Gemma on NVIDIA Ada

Can I run Gemma 3 4B on an RTX 4070 Super?

Yes. Gemma 3 4B at Q4_K_M uses 3.6 GB of the 10.5 GB available on a RTX 4070 Super, and runs at about 110 tokens per second. You can push the context to 128K.

Runs comfortably

3.6 GB of 10.5 GB · 34%
010 GB
Weights 2.5 GB
KV cache 0.3 GB
Runtime overhead 0.8 GB

Gemma 3 4B at Q4_K_M leaves 6.9 GB spare on a RTX 4070 Super. There is room to raise the context length or move up a quantisation level.

Generation110tok/s
Prompt processing3467tok/s
Max context128Ktokens
KV per 1K tokens0GB

Every quantisation of Gemma 3 4B on a RTX 4070 Super

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

QuantisationbpwWeights TotalVerdictMax ctxtok/s
FP16 / BF16 16.00 8.0 GB 9.1 GB Runs comfortably 67K 36.5
INT8 / W8A8 8.50 4.1 GB 5.2 GB Runs comfortably 128K 69.2
Q8_0 (GGUF) 8.50 4.1 GB 5.2 GB Runs comfortably 128K 69.2
FP8 (E4M3) 8.00 4.0 GB 5.1 GB Runs comfortably 128K 70.8
Q6_K 6.56 3.3 GB 4.4 GB Runs comfortably 128K 85.2
AWQ 4-bit 4.25 3.0 GB 4.1 GB Runs comfortably 128K 91.3
GPTQ 4-bit 4.25 3.0 GB 4.1 GB Runs comfortably 128K 91.3
MXFP4 4.25 3.0 GB 4.1 GB Runs comfortably 128K 91.3
Q5_K_M 5.67 2.8 GB 3.9 GB Runs comfortably 128K 97.4
Q5_K_S 5.52 2.8 GB 3.9 GB Runs comfortably 128K 99.8
Q4_K_M 4.85 2.5 GB 3.6 GB Runs comfortably 128K 110
Q4_K_S 4.58 2.4 GB 3.5 GB Runs comfortably 128K 115
Q4_0 4.55 2.4 GB 3.4 GB Runs comfortably 128K 116
IQ4_XS 4.25 2.2 GB 3.3 GB Runs comfortably 128K 121
Q3_K_M 3.91 2.1 GB 3.2 GB Runs comfortably 128K 129
IQ3_M 3.70 2.0 GB 3.1 GB Runs comfortably 128K 134
IQ3_XXS 3.06 1.7 GB 2.8 GB Runs comfortably 128K 152
Q2_K 2.63 1.5 GB 2.6 GB Runs comfortably 128K 167
IQ2_XXS 2.06 1.3 GB 2.4 GB Runs comfortably 128K 193
IQ1_M 1.75 1.2 GB 2.3 GB Runs comfortably 128K 211

Also worth checking

Gemma 3 4B on every GPU
Full hardware tableEverything that runs on a RTX 4070 Super
Full model tableWhy the KV cache is the part that bites
Guide