Fits comfortably
Running Gemma 3 4B on NVIDIA GeForce RTX 3080 16GB (Mobile)
NVIDIA GeForce RTX 3080 16GB (Mobile) runs Gemma 3 4B comfortably at Q8_0 with 10 GB of headroom for context.
Model size
4B params
Gemma 3 4B →Memory available
Recommended quant
Q8_0
Highest quality that fits
Quick start with Ollama
1. Install
ollama pull gemma3:4b2. Run
ollama run gemma3:4bDefault quant in Ollama is Q4_K_M. To use a different quant, append it: gemma3:4b-q5_K_M.
Variants and what fits
| Quantization | File size | VRAM required | Fits on NVIDIA GeForce RTX 3080 16GB (Mobile)? |
|---|---|---|---|
| Q4_K_M | 2.5 GB | 4 GB | Yes |
| Q8_0 | 4.4 GB | 6 GB | Yes |
Real benchmarks
Frequently asked
Can NVIDIA GeForce RTX 3080 16GB (Mobile) run Gemma 3 4B?
NVIDIA GeForce RTX 3080 16GB (Mobile) runs Gemma 3 4B comfortably at Q8_0 with 10 GB of headroom for context.
What quantization should I use?
Q8_0 is the highest-quality variant of Gemma 3 4B that fits in 16 GB VRAM. Lower-bit quants will be smaller but lose some quality.
How fast will it be?
Measured at 97.7 tok/s on this combination in our testing.
See also: Gemma 3 4B, NVIDIA GeForce RTX 3080 16GB (Mobile), all benchmarks.
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