Question 1

Can I run Gemma 3n E4B on a NVIDIA GeForce GTX 1080?

Accepted Answer

Yes — NVIDIA GeForce GTX 1080 runs Gemma 3n E4B fully on GPU at the Q8_0 quantization. Full GPU inference — 8 GB VRAM meets the 5.2 GB recommendation.

Question 2

What quantization of Gemma 3n E4B should I use on a NVIDIA GeForce GTX 1080?

Accepted Answer

For 8 GB VRAM on the NVIDIA GeForce GTX 1080, the Q8_0 variant is the best fit. Estimated ~76.2 tokens/sec on the Q8_0 quantization.

Question 3

How fast does Gemma 3n E4B run on NVIDIA GeForce GTX 1080?

Accepted Answer

Roughly 76.2 tokens/sec for Q8_0. Real speed depends on context length, backend (Ollama, llama.cpp, LM Studio), and KV cache size.

Question 4

What if NVIDIA GeForce GTX 1080 is not enough for Gemma 3n E4B?

Accepted Answer

Try a smaller quantization variant or run on CPU + RAM with the trade-off of slower generation.

Quantization	File Size	Min VRAM	Rec VRAM	Context	Verdict	Estimated tok/s
Q4_K_M	2 GB	2.3 GB	2.6 GB	8K / 8K	Full GPU	~128
Q5_K_M	2.5 GB	2.9 GB	3.3 GB	8K / 8K	Full GPU	~111.3
Q8_0Best fit	4 GB	4.6 GB	5.2 GB	8K / 8K	Full GPU	~76.2
FP16	8 GB	9.2 GB	10.4 GB	8K / 8K	Hybrid CPU+GPU	~14

Can I Run Gemma 3n E4B on NVIDIA GeForce GTX 1080?

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Every Gemma 3n E4B quantization on NVIDIA GeForce GTX 1080