Can You Run Gemma 4 on a CPU-Only PC (8GB RAM)?
Yes — best fit is Gemma 4 E2B at Q4_0 (4-bit) (~2.5GB) ✅ Comfortable, using 4GB of usable memory on a 8GB CPU-Only PC.
Every Gemma 4 model on this configuration
| Model | Best quant | Size | Status |
|---|---|---|---|
| Gemma 4 E2B | Q4_0 (4-bit) | ~2.5 GB | ✅ Comfortable |
| Gemma 4 E4B | — | — | ❌ Won't fit |
| Gemma 4 12B | — | — | ❌ Won't fit |
| Gemma 4 26B A4B | — | — | ❌ Won't fit |
| Gemma 4 31B | — | — | ❌ Won't fit |
How we got this verdict
8 ÷ 2 = 4GB usable (the RAM-÷-2 rule: one copy of the weights, one copy for working memory).
E2B 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 E2B at essentially the same ~4.3GB download size, with noticeably better output quality than a naive 4-bit quant. See the QAT guide for exact file names.
Going up to 16GB (16GB RAM) unlocks E4B at Q4_0 (4-bit) — a step up from E2B here.
Adding a discrete NVIDIA GPU is usually a bigger lever than more system RAM — it unlocks GPU offload and much faster tokens/sec, on top of whatever the RAM ÷ 2 rule already gives you here. See the GPU pages if a card is on the table.
Try a different configuration
Best fit: Gemma 4 E2B · Q4_0 (4-bit) · ~2.5 GB ✅ Comfortable
FAQ
Can a CPU-Only PC (8GB RAM) 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 4GB usable. Gemma 4 E2B is the largest model that fits here.
What's the best Gemma 4 model for a CPU-Only PC (8GB RAM)?
Gemma 4 E2B at Q4_0 (4-bit) (~2.5GB) is the best fit — it's the largest model that runs comfortably within the 4GB of usable memory here.
What if I have more or less memory than 8GB RAM?
With more (e.g. 16GB), you can run larger models or the same model more comfortably — see the CPU-Only PC page. This is already close to the practical floor for running Gemma 4 at all.