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Can You Run Gemma 4 on an RTX 3070 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 3070 Ti.

Every Gemma 4 model on this configuration

ModelBest quantSizeStatus
Gemma 4 E2BSFP8 (8-bit)~4 GB Comfortable
Gemma 4 E4BQ4_0 (4-bit)~5 GB Comfortable
Gemma 4 12BQ4_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 4060 (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 3070 Ti runs the full, unlocked GA104 die at higher clocks and power (around 290W board power, notably high for its tier) — but it's capped at the same 8GB of GDDR6X VRAM as the plain 3070 and the 3060 Ti. It's arguably the clearest case in the whole 30-series lineup of a card built purely for gaming clock speed with no corresponding memory upgrade, which matters for local AI where the ceiling on what fits doesn't move.

  • Highest power draw of any card at its VRAM tier in this lineup — check your PSU headroom, especially in a small-form-factor build meant to run as an always-on local-AI box.
  • GDDR6X memory runs hotter than the plain GDDR6 on the base 3070 — factor in case airflow for sustained, long-running inference sessions.

Try a different configuration

🔍 Quick check: your PC with

Best fit: Gemma 4 E4B · Q4_0 (4-bit) · ~5 GB Comfortable

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

FAQ

Can a RTX 3070 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 3070 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 4060), you can run larger models or the same model more comfortably — see the RTX 4060 page. With less (e.g. RTX 3070), the best-fitting model gets smaller or tighter — see the RTX 3070 page.

Is the RTX 3070 Ti's extra power draw worth it for local AI over a plain 3070?

For local AI specifically, no — both cards share the same 8GB ceiling, so the 3070 Ti's higher clocks and ~290W power draw buy faster token generation on models that already fit, not access to bigger models.

Does the RTX 3070 Ti use GDDR6X or GDDR6 memory?

GDDR6X — faster and hotter-running than the plain GDDR6 on the base 3070, though the capacity (8GB) is identical between the two.

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