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Can You Run Gemma 4 on an RTX 4090 (24GB VRAM)?

Yes — best fit is Gemma 4 31B at Q4_0 (4-bit) (~17.4GB) Comfortable, using 23GB of usable memory on a 24GB RTX 4090.

Every Gemma 4 model on this configuration

ModelBest quantSizeStatus
Gemma 4 E2BBF16 (16-bit)~8 GB Comfortable
Gemma 4 E4BBF16 (16-bit)~15 GB Comfortable
Gemma 4 12BSFP8 (8-bit)~13.4 GB Comfortable
Gemma 4 26B A4BQ4_0 (4-bit)~15.6 GB Comfortable
Gemma 4 31BQ4_0 (4-bit)~17.4 GB Comfortable

How we got this verdict

24 - 1 = 23GB usable VRAM (the driver and OS reserve roughly 1 GB).

31B lands on Q4_0 here, so grab the official QAT (quantization-aware training) checkpoint instead of a generic Q4_0 quant. Google shipped a full-quality QAT build for 31B at essentially the same ~19GB download size, with noticeably better output quality than a naive 4-bit quant. See the QAT guide for exact file names.

Switching to the RTX 5090 (32GB VRAM) doesn't change the top recommendation — 31B is still the best fit, just with more headroom.

The fastest lever on a fixed budget isn't more VRAM on the same card — it's switching cards. Compare this tier against neighboring cards below, or check the full checker for any GPU model.

Try a different configuration

🔍 Quick check: your PC with

Best fit: Gemma 4 31B · Q4_0 (4-bit) · ~17.4 GB Comfortable

31B 26B A4B 12B E4B E2B
Full breakdown for every model & quant →

FAQ

Can a RTX 4090 (24GB VRAM) run the 31B flagship model?

Yes, comfortably — Gemma 4 31B fits at Q4_0 (4-bit) (~17.4GB), using 23GB of usable memory on this configuration.

What's the best Gemma 4 model for a RTX 4090 (24GB VRAM)?

Gemma 4 31B at Q4_0 (4-bit) (~17.4GB) is the best fit — it's the largest model that runs comfortably within the 23GB of usable memory here.

What if I have more or less memory than 24GB VRAM?

With more (e.g. RTX 5090), you can run larger models or the same model more comfortably — see the RTX 5090 page. With less (e.g. RTX 3090), the best-fitting model gets smaller or tighter — see the RTX 3090 page.

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