Can You Run Gemma 4 on an RTX 3060 Ti (8GB VRAM)?
Yes — best fit is Gemma 4 E4B at Q4_0 (4-bit) (~5GB) ✅ Comfortable, using 7GB of usable memory on a 8GB RTX 3060 Ti.
Every Gemma 4 model on this configuration
| Model | Best quant | Size | Status |
|---|---|---|---|
| Gemma 4 E2B | SFP8 (8-bit) | ~4 GB | ✅ Comfortable |
| Gemma 4 E4B | Q4_0 (4-bit) | ~5 GB | ✅ Comfortable |
| Gemma 4 12B | Q4_0 (4-bit) | ~6.7 GB | ⚠️ Tight |
| Gemma 4 26B A4B | — | — | ❌ Won't fit |
| Gemma 4 31B | — | — | ❌ Won't fit |
How we got this verdict
8 - 1 = 7GB usable VRAM (the driver and OS reserve roughly 1 GB).
E4B 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 E4B at essentially the same ~6.1GB 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 3070 (8GB VRAM) doesn't change the top recommendation — E4B 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
The RTX 3060 Ti is built on the same GA104 die as the RTX 3070, giving it meaningfully more compute and a wider 256-bit memory bus than the plain 3060 — but NVIDIA paired that with only 8GB of VRAM, 4GB less than the non-Ti 3060. It's a genuine case of a "Ti" branding upgrade trading away capacity for speed, which matters more than usual for local AI, where what fits is often the bigger question than how fast it runs.
- ⚠Don't assume "Ti" means strictly better for local AI — for this specific pair, the non-Ti 3060 has 50% more VRAM despite being the cheaper, lower-tier card.
- ⚠8GB is the same ceiling as several other cards spanning two generations (3070, 3070 Ti, base 4060) — if you're shopping for VRAM specifically, compare the full card lineup rather than assuming a newer or higher model number means more memory.
Try a different configuration
Best fit: Gemma 4 E4B · Q4_0 (4-bit) · ~5 GB ✅ Comfortable
FAQ
Can a RTX 3060 Ti (8GB VRAM) run the 31B flagship model?
No — the 31B model needs at least 17.4GB usable memory even at Q4_0, and this configuration only has 7GB usable. Gemma 4 E4B is the largest model that fits here.
What's the best Gemma 4 model for a RTX 3060 Ti (8GB VRAM)?
Gemma 4 E4B at Q4_0 (4-bit) (~5GB) is the best fit — it's the largest model that runs comfortably within the 7GB of usable memory here.
What if I have more or less memory than 8GB VRAM?
With more (e.g. RTX 3070), you can run larger models or the same model more comfortably — see the RTX 3070 page. This is already close to the practical floor for running Gemma 4 at all.
Should I buy an RTX 3060 Ti or a plain RTX 3060 for local AI?
If VRAM capacity is your priority, the non-Ti 3060 (12GB) fits larger models than the 3060 Ti (8GB) despite being the cheaper card — the Ti's advantage is raw compute speed, which matters once a model already fits, not whether it fits in the first place.
Is the RTX 3060 Ti's memory bus faster than the plain 3060's?
Yes — the 3060 Ti shares its GA104 die and 256-bit bus with the 3070, giving it higher memory bandwidth than the 3060's 192-bit bus. That helps token generation speed once a model is loaded, but doesn't change the 8GB capacity ceiling.