortably 128K 149
IQ1_M 1.75 2.9 GB 4.6 GB Runs comfortably 128K 165

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