Can the NVIDIA RTX 3080 10GB run Gemma 3 27B?
No
No. Even at Q4_K_M, Gemma 3 27B needs about 21.4 GB, but the NVIDIA RTX 3080 10GB has 10 GB usable. You could offload some layers to system RAM, but it will be very slow.
Try other context lengths in the calculator →Run it in the cloud
Too big for the NVIDIA RTX 3080 10GB? Run Gemma 3 27B on a rented GPU instead.
Rent a cloud GPU by the hour. No upfront cost, cancel any time.
Memory needed by quantization
At 8,192 tokens of context.
| Quant | Quality | Memory | Fits? | Speed |
|---|---|---|---|---|
| FP16 | Full quality | 59.6 GB | Too big | — |
| Q8_0 | Near-lossless | 33.9 GB | Too big | — |
| Q6_K | Excellent | 27.2 GB | Too big | — |
| Q5_K_M | Very good | 24.2 GB | Too big | — |
| Q4_K_M | Good, most popular | 21.4 GB | Too big | — |
| Q3_K_M | Noticeably degraded | 18.2 GB | Too big | — |
| Q2_K | Heavily degraded | 15 GB | Too big | — |
How to run Gemma 3 27B anyway
On a rented cloud GPU with enough memory, the same command you'd use locally works:
ollama run gemma3:27bAt Q4_K_M it needs about 21.4 GB, so pick a GPU with at least 24 GB.
GPUs that run Gemma 3 27B comfortably
- NVIDIA RTX 3090 (24 GB)
- AMD Radeon RX 7900 XTX (24 GB)
- NVIDIA RTX 4090 (24 GB)
- Apple M2 Pro (32GB)
- NVIDIA RTX 5090 (32 GB)