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
| Model | Best quant | Size | Status |
|---|---|---|---|
| Gemma 4 E2B | BF16 (16-bit) | ~8 GB | ✅ Comfortable |
| Gemma 4 E4B | BF16 (16-bit) | ~15 GB | ✅ Comfortable |
| Gemma 4 12B | SFP8 (8-bit) | ~13.4 GB | ✅ Comfortable |
| Gemma 4 26B A4B | Q4_0 (4-bit) | ~15.6 GB | ✅ Comfortable |
| Gemma 4 31B | Q4_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.
Real-world notes for this configuration
Desktop and "laptop" RTX 4090s are very different cards despite the shared name: the desktop 4090 used in this checker has 24GB of GDDR6X on a 384-bit bus, while NVIDIA's mobile 4090 is built on a much smaller die closer to a desktop 4080, with only 16GB of VRAM — a naming choice that's confused plenty of laptop buyers expecting desktop-4090-level capacity.
- ⚠If you're shopping a gaming laptop advertised with an "RTX 4090," don't assume it has this card's 24GB — the mobile version tops out at 16GB on a different, smaller die entirely.
- ⚠At 450W typical board power, the desktop 4090 needs serious PSU headroom and case airflow for sustained local-AI sessions.
Try a different configuration
Best fit: Gemma 4 31B · Q4_0 (4-bit) · ~17.4 GB ✅ Comfortable
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.
Does a laptop RTX 4090 have the same 24GB VRAM as a desktop RTX 4090?
No — this is one of NVIDIA's more confusing naming choices. The mobile RTX 4090 is built on a smaller die (closer to a desktop 4080) with only 16GB of VRAM, not the 24GB the desktop card in this checker has.
How much power headroom does a desktop RTX 4090 need for local AI?
NVIDIA rates it at 450W typical board power — plan for a PSU with real headroom above that, plus case airflow suited to sustained, not just burst, load if you're running long local-AI sessions.
Related
Gemma 4 on RTX 3070/3080
The full setup guide for this device family.
Can You Run Gemma 4 on an RTX 3090 (24GB VRAM)?
NVIDIA GPU — 24GB VRAM
Can You Run Gemma 4 on an RTX 5090 (32GB VRAM)?
NVIDIA GPU — 32GB VRAM
Gemma 4 Hardware Requirements
The full memory table this checker is built on.
Full Hardware Checker
Every device type, every model, one tool.