Can the NVIDIA RTX 3080 10GB run Gemma 3 4B?
Yes
QuantQ8_0Near-lossless
Memory6.3 GBof 10 GB
Speed~100tokens/s
Yes. The NVIDIA RTX 3080 10GB can run Gemma 3 4B fully in VRAM at Q8_0 (near-lossless), using about 6.3 GB of the 10 GB available, at roughly 100 tokens/second.
Try other context lengths in the calculator →Memory needed by quantization
At 8,192 tokens of context.
| Quant | Quality | Memory | Fits? | Speed |
|---|---|---|---|---|
| FP16 | Full quality | 10.3 GB | Too big | — |
| Q8_0 | Near-lossless | 6.3 GB | Fits | ~100 tok/s |
| Q6_K | Excellent | 5.3 GB | Fits | ~129 tok/s |
| Q5_K_M | Very good | 4.8 GB | Fits | ~149 tok/s |
| Q4_K_M | Good, most popular | 4.3 GB | Fits | ~175 tok/s |
| Q3_K_M | Noticeably degraded | 3.8 GB | Fits | ~217 tok/s |
| Q2_K | Heavily degraded | 3.4 GB | Fits | ~283 tok/s |
How to run Gemma 3 4B on the NVIDIA RTX 3080 10GB
With Ollama installed, one command downloads and starts it:
ollama run gemma3:4bOllama's default download is Q4_K_M (about 4.3 GB here). You have room for Q8_0, which is near-lossless: pick that GGUF in LM Studio or from Hugging Face.
GPUs that run Gemma 3 4B comfortably
- NVIDIA RTX 4060 (8 GB)
- NVIDIA RTX 3070 (8 GB)
- NVIDIA RTX 3060 12GB
- NVIDIA RTX 4070 (12 GB)
- NVIDIA RTX 5070 (12 GB)
Models that run well on the NVIDIA RTX 3080 10GB
Run it in the cloud
Don't want to buy hardware? Run Gemma 3 4B on a rented GPU today.
Rent a cloud GPU by the hour. No upfront cost, cancel any time.