How much VRAM does Gemma-4-31B-StyleTune need?

Its published quantizations range from 7.10 GiB to 59.82 GiB in weights alone, before KV cache and runtime overhead.

Gemma-4-31B-StyleTune on Radeon RX 6500 XT

Can I run Gemma-4-31B-StyleTune on a Radeon RX 6500 XT?

Q: Can I run Gemma-4-31B-StyleTune on a Radeon RX 6500 XT?

No. No published quantization of Gemma-4-31B-StyleTune fits a Radeon RX 6500 XT at any context with q8_0 KV cache.

Not at these settings. No indexed quantization of Gemma-4-31B-StyleTune fits Radeon RX 6500 XT at any context we compute, with q8_0 KV. The smallest shipped quantization is 7.10 GiB in weights alone, against 3.72 GiB usable. CPU offload can still run it, slowly.

From the file· weights summed from filesFrom the file· KV computed per layerPredicted· speed and compute buffer

KV cache dtypef16 q8_0 q4_0— 4 GB card, 3.72 GiB usable after overhead

Every quantization at every context

total memory required; green fits, red does not

Quant	Weights●	4K◐	8K◐	16K◐	32K◐	64K◐	128K◐
BF16	59.82 GiB	61.8	62.1	62.8	64.1	66.7	72.0
Q8_0	31.79 GiB	33.7	34.1	34.7	36.0	38.7	44.0
Q6_K_L	26.60 GiB	28.5	28.9	29.5	30.9	33.5	38.8
Q6_K	25.97 GiB	27.9	28.2	28.9	30.2	32.9	38.2
I1-Q6_K	24.55 GiB	26.5	26.8	27.5	28.8	31.5	36.8
Q5_K_L	22.77 GiB	24.7	25.0	25.7	27.0	29.7	35.0
Q5_K_M	21.96 GiB	23.9	24.2	24.9	26.2	28.9	34.2
I1-Q5_K_M	21.25 GiB	23.2	23.5	24.2	25.5	28.2	33.5
Q5_K_S	20.93 GiB	22.9	23.2	23.9	25.2	27.8	33.2
I1-Q5_K_S	20.75 GiB	22.7	23.0	23.7	25.0	27.7	33.0
Q4_K_L	19.96 GiB	21.9	22.2	22.9	24.2	26.9	32.2
Q4_1	19.23 GiB	21.2	21.5	22.2	23.5	26.1	31.5
Q4_K_M	18.99 GiB	20.9	21.3	21.9	23.3	25.9	31.2
I1-Q4_1	18.96 GiB	20.9	21.2	21.9	23.2	25.9	31.2
Q5_K	18.17 GiB	20.1	20.4	21.1	22.4	25.1	30.4
I1-Q4_K_M	18.14 GiB	20.1	20.4	21.1	22.4	25.1	30.4
Q4_K_S	17.68 GiB	19.6	20.0	20.6	21.9	24.6	29.9
Q4_0	17.57 GiB	19.5	19.8	20.5	21.8	24.5	29.8
IQ4_NL	17.53 GiB	19.5	19.8	20.5	21.8	24.4	29.8
I1-Q4_K_S	17.28 GiB	19.2	19.5	20.2	21.5	24.2	29.5
I1-Q4_0	17.22 GiB	19.2	19.5	20.2	21.5	24.1	29.5
IQ4_XS	16.67 GiB	18.6	18.9	19.6	20.9	23.6	28.9
I1-IQ4_XS	16.28 GiB	18.2	18.6	19.2	20.5	23.2	28.5
Q3_K_L	16.22 GiB	18.2	18.5	19.2	20.5	23.1	28.4
I1-Q3_K_L	16.05 GiB	18.0	18.3	19.0	20.3	23.0	28.3
Q3_K_M	15.39 GiB	17.3	17.7	18.3	19.6	22.3	27.6
I1-Q3_K_M	14.80 GiB	16.7	17.1	17.7	19.1	21.7	27.0
IQ3_M	14.65 GiB	16.6	16.9	17.6	18.9	21.6	26.9
I1-IQ3_M	14.00 GiB	15.9	16.3	16.9	18.3	20.9	26.2
Q3_K_S	13.91 GiB	15.8	16.2	16.8	18.2	20.8	26.1
Q2_K_L	13.48 GiB	15.4	15.7	16.4	17.7	20.4	25.7
IQ3_XS	13.45 GiB	15.4	15.7	16.4	17.7	20.4	25.7
I1-IQ3_S	13.38 GiB	15.3	15.6	16.3	17.6	20.3	25.6
I1-Q3_K_S	13.38 GiB	15.3	15.6	16.3	17.6	20.3	25.6
I1-IQ3_XS	12.74 GiB	14.7	15.0	15.7	17.0	19.7	25.0
IQ3_XXS	12.65 GiB	14.6	14.9	15.6	16.9	19.6	24.9
IQ2_M	12.34 GiB	14.3	14.6	15.3	16.6	19.3	24.6
IQ3_S	12.22 GiB	14.2	14.5	15.2	16.5	19.1	24.5
Q2_K	12.19 GiB	14.1	14.5	15.1	16.5	19.1	24.4
I1-IQ3_XXS	11.81 GiB	13.7	14.1	14.7	16.1	18.7	24.0
I1-Q2_K	11.53 GiB	13.5	13.8	14.5	15.8	18.4	23.8
IQ2_XS	11.14 GiB	13.1	13.4	14.1	15.4	18.1	23.4
I1-IQ2_M	10.73 GiB	12.7	13.0	13.7	15.0	17.6	23.0
I1-Q2_K_S	10.65 GiB	12.6	12.9	13.6	14.9	17.6	22.9
IQ2_XXS	10.52 GiB	12.5	12.8	13.4	14.8	17.4	22.7
I1-IQ2_S	10.02 GiB	12.0	12.3	13.0	14.3	16.9	22.3
I1-IQ2_XS	9.31 GiB	11.2	11.6	12.2	13.6	16.2	21.5
IQ2_S	9.01 GiB	10.9	11.3	11.9	13.3	15.9	21.2
I1-IQ2_XXS	8.51 GiB	10.4	10.8	11.4	12.8	15.4	20.7
I1-IQ1_M	7.63 GiB	9.6	9.9	10.6	11.9	14.5	19.9
I1-IQ1_S	7.10 GiB	9.0	9.4	10.0	11.4	14.0	19.3

●From the file◐Predictedwhat these mean

Figures are GiB of total memory: weights plus KV cache plus compute buffer and backend overhead. Weights and KV are near-exact; the overhead term is modeled. Hover any cell for the breakdown.

Why other calculators disagree

A parameters × bits ÷ 8 estimate ignores two things that dominate at long context. First, the weights themselves are not the nominal rate — quantizations are mixtures, so the real file is consistently larger than the label implies. Second, most of this model's layers cache only a 1,024-token window rather than the full context.