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.
Real-world notes for this configuration
At 8GB total system RAM, the RAM-÷-2 rule this checker uses is actually a generous simplification — in practice the OS and any inference runtime overhead often leave less than 4GB free before a model even loads, and per this site's own hardware guide, CPU-only inference needs roughly 2x the model's Q4_0 weight size in free RAM (one copy for weights, one for working memory).
- ⚠Single-channel memory is common at this tier (one stick installed) — check with a tool like CPU-Z or dmidecode, since dual-channel roughly doubles the memory bandwidth that CPU inference actually depends on, not raw capacity.
- ⚠Expect noticeably slow generation even for the smallest model that fits — this site's hardware guide puts E4B on CPU at roughly 2-5 tokens/sec on a modern laptop, and 8GB leaves little margin even for that.
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.
Is 8GB of system RAM realistic for any local Gemma 4 model without a GPU?
It's the tightest tier this checker covers — see the table above for the exact verdict, but in practice expect to close nearly everything else running on the machine, and don't expect more than the smallest model in the lineup.
Does single- vs dual-channel RAM matter at 8GB?
Yes, more than the capacity number suggests — CPU inference is memory-bandwidth-bound, and dual-channel configurations (two matched sticks) roughly double the bandwidth available versus a single stick, directly affecting tokens-per-second.