FitMyLLM
Google/Dense

Googlegemma-2-9b

* [Responsible Generative AI Toolkit][rai-toolkit] * [Gemma on Kaggle][kaggle-gemma] * [Gemma on Vertex Model Garden][vertex-mg-gemma]

chatThinking
9.2B
Parameters
4K
Context length
9
Benchmarks
6
Quantizations
270K
HF downloads
Architecture
Dense
Released
2024-06-27
Layers
42
KV Heads
8
Head Dim
256
Family
gemma

Quantization Options

QuantBitsVRAM @ 4KQuality
Q4_K_M4.89
6.1 GB
good
Q5_K_S5.57
6.9 GB
good
Q5_K_M5.7
7.0 GB
good
Q6_K6.56
8.0 GB
excellent
Q8_08.5
10.3 GB
lossless
FP1616
18.9 GB
lossless

Select your GPU above to see speed estimates and compatibility for each quantization.

Deploying for a team or in production? Size GPUs, cost & scaling in Enterprise →
▸ READY TO RUN THIS?RENT BY THE HOUR

RENT A GPU AND RUN GEMMA-2-9B NOW

Spin up an A100 / H100 / 4090 in ~60s. Pay by the second. Cancel anytime.

Community Ratings

Loading ratings...

Benchmarks (9)

Arena Elo1455
IFEval74.4
BBH42.1
BigCodeBench34.7
MMLU-PRO31.9
MATH19.5
GPQA14.8
GPQA Diamond14.8
MUSR9.7

Run this model

▸Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run gemma2:9b-text-q4_K_M

Downloads and runs automatically. Add --verbose for speed stats.

▸ SETUP GUIDE
>_

Auto-setup with fitmyllm CLI

Detects your GPU, recommends the best model, downloads it, and starts chatting — zero config. Benchmarks your speed and contributes anonymous data to improve predictions.

pip install fitmyllmthen run fitmyllmLearn more
Auto-detect GPULive tok/s in chatSpeed benchmarks9 inference engines

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

Apple M1 (8GB)
8 GB VRAM • 68 GB/s
APPLE
$499
Apple M2 (8GB)
8 GB VRAM • 100 GB/s
APPLE
$599
Apple M3 (8GB)
8 GB VRAM • 100 GB/s
APPLE
$599
NVIDIA Tesla K8
8 GB VRAM • 160 GB/s
NVIDIA
NVIDIA Tesla M60
8 GB VRAM • 160 GB/s
NVIDIA

Find the best GPU for gemma-2-9b

Build Hardware for gemma-2-9b

* [Responsible Generative AI Toolkit][rai-toolkit] * [Gemma on Kaggle][kaggle-gemma] * [Gemma on Vertex Model Garden][vertex-mg-gemma]

▸ SPEC SHEET

gemma-2-9b — 9.2B Dense.

▸ SPECIFICATIONS
PARAMETERS
9.2B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
4K tokens
CAPABILITIES
chat
RELEASE DATE
2024-06-27
PROVIDER
Google
FAMILY
gemma
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q4_K_M4.896.1 GB94%
Q5_K_S5.576.9 GB96%
Q5_K_M5.77.0 GB96%
Q6_K6.568.0 GB97%
Q8_08.510.3 GB100%
FP161618.9 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO31.9
MATH19.5
IFEval74.4
BBH42.1
GPQA14.8
MUSR9.7
BigCodeBench34.7
Arena Elo1455.0
GPQA Diamond14.8
§ 02RUN COMMAND

Run gemma-2-9b locally with Ollama — needs 6.1 GB VRAM at Q4_K_M:

$ollama run gemma2:9b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M