Gemma on NVIDIA Ada

Can I run Gemma 3 27B on an RTX 4090?

Yes. Gemma 3 27B at Q4_K_M uses 17.5 GB of the 21.8 GB available on a RTX 4090, and runs at about 36.5 tokens per second. You can push the context to 57K.

Runs comfortably

17.5 GB of 21.8 GB · 80%
022 GB
Weights 15.6 GB
KV cache 1.1 GB
Runtime overhead 0.8 GB

Gemma 3 27B at Q4_K_M leaves 4.3 GB spare on a RTX 4090. There is room to raise the context length or move up a quantisation level.

Generation36.5tok/s
Prompt processing1265tok/s
Max context57Ktokens
KV per 1K tokens0GB

Every quantisation of Gemma 3 27B on a RTX 4090

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

QuantisationbpwWeights TotalVerdictMax ctxtok/s
FP16 / BF16 16.00 51.0 GB 53.0 GB Won't fit — 1.16
INT8 / W8A8 8.50 26.8 GB 28.7 GB Won't fit — 4.33
Q8_0 (GGUF) 8.50 26.8 GB 28.7 GB Won't fit — 4.33
FP8 (E4M3) 8.00 25.5 GB 27.4 GB Won't fit — 5.29
Q6_K 6.56 20.9 GB 22.9 GB Won't fit — 14.2
Q5_K_M 5.67 18.1 GB 20.0 GB Fits, but tight 28K 31.7
Q5_K_S 5.52 17.6 GB 19.5 GB Runs comfortably 34K 32.5
Q4_K_M 4.85 15.6 GB 17.5 GB Runs comfortably 57K 36.5
AWQ 4-bit 4.25 15.5 GB 17.4 GB Runs comfortably 59K 36.7
GPTQ 4-bit 4.25 15.5 GB 17.4 GB Runs comfortably 59K 36.7
MXFP4 4.25 15.5 GB 17.4 GB Runs comfortably 59K 36.7
Q4_K_S 4.58 14.8 GB 16.7 GB Runs comfortably 67K 38.4
Q4_0 4.55 14.7 GB 16.6 GB Runs comfortably 68K 38.7
IQ4_XS 4.25 13.8 GB 15.7 GB Runs comfortably 79K 41.0
Q3_K_M 3.91 12.7 GB 14.7 GB Runs comfortably 91K 44.1
IQ3_M 3.70 12.1 GB 14.0 GB Runs comfortably 98K 46.3
IQ3_XXS 3.06 10.2 GB 12.1 GB Runs comfortably 121K 54.3
Q2_K 2.63 8.9 GB 10.8 GB Runs comfortably 128K 61.5
IQ2_XXS 2.06 7.1 GB 9.1 GB Runs comfortably 128K 74.6
IQ1_M 1.75 6.2 GB 8.1 GB Runs comfortably 128K 84.4

Also worth checking

Gemma 3 27B on every GPU
Full hardware tableEverything that runs on a RTX 4090
Full model tableWhy the KV cache is the part that bites
Guide