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Can the GeForce RTX 5090 run Gemma 3 27B?

Gemma 3 27B runs locally on a 24 GB GPU at Q4_K_M, which needs about 20.2 GB of VRAM with a 4k-token context. A 32 GB or larger GPU is needed for comfortable 32k-token use, because the upper-bound KV cache grows to 16.6 GB at 32k tokens.

No

At Q4_K_M quantization with 131,072 context, the Gemma 3 27B requires approximately 84.65GB of VRAM. The GeForce RTX 5090 has 32GB available (52.65GB shortfall).

VRAM Breakdown

ComponentSize (GB)Source
Model weights (Q4_K_M)16.44calculated
Loading overhead (10%)1.64calculated
KV cache @ 131,072 context66.57calculated
Total required84.65
GPU memory available32vendor_spec
Headroom / shortfall-52.65

Quantization Options

QuantWeights (GB)Total @ 4K (GB)Total @ 32K (GB)Fits GeForce RTX 5090?
Q4_K_M 16.44 20.16 34.72 Yes
Q5_K_M 19.52 23.55 38.11 Yes
Q6_K 22.61 26.95 41.51 Yes
Q8_0 29.11 34.1 48.66 No
FP16 54.8 62.36 76.92 No

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If It Doesn't Fit: Alternatives

H200 SXM 141GB VRAM
NVIDIA B200 192GB VRAM
AMD Instinct MI300X 192GB VRAM
AMD Instinct MI325X 256GB VRAM
AMD Instinct MI355X 288GB VRAM

Same GPU, Other Models

Frequently Asked Questions

Can the Gemma 3 27B run on 32GB VRAM?

No. The Gemma 3 27B requires approximately 84.65GB at Q4_K_M quantization with 4K context. 32GB is not enough.

What is the maximum context length I can use on the GeForce RTX 5090?

The Gemma 3 27B supports up to 131,072 tokens of context. Larger context increases KV-cache memory requirements. At 4K context the model needs ~84.65GB; at 32K it needs more.

Which quantization should I use with the GeForce RTX 5090?

Q4_K_M is the recommended starting point — it offers the best speed-to-quality tradeoff. If you have VRAM headroom, Q6_K or Q8_0 improves quality at the cost of speed. FP16 is only for inference servers with ample memory.

Can an RTX 4090 run Gemma 3 27B?

Yes. Gemma 3 27B needs about 20.2 GB of VRAM at Q4_K_M with a 4k context, which fits the RTX 4090’s 24 GB with headroom for longer contexts thanks to Gemma 3’s sliding-window attention on most layers.

How much VRAM does Gemma 3 27B need?

Gemma 3 27B needs about 20.2 GB of VRAM at Q4_K_M with a 4k context and up to about 34.7 GB at 32k tokens using the full-attention upper bound; sliding-window attention keeps actual usage lower.

Related Pages

Full Gemma 3 27B fit page · All AI models · GeForce RTX 5090 specs · VRAM calculator

VRAM figures are calculated from model architecture parameters using established formulas. Benchmark data is measured and cited per row. GPU memory is vendor_spec from manufacturer datasheets.

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