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OP·Fredoline Eruo
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RUNLOCALAI · v38
Gemma 3 4B / on / NVIDIA GeForce RTX 3080 16GB (Mobile)
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.

By Fredoline Eruo·Latest benchmark evidence Jun 2, 2026

Model size

4B params
Gemma 3 4B →

Memory available

16 GB
NVIDIA GeForce RTX 3080 16GB (Mobile) →

Recommended quant

Q8_0
Highest quality that fits

Quick start with Ollama

1. Install
ollama pull gemma3:4b
2. Run
ollama run gemma3:4b

Default quant in Ollama is Q4_K_M. To use a different quant, append it: gemma3:4b-q5_K_M.

Variants and what fits

QuantizationFile sizeVRAM requiredFits on NVIDIA GeForce RTX 3080 16GB (Mobile)?
Q4_K_M2.5 GB4 GB
Yes
Q8_04.4 GB6 GB
Yes

Real benchmarks

ToolQuantContexttok/sVRAM usedDateEvidenceExport
—Q4_K_M4,09697.7 tok/s—Jun 2, 2026Measured here
operator: fred-oline
DetailSourceJSON

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.

Reviewed by RunLocalAI Editorial. See our editorial policy.