How much VRAM does Gemma 2 9B need?

Gemma 2 9B requires 5.5 GB VRAM to run at Q4 quantization (recommended), 9 GB for Q8, and 18 GB for full FP16 precision. The minimum is 3.5 GB at Q2 with some quality loss.

What GPU do I need for Gemma 2 9B?

You need at least 5.5 GB VRAM to run Gemma 2 9B at Q4 quantization. 40 consumer GPUs are compatible. The most popular choice is an NVIDIA RTX-class GPU with 5.5+ GB VRAM.

Is Gemma 2 9B free to use?

Gemma 2 9B by Google is available under the Gemma license. Check the license terms for commercial use restrictions. You can download and run it for free with Ollama: ollama run gemma2:9b

Local Engine Ready

Gemma 2 9B

Name: Gemma 2 9B
Author: Javier Morales

40 consumer GPUs can run Gemma 2 9B at Q4 natively. Precise VRAM thresholds and benchmarks below.

40 Compatible GPUs

9B params

8K context

Top pick

RTX 5090 · 32 GB VRAM runs Q4 natively

Check availability See top 3 ↓

Prices and availability may change · affiliate link

Javier Morales AI hardware specialist — 8 years of experience Updated 2026-04-08

GitHub: github.com/javier-morales-ia

llama.cpp 0.2.x · CUDA 12 · ROCm 6 · updated monthly · methodology →

Execution Context

ARCHITECTURE TRANSFORMER

CONTEXT 8K TOKENS

QUANTIZATION 4-BIT GGUF

PROVIDER Google

LICENSE Gemma

VRAM REQUIREMENT

5.5 GB

4GB 8GB 12GB 16GB 24GB+

Hardware Decision

This model requires aEntry GPU (8 GB VRAM)

Minimum

GTX 1660 Super

Runs at Q4 — functional, some wait

6 GB VRAM

View compatible setup

Balanced

RTX 4060 Ti 16GB

Best value for daily use

16 GB VRAM

View compatible setup

Optimal

RTX 5090

Full quality, fastest inference

32 GB VRAM

View compatible setup

Compatible GPUs for Gemma 2 9B

Best picks by compatibility, VRAM headroom, and value — prices and availability may change.

32 GB VRAM · Q4 native Amazon

RTX 5090

4.0 (61 reviews)

Pros

Runs Gemma 2 9B at Q4 natively
32 GB VRAM — adequate headroom

24 GB VRAM · Q4 native Amazon

RTX 4090

4.7 (207 reviews)

Pros

Runs Gemma 2 9B at Q4 natively
24 GB VRAM — adequate headroom

128 GB VRAM · Q4 native Amazon

M4 Ultra

0.0 (0 reviews)

Pros

Runs Gemma 2 9B at Q4 natively
128 GB VRAM — adequate headroom

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How to run this model

Check if your GPU can run Gemma 2 9B →

VRAM Calculator — instant compatibility check

RTX 5090

32 GB · Runs Q4 natively · Check availability

*Prices and availability may change. Some links are affiliate links.

System Requirements

GPU VRAM 5.5 GB Entry GPU

System RAM 16 GB DDR4/DDR5

Storage 5.2 GB Q4 · SSD recommended

CPU Any modern CPU GPU required

VRAM by Quantization

Quantization	VRAM needed	Disk space	Quality
FP16 (max quality)	18 GB	18 GB	Maximum
Q8 (high quality)	9 GB	9 GB	Near-lossless
Q4 (recommended) Best balance	5.5 GB	5.2 GB	Recommended
Q2 (minimum)	3.5 GB	2.8 GB	Quality loss

Model Details

Developer	Google
Parameters	9B
Context window	8,192 tokens
License	Gemma
Use cases	chat, coding, reasoning
Released	2024-06

Install with Ollama

ollama run gemma2:9b

Hugging Face

google/gemma-2-9b-it

View on HF →

Technical Requirements

Can your GPU run Gemma 2 9B?

Gemma 2 9B requires <strong class="text-primary-container">5.5 GB VRAM</strong> at Q4. 40 consumer GPUs meet this threshold. Below 8 GB or 3.5 GB you'll hit significant offload latency.

RTX 5090 (32 GB) RTX 4090 (24 GB) M4 Ultra (128 GB)

3.5GB Critical min

5.5GB Optimal Q4

9GB High Quality Q8

18GB Max FP16

Hardware Performance Matrix

40 Q4 native · 0 offload

GPU Unit	VRAM	Compatibility	Est. Speed	Action
RTX 5090	32GB	Optimal	84 tok/s	Calculate →
RTX 4090	24GB	Optimal	47 tok/s	Calculate →
M4 Ultra	128GB	Optimal	51 tok/s	Calculate →
RTX 5080	16GB	Optimal	45 tok/s	Calculate →
M3 Ultra	192GB	Optimal	37 tok/s	Calculate →
RTX 4080 Super	16GB	Optimal	34 tok/s	Calculate →
RTX 5070 Ti	16GB	Optimal	42 tok/s	Calculate →
RTX 3090	24GB	Optimal	44 tok/s	Calculate →
M4 Max 48GB	48GB	Optimal	25 tok/s	Calculate →
RX 7900 XTX	24GB	Optimal	45 tok/s	Calculate →
M4 Max 36GB	36GB	Optimal	25 tok/s	Calculate →
RTX 4070 Ti Super	16GB	Optimal	31 tok/s	Calculate →
RTX 3080 Ti	12GB	Optimal	33 tok/s	Calculate →
RX 7900 XT	20GB	Optimal	37 tok/s	Calculate →
RTX 5070	12GB	Optimal	31 tok/s	Calculate →
RTX 3080	10GB	Optimal	35 tok/s	Calculate →
M4 Pro	24GB	Optimal	13 tok/s	Calculate →
RX 7800 XT	16GB	Optimal	29 tok/s	Calculate →
RX 6800 XT	16GB	Optimal	20 tok/s	Calculate →
RTX 4070	12GB	Optimal	20 tok/s	Calculate →
RTX 4060 Ti 16GB	16GB	Optimal	13 tok/s	Calculate →
RX 7700 XT	12GB	Optimal	18 tok/s	Calculate →
RTX 3070 Ti	8GB	Optimal	23 tok/s	Calculate →
RTX 4060 Ti	8GB	Optimal	19 tok/s	Calculate →
RTX 3070	8GB	Optimal	19 tok/s	Calculate →
RX 6700 XT	12GB	Optimal	13 tok/s	Calculate →
M3 Pro	18GB	Optimal	7 tok/s	Calculate →
RTX 3060 Ti	8GB	Optimal	18 tok/s	Calculate →
RTX 2080 Ti	11GB	Optimal	16 tok/s	Calculate →
RTX 3060	12GB	Optimal	17 tok/s	Calculate →
M2 Pro	16GB	Optimal	9 tok/s	Calculate →
RTX 4060	8GB	Optimal	14 tok/s	Calculate →
Arc A770 16GB	16GB	Optimal	8 tok/s	Calculate →
M1 Pro	16GB	Optimal	9 tok/s	Calculate →
RX 7600	8GB	Optimal	12 tok/s	Calculate →
RX 6600 XT	8GB	Optimal	12 tok/s	Calculate →
Arc A750 8GB	8GB	Optimal	9 tok/s	Calculate →
RX 6600	8GB	Optimal	10 tok/s	Calculate →
RTX 3050 8GB	8GB	Optimal	9 tok/s	Calculate →
GTX 1660 Super	6GB	Optimal	11 tok/s	Calculate →

Recommended GPUs for Gemma 2 9B

Real Benchmarks

No Paid Reviews

Editorial Pick

Data-driven

Best picks by compatibility, VRAM headroom, and value — prices and availability may change.

RTX 5090

32 GB VRAM

Q4 native

Check availability →

RTX 4090

24 GB VRAM

Q4 native

Check availability →

M4 Ultra

128 GB VRAM

Q4 native

Check availability →

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Gemma 2 9B — Compatibility guide

A lightweight model like Gemma 2 9B runs well on consumer hardware from 6 GB VRAM. Ideal for daily use with Ollama or LM Studio. Use the VRAM calculator to check your setup.