Question 1

Can I run Gemma 4 E2B on a NVIDIA GeForce GTX 1650 Super?

Accepted Answer

Yes — NVIDIA GeForce GTX 1650 Super runs Gemma 4 E2B fully on GPU at the Q4_K_M quantization. Full GPU inference — 4 GB VRAM meets the 4 GB recommendation.

Question 2

What quantization of Gemma 4 E2B should I use on a NVIDIA GeForce GTX 1650 Super?

Accepted Answer

For 4 GB VRAM on the NVIDIA GeForce GTX 1650 Super, the Q4_K_M variant is the best fit. Estimated ~56.9 tokens/sec on the Q4_K_M quantization.

Question 3

How fast does Gemma 4 E2B run on NVIDIA GeForce GTX 1650 Super?

Accepted Answer

Roughly 56.9 tokens/sec for Q4_K_M. Real speed depends on context length, backend (Ollama, llama.cpp, LM Studio), and KV cache size.

Question 4

What if NVIDIA GeForce GTX 1650 Super is not enough for Gemma 4 E2B?

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_MBest fit	2.7 GB	3.5 GB	4 GB	8K / 128K	Full GPU	~56.9
Q8_0	5.3 GB	6 GB	8 GB	8K / 128K	Hybrid CPU+GPU	~13

Can I Run Gemma 4 E2B on NVIDIA GeForce GTX 1650 Super?

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Every Gemma 4 E2B quantization on NVIDIA GeForce GTX 1650 Super